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  • 1.
    Abraham-Nordling, Mirna
    et al.
    Karolinska institutet.
    Persson, Bengt
    Linköping University, Department of Physics, Chemistry and Biology, Bioinformatics. Linköping University, The Institute of Technology.
    Nordling, Erik
    Linköping University, Department of Physics, Chemistry and Biology, Bioinformatics. Linköping University, The Institute of Technology.
    Model of the complex of Parathyroid hormone-2receptor and Tuberoinfundibular peptide of39 residues2010In: BMC Reseach Notes, ISSN 1756-0500, Vol. 3, no 270Article in journal (Refereed)
    Abstract [en]

    Background

    We aim to propose interactions between the parathyroid hormone-2 receptor (PTH2R) and its ligand the tuberoinfundibular peptide of 39 residues (TIP39) by constructing a homology model of their complex. The two related peptides parathyroid hormone (PTH) and parathyroid hormone related protein (PTHrP) are compared with the complex to examine their interactions.

    Findings

    In the model, the hydrophobic N-terminus of TIP39 is buried in a hydrophobic part of the central cavity between helices 3 and 7. Comparison of the peptide sequences indicates that the main discriminator between the agonistic peptides TIP39 and PTH and the inactive PTHrP is a tryptophan-phenylalanine replacement. The model indicates that the smaller phenylalanine in PTHrP does not completely occupy the binding site of the larger tryptophan residue in the other peptides. As only TIP39 causes internalisation of the receptor and the primary difference being an aspartic acid in position 7 of TIP39 that interacts with histidine 396 in the receptor, versus isoleucine/histidine residues in the related hormones, this might be a trigger interaction for the events that cause internalisation.

    Conclusions

    A model is constructed for the complex and a trigger interaction for full agonistic activation between aspartic acid 7 of TIP39 and histidine 396 in the receptor is proposed.

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  • 2.
    Agirre, Jon
    et al.
    Univ York, England.
    Atanasova, Mihaela
    Univ York, England.
    Bagdonas, Haroldas
    Univ York, England.
    Ballard, Charles B.
    Rutherford Appleton Lab, England; Rutherford Appleton Lab, England.
    Basle, Arnaud
    Newcastle Univ, England.
    Beilsten-Edmands, James
    Diamond Light Source, England.
    Borges, Rafael J.
    Univ Campinas UNICAMP, Brazil.
    Brown, David G.
    Lab Servier SAS Inst Rech, France.
    Burgos-Marmol, J. Javier
    Univ Liverpool, England.
    Berrisford, John M.
    European Mol Biol Lab, England.
    Bond, Paul S.
    Univ York, England.
    Caballero, Iracema
    CSIC, Spain.
    Catapano, Lucrezia
    MRC Lab Mol Biol, England; Kings Coll London, England.
    Chojnowski, Grzegorz
    European Mol Biol Lab, Germany.
    Cook, Atlanta G.
    Univ Edinburgh, Scotland.
    Cowtan, Kevin D.
    Univ York, England.
    Croll, Tristan I.
    Univ Cambridge, England; Altos Labs, England.
    Debreczeni, Judit E.
    AstraZeneca, England.
    Devenish, Nicholas E.
    Diamond Light Source, England.
    Dodson, Eleanor J.
    Univ York, England.
    Drevon, Tarik R.
    Rutherford Appleton Lab, England; Rutherford Appleton Lab, England.
    Emsley, Paul
    MRC Lab Mol Biol, England.
    Evans, Gwyndaf
    Diamond Light Source, England; Rosalind Franklin Inst, England.
    Evans, Phil R.
    MRC Lab Mol Biol, England.
    Fando, Maria
    Rutherford Appleton Lab, England; Rutherford Appleton Lab, England.
    Foadi, James
    Univ Bath, England.
    Fuentes-Montero, Luis
    Diamond Light Source, England.
    Garman, Elspeth F.
    Univ Oxford, England.
    Gerstel, Markus
    Diamond Light Source, England.
    Gildea, Richard J.
    Diamond Light Source, England.
    Hatti, Kaushik
    Univ Cambridge, England.
    Hekkelman, Maarten L.
    Netherlands Canc Inst, Netherlands; Netherlands Canc Inst, Netherlands.
    Heuser, Philipp
    DESY, Germany.
    Hoh, Soon Wen
    Univ York, England.
    Hough, Michael A.
    Diamond Light Source, England; Univ Essex, England.
    Jenkins, Huw T.
    Univ York, England.
    Jimenez, Elisabet
    CSIC, Spain.
    Joosten, Robbie P.
    Netherlands Canc Inst, Netherlands; Netherlands Canc Inst, Netherlands.
    Keegan, Ronan M.
    Rutherford Appleton Lab, England; Rutherford Appleton Lab, England; Univ Liverpool, England.
    Keep, Nicholas
    Birkbeck Coll, England.
    Krissinel, Eugene B.
    Rutherford Appleton Lab, England; Rutherford Appleton Lab, England.
    Kolenko, Petr
    Czech Tech Univ, Czech Republic; Czech Acad Sci, Czech Republic.
    Kovalevskiy, Oleg
    Rutherford Appleton Lab, England; Rutherford Appleton Lab, England.
    Lamzin, Victor S.
    European Mol Biol Lab, Germany.
    Lawson, David M.
    John Innes Ctr, England.
    Lebedev, Andrey A.
    Rutherford Appleton Lab, England; Rutherford Appleton Lab, England.
    Leslie, Andrew G. W.
    MRC Lab Mol Biol, England.
    Lohkamp, Bernhard
    Karolinska Inst, Sweden.
    Long, Fei
    MRC Lab Mol Biol, England.
    Maly, Martin
    Czech Tech Univ, Czech Republic; Czech Acad Sci, Czech Republic; Univ Southampton, England.
    McCoy, Airlie J.
    Univ Cambridge, England.
    McNicholas, Stuart J.
    Univ York, England.
    Medina, Ana
    CSIC, Spain.
    Millan, Claudia
    Univ Cambridge, England.
    Murray, James W.
    Imperial Coll London, England.
    Murshudov, Garib N.
    MRC Lab Mol Biol, England.
    Nicholls, Robert A.
    MRC Lab Mol Biol, England.
    Noble, Martin E. M.
    Newcastle Univ, England.
    Oeffner, Robert
    Univ Cambridge, England.
    Pannu, Navraj S.
    Leiden Univ, Netherlands.
    Parkhurst, James M.
    Diamond Light Source, England; Rosalind Franklin Inst, England.
    Pearce, Nicholas
    Linköping University, Department of Physics, Chemistry and Biology, Bioinformatics. Linköping University, Faculty of Science & Engineering.
    Pereira, Joana
    Univ Basel, Switzerland; Univ Basel, Switzerland.
    Perrakis, Anastassis
    Netherlands Canc Inst, Netherlands; Netherlands Canc Inst, Netherlands.
    Powell, Harold R.
    Imperial Coll London, England.
    Read, Randy J.
    Univ Cambridge, England.
    Rigden, Daniel J.
    Univ Liverpool, England.
    Rochira, William
    Univ York, England.
    Sammito, Massimo
    Univ Cambridge, England; AstraZeneca, England.
    Rodriguez, Filomeno Sanchez
    Univ York, England; Diamond Light Source, England; Univ Liverpool, England.
    Sheldrick, George M.
    Georg August Univ Gottingen, Germany.
    Shelley, Kathryn L.
    Univ Washington, WA 98195 USA.
    Simkovic, Felix
    Univ Liverpool, England.
    Simpkin, Adam J.
    Lab Servier SAS Inst Rech, France.
    Skubak, Pavol
    Leiden Univ, Netherlands.
    Sobolev, Egor
    DESY, Germany.
    Steiner, Roberto A.
    European Mol Biol Lab, England; Univ Padua, Italy.
    Stevenson, Kyle
    Rutherford Appleton Lab, England.
    Tews, Ivo
    Univ Southampton, England.
    Thomas, Jens M. H.
    Univ Liverpool, England.
    Thorn, Andrea
    Univ Hamburg, Germany.
    Trivino Valls, Josep
    CSIC, Spain.
    Uski, Ville
    Rutherford Appleton Lab, England; Rutherford Appleton Lab, England.
    Uson, Isabel
    CSIC, Spain; ICREA, Spain.
    Vagin, Alexei
    Univ York, England.
    Velankar, Sameer
    European Mol Biol Lab, England.
    Vollmar, Melanie
    European Mol Biol Lab, England.
    Walden, Helen
    Univ Glasgow, Scotland.
    Waterman, David
    Rutherford Appleton Lab, England; Rutherford Appleton Lab, England.
    Wilson, Keith S.
    Univ York, England.
    Winn, Martyn D.
    Sci & Technol Facil Council, England.
    Winter, Graeme
    Diamond Light Source, England.
    Wojdyr, Marcin
    Global Phasing Ltd, England.
    Yamashita, Keitaro
    MRC Lab Mol Biol, England.
    The CCP4 suite: integrative software for macromolecular crystallography2023In: Acta Crystallographica Section D: Structural Biology , E-ISSN 2059-7983, Vol. 79, p. 449-461Article in journal (Refereed)
    Abstract [en]

    The Collaborative Computational Project No. 4 (CCP4) is a UK-led international collective with a mission to develop, test, distribute and promote software for macromolecular crystallography. The CCP4 suite is a multiplatform collection of programs brought together by familiar execution routines, a set of common libraries and graphical interfaces. The CCP4 suite has experienced several considerable changes since its last reference article, involving new infrastructure, original programs and graphical interfaces. This article, which is intended as a general literature citation for the use of the CCP4 software suite in structure determination, will guide the reader through such transformations, offering a general overview of the new features and outlining future developments. As such, it aims to highlight the individual programs that comprise the suite and to provide the latest references to them for perusal by crystallographers around the world.

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  • 3.
    Al-Absi, Thabit
    Linköping University, Department of Physics, Chemistry and Biology, Bioinformatics. Linköping University, The Institute of Technology.
    Efficient Characterization of Short Anelloviruses Fragments Found in Metagenomic Samples2012Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    Some viral metagenomic serum samples contain a huge amount of Anellovirus, which is a genetically diverse family with a few conserved regions making it hard to efficiently characterize. Multiple sequence alignment of the Anelloviruses found in the sample must be constructed to get a clear picture of Anellovirus diversity and to identify stable regions. Using available multiple sequence alignment software directly on these fragments results in an MSA of a very poor quality due to their diversity, misaligned regions and low-quality regions present in the sequence.

    An efficient MSA must be constructed in order to characterize these Anellovirus present in the samples. Pairwise alignment is used to align one fragment to the database sequences at a time. The fragments are then aligned to the database sequences using the start and end position from the pairwise alignment results. The algorithm will also exclude non-aligned portions of the fragments, as these are very hard to handle properly and are often products of misassembly or chimeric sequenced fragments. Other tools to aid further analysis were developed, such as finding a non-overlapping window that contains the most fragments, find consensus of the alignment and extract any regions from the MSA for further analysis.

    An MSA was constructed with a high percent of correctly aligned bases compared to an MSA constructed using MSA softwares. The minimal number of genomes found in the sampled sequence was found as well as a distribution of the fragments along the database sequence. Moreover, highly conserved region and the window containing most fragments were extracted from the MSA and phylogenetic trees were constructed for these regions. 

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  • 4.
    Alexsson, Andrei
    Linköping University, Department of Physics, Chemistry and Biology, Bioinformatics .
    Unsupervised hidden Markov model for automatic analysis of expressed sequence tags2011Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    This thesis provides an in-depth analyze of expressed sequence tags (EST) that represent pieces of eukaryotic mRNA by using unsupervised hidden Markov model (HMM). ESTs are short nucleotide sequences that are used primarily for rapid identificationof new genes with potential coding regions (CDS). ESTs are made by sequencing on double-stranded cDNA and the synthesizedESTs are stored in digital form, usually in FASTA format. Since sequencing is often randomized and that parts of mRNA contain non-coding regions, some ESTs will not represent CDS.It is desired to remove these unwanted ESTs if the purpose is to identifygenes associated with CDS. Application of stochastic HMM allow identification of region contents in a EST. Softwares like ESTScanuse HMM in which a training of the HMM is done by supervised learning with annotated data. However, because there are not always annotated data at hand this thesis focus on the ability to train an HMM with unsupervised learning on data containing ESTs, both with and without CDS. But the data used for training is not annotated, i.e. the regions that an EST consists of are unknown. In this thesis a new HMM is introduced where the parameters of the HMM are in focus so that they are reasonablyconsistent with biologically important regionsof an mRNA such as the Kozak sequence, poly(A)-signals and poly(A)-tails to guide the training and decoding correctly with ESTs to proper statesin the HMM. Transition probabilities in the HMMhas been adapted so that it represents the mean length and distribution of the different regions in mRNA. Testing of the HMM's specificity and sensitivityhave been performed via BLAST by blasting each EST and compare the BLAST results with the HMM prediction results.A regression analysis test shows that the length of ESTs used when training the HMM is significantly important, the longer the better. The final resultsshows that it is possible to train an HMM with unsupervised machine learning but to be comparable to supervised machine learning as ESTScan, further expansion of the HMM is necessary such as frame-shift correction of ESTs byimproving the HMM's ability to choose correctly positioned start codons or nucleotides. Usually the false positive results are because of incorrectly positioned start codons leadingto too short CDS lengths. Since no frame-shift correction is implemented, short predicted CDS lengths are not acceptable and is hence not counted as coding regionsduring prediction. However, when there is a lack of supervised models then unsupervised HMM is a potential replacement with stable performance and able to be adapted forany eukaryotic organism.

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    Master Thesis
  • 5.
    Almgren, Malin
    et al.
    Karolinska Institutet.
    Nyengaard, Jens R
    Aarhus University.
    Persson, Bengt
    Linköping University, The Institute of Technology. Linköping University, Department of Physics, Chemistry and Biology, Bioinformatics .
    Lavebratt, Catharina
    Karolinska Institutet.
    Carbamazepine protects against neuronal hyperplasia and abnormal gene expression in the megencephaly mouse2008In: Neurobiology of Disease, ISSN 0969-9961, E-ISSN 1095-953X, Vol. 32, p. 364-376Article in journal (Refereed)
  • 6.
    Almstedt, Karin
    et al.
    Linköping University, Department of Physics, Chemistry and Biology, Biochemistry. Linköping University, The Institute of Technology.
    Lundqvist, Martin
    Linköping University, Department of Physics, Chemistry and Biology, Molecular Biotechnology . Linköping University, The Institute of Technology.
    Carlsson, Jonas
    Linköping University, Department of Physics, Chemistry and Biology, Bioinformatics . Linköping University, The Institute of Technology.
    Karlsson, Martin
    Linköping University, Department of Physics, Chemistry and Biology, Biochemistry. Linköping University, The Institute of Technology.
    Persson, Bengt
    Linköping University, Department of Physics, Chemistry and Biology, Bioinformatics . Linköping University, The Institute of Technology.
    Jonsson, Bengt-Harald
    Linköping University, Department of Physics, Chemistry and Biology, Molecular Biotechnology . Linköping University, The Institute of Technology.
    Carlsson, Uno
    Linköping University, Department of Physics, Chemistry and Biology, Biochemistry. Linköping University, The Institute of Technology.
    Hammarström, Per
    Linköping University, Department of Physics, Chemistry and Biology, Biochemistry. Linköping University, The Institute of Technology.
    Unfolding a folding disease: folding, misfolding and aggregation of the marble brain syndrome-associated mutant H107Y of human carbonic anhydrase II2004In: Journal of Molecular Biology, ISSN 0022-2836, E-ISSN 1089-8638, Vol. 342, no 2, p. 619-633Article in journal (Refereed)
    Abstract [en]

    Most loss-of-function diseases are caused by aberrant folding of important proteins. These proteins often misfold due to mutations. The disease marble brain syndrome (MBS), known also as carbonic anhydrase II deficiency syndrome (CADS), can manifest in carriers of point mutations in the human carbonic anhydrase II (HCA II) gene. One mutation associated with MBS entails the His107Tyr substitution. Here, we demonstrate that this mutation is a remarkably destabilizing folding mutation. The loss-of-function is clearly a folding defect, since the mutant shows 64% of CO2 hydration activity compared to that of the wild-type at low temperature where the mutant is folded. On the contrary, its stability towards thermal and guanidine hydrochloride (GuHCl) denaturation is highly compromised. Using activity assays, CD, fluorescence, NMR, cross-linking, aggregation measurements and molecular modeling, we have mapped the properties of this remarkable mutant. Loss of enzymatic activity had a midpoint temperature of denaturation (Tm) of 16 °C for the mutant compared to 55 °C for the wild-type protein. GuHCl-denaturation (at 4 °C) showed that the native state of the mutant was destabilized by 9.2 kcal/mol. The mutant unfolds through at least two equilibrium intermediates; one novel intermediate that we have termed the molten globule light state and, after further denaturation, the classical molten globule state is populated. Under physiological conditions (neutral pH; 37 °C), the His107Tyr mutant will populate the molten globule light state, likely due to novel interactions between Tyr107 and the surroundings of the critical residue Ser29 that destabilize the native conformation. This intermediate binds the hydrophobic dye 8-anilino-1-naphthalene sulfonic acid (ANS) but not as strong as the molten globule state, and near-UV CD reveals the presence of significant tertiary structure. Notably, this intermediate is not as prone to aggregation as the classical molten globule. As a proof of concept for an intervention strategy with small molecules, we showed that binding of the CA inhibitor acetazolamide increases the stability of the native state of the mutant by 2.9 kcal/mol in accordance with its strong affinity. Acetazolamide shifts the Tm to 34 °C that protects from misfolding and will enable a substantial fraction of the enzyme pool to survive physiological conditions.

  • 7.
    Anandapadmanaban, Madhanagopal
    et al.
    Linköping University, Department of Physics, Chemistry and Biology. Linköping University, Faculty of Science & Engineering.
    Pilstål, Robert
    Linköping University, Department of Physics, Chemistry and Biology, Bioinformatics. Linköping University, Faculty of Science & Engineering.
    Andrésen, Cecilia
    Linköping University, Department of Physics, Chemistry and Biology, Chemistry. Linköping University, Faculty of Science & Engineering.
    Trewhella, Jill
    Linköping University, Department of Physics, Chemistry and Biology, Chemistry. Linköping University, Faculty of Science & Engineering. University of Sydney, Australia.
    Moche, Martin
    Karolinska Institute, Sweden.
    Wallner, Björn
    Linköping University, Department of Physics, Chemistry and Biology, Bioinformatics. Linköping University, Faculty of Science & Engineering.
    Sunnerhagen, Maria
    Linköping University, Department of Physics, Chemistry and Biology, Chemistry. Linköping University, Faculty of Science & Engineering.
    Mutation-Induced Population Shift in the MexR Conformational Ensemble Disengages DNA Binding: A Novel Mechanism for MarR Family Derepression2016In: Structure, ISSN 0969-2126, E-ISSN 1878-4186, Vol. 24, no 8, p. 1311-1321Article in journal (Refereed)
    Abstract [en]

    MexR is a repressor of the MexAB-OprM multidrug efflux pump operon of Pseudomonas aeruginosa, where DNA-binding impairing mutations lead to multidrug resistance (MDR). Surprisingly, the crystal structure of an MDR-conferring MexR mutant R21W (2.19 angstrom) presented here is closely similar to wildtype MexR. However, our extended analysis, by molecular dynamics and small-angle X-ray scattering, reveals that the mutation stabilizes a ground state that is deficient of DNA binding and is shared by both mutant and wild-type MexR, whereas the DNA-binding state is only transiently reached by the more flexible wild-type MexR. This population shift in the conformational ensemble is effected by mutation-induced allosteric coupling of contact networks that are independent in the wild-type protein. We propose that the MexR-R21W mutant mimics derepression by small-molecule binding to MarR proteins, and that the described allosteric model based on population shifts may also apply to other MarR family members.

  • 8.
    Andrésen, Cecilia
    et al.
    Linköping University, Department of Physics, Chemistry and Biology, Molecular Biotechnology. Linköping University, The Institute of Technology.
    Helander, Sara
    Linköping University, Department of Physics, Chemistry and Biology, Chemistry. Linköping University, Faculty of Science & Engineering.
    Lemak, Alexander
    University of Toronto, Canada .
    Fares, Christophe
    University of Toronto, Canada .
    Csizmok, Veronika
    Hospital for Sick Children, Canada .
    Carlsson, Jonas
    Linköping University, Department of Physics, Chemistry and Biology, Bioinformatics. Linköping University, The Institute of Technology.
    Penn, Linda Z
    University of Toronto, Canada .
    Forman-Kay, Julie D
    Hospital Sick Children, Canada University of Toronto, Canada .
    Arrowsmith, Cheryl H
    University of Toronto, Canada.
    Lundström, Patrik
    Linköping University, Department of Physics, Chemistry and Biology, Molecular Biotechnology. Linköping University, The Institute of Technology.
    Sunnerhagen, Maria
    Linköping University, Department of Physics, Chemistry and Biology, Molecular Biotechnology. Linköping University, The Institute of Technology.
    Transient structure and dynamics in the disordered c-Myc transactivation domain affect Bin1 binding2012In: Nucleic Acids Research, ISSN 0305-1048, E-ISSN 1362-4962, Vol. 40, no 13, p. 6353-6366Article in journal (Refereed)
    Abstract [en]

    The crucial role of Myc as an oncoprotein and as a key regulator of cell growth makes it essential to understand the molecular basis of Myc function. The N-terminal region of c-Myc coordinates a wealth of protein interactions involved in transformation, differentiation and apoptosis. We have characterized in detail the intrinsically disordered properties of Myc-1-88, where hierarchical phosphorylation of S62 and T58 regulates activation and destruction of the Myc protein. By nuclear magnetic resonance (NMR) chemical shift analysis, relaxation measurements and NOE analysis, we show that although Myc occupies a very heterogeneous conformational space, we find transiently structured regions in residues 22-33 and in the Myc homology box I (MBI; residues 45-65); both these regions are conserved in other members of the Myc family. Binding of Bin1 to Myc-1-88 as assayed by NMR and surface plasmon resonance (SPR) revealed primary binding to the S62 region in a dynamically disordered and multivalent complex, accompanied by population shifts leading to altered intramolecular conformational dynamics. These findings expand the increasingly recognized concept of intrinsically disordered regions mediating transient interactions to Myc, a key transcriptional regulator of major medical importance, and have important implications for further understanding its multifaceted role in gene regulation.

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  • 9.
    Andrésen, Cecilia
    et al.
    Linköping University, Department of Physics, Chemistry and Biology, Chemistry. Linköping University, Faculty of Science & Engineering.
    Niklasson, Markus
    Linköping University, Department of Physics, Chemistry and Biology, Chemistry. Linköping University, Faculty of Science & Engineering.
    Cassman Eklöf, Sofie
    Linköping University, Department of Physics, Chemistry and Biology, Chemistry. Linköping University, Faculty of Science & Engineering.
    Wallner, Björn
    Linköping University, Department of Physics, Chemistry and Biology, Bioinformatics. Linköping University, Faculty of Science & Engineering.
    Lundström, Patrik
    Linköping University, Department of Physics, Chemistry and Biology, Chemistry. Linköping University, Faculty of Science & Engineering.
    Biophysical characterization of the calmodulin-like domain of Plasmodium falciparum calcium dependent protein kinase 32017In: PLOS ONE, E-ISSN 1932-6203, Vol. 12, no 7, article id e0181721Article in journal (Refereed)
    Abstract [en]

    Calcium dependent protein kinases are unique to plants and certain parasites and comprise an N-terminal segment and a kinase domain that is regulated by a C-terminal calcium binding domain. Since the proteins are not found in man they are potential drug targets. We have characterized the calcium binding lobes of the regulatory domain of calcium dependent protein kinase 3 from the malaria parasite Plasmodium falciparum. Despite being structurally similar, the two lobes differ in several other regards. While the monomeric N-terminal lobe changes its structure in response to calcium binding and shows global dynamics on the sub-millisecond time-scale both in its apo and calcium bound states, the C-terminal lobe could not be prepared calcium-free and forms dimers in solution. If our results can be generalized to the full-length protein, they suggest that the C-terminal lobe is calcium bound even at basal levels and that activation is caused by the structural reorganization associated with binding of a single calcium ion to the N-terminal lobe.

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  • 10.
    Apostolopoulou-Kalkavoura, Varvara
    et al.
    Stockholm Univ, Sweden.
    Hu, Shiqian
    Univ Tokyo, Japan.
    Lavoine, Nathalie
    NC State Univ, NC 27695 USA.
    Garg, Mohit
    Linköping University, Department of Science and Technology, Laboratory of Organic Electronics. Linköping University, Faculty of Science & Engineering.
    Linares, Mathieu
    Linköping University, Department of Physics, Chemistry and Biology, Bioinformatics. Linköping University, Faculty of Science & Engineering.
    Munier, Pierre
    Stockholm Univ, Sweden.
    Zozoulenko, Igor
    Linköping University, Department of Science and Technology, Laboratory of Organic Electronics. Linköping University, Faculty of Science & Engineering.
    Shiomi, Junichiro
    Univ Tokyo, Japan.
    Bergstrom, Lennart
    Stockholm Univ, Sweden.
    Humidity-Dependent Thermal Boundary Conductance Controls Heat Transport of Super-Insulating Nanofibrillar Foams2021In: Matter, ISSN 2590-2393, E-ISSN 2590-2385, Vol. 4, no 1Article in journal (Refereed)
    Abstract [en]

    Cellulose nanomaterial (CNM)-based foams and aerogels with thermal conductivities substantially below the value for air attract significant interest as super-insulating materials in energy-efficient green buildings. However, the moisture dependence of the thermal conductivity of hygroscopic CNM-based materials is poorly understood, and the importance of phonon scattering in nanofibrillar foams remains unexplored. Here, we show that the thermal conductivity perpendicular to the aligned nanofibrils in super-insulating icetemplated nanocellulose foams is lower for thinner fibrils and depends strongly on relative humidity (RH), with the lowest thermal conductivity (14 mW m(-1) K-1) attained at 35% RH. Molecular simulations show that the thermal boundary conductance is reduced by the moisture-uptake-controlled increase of the fibril-fibril separation distance and increased by the replacement of air with water in the foam walls. Controlling the heat transport of hygroscopic super-insulating nanofibrillar foams by moisture uptake and release is of potential interest in packaging and building applications.

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  • 11.
    Arpa Gonzalez, Enrique Manuel
    et al.
    Linköping University, Department of Physics, Chemistry and Biology, Bioinformatics. Linköping University, Faculty of Science & Engineering. Univ Autonoma Madrid, Spain.
    Corral, Ines
    Univ Autonoma Madrid, Spain.
    Unveiling Photodegradation and Photosensitization Mechanisms of Unconjugated Pterins2023In: Chemistry - A European Journal, ISSN 0947-6539, E-ISSN 1521-3765Article in journal (Other academic)
    Abstract [en]

    Invited for the cover of this issue are Enrique M. Arpa (Linkoping University) and Ines Corral (Universidad Autonoma de Madrid). The image depicts two examples where pterin chemistry is relevant, the wing coloration of some butterflies and the cytotoxic action in vitiligo. Read the full text of the article at 10.1002/chem.202300519.

  • 12.
    Arpa Gonzalez, Enrique Manuel
    et al.
    Linköping University, Department of Physics, Chemistry and Biology, Bioinformatics. Linköping University, Faculty of Science & Engineering. Univ Autonoma Madrid, Spain.
    Corral, Ines
    Univ Autonoma Madrid, Spain; Univ Autonoma Madrid, Spain.
    Unveiling Photodegradation and Photosensitization Mechanisms of Unconjugated Pterins2023In: Chemistry - A European Journal, ISSN 0947-6539, E-ISSN 1521-3765, Vol. 29, no 29, article id e202300519Article in journal (Refereed)
    Abstract [en]

    Unconjugated pterins are ubiquitous molecules that participate in countless enzymatic processes and are potentially involved in the photosensitization of singlet oxygen, amino acids, and nucleotides. Following electronic excitation with UV-A light, some of these pterins degrade, producing hydrogen peroxide as the main side product. This process, which is known to take place in vivo, contributes to oxidative stress and melanocyte destruction in vitiligo. In this work, we present for the first time mechanistic insight into the formation of transient triplet species that simultaneously trigger Type I and Type II photosensitizing processes and the initiation of degradation processes. Our calculations reveal that photodegradation of 6-biopterin, which accumulates in the skin of vitiligo patients, leads to 6-formylpterin through a retro-aldol reaction, and subsequently to 6-carboxypterin through a water-mediated aldehyde oxidation. Additionally, we show that the changes in the photosensitizing potential of these systems with pH come from the modulation of their excited-state redox potentials.

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  • 13.
    Arpa Gonzalez, Enrique Manuel
    et al.
    Linköping University, Department of Physics, Chemistry and Biology, Bioinformatics. Linköping University, Faculty of Science & Engineering.
    Durbeej, Bo
    Linköping University, Department of Physics, Chemistry and Biology, Bioinformatics. Linköping University, Faculty of Science & Engineering.
    HOMER: a reparameterization of the harmonic oscillator model of aromaticity (HOMA) for excited states2023In: Physical Chemistry, Chemical Physics - PCCP, ISSN 1463-9076, E-ISSN 1463-9084, Vol. 25, no 25, p. 16763-16771Article in journal (Refereed)
    Abstract [en]

    Excited-state aromaticity (ESA) and antiaromaticity (ESAA) are by now well-established concepts for explaining photophysical properties and photochemical reactivities of cyclic, conjugated molecules. However, their application is less straightforward than the corresponding process by which the thermal chemistry of such systems is rationalized in terms of ground-state aromaticity (GSA) and antiaromaticity (GSAA). Recognizing that the harmonic oscillator model of aromaticity (HOMA) provides an easy way to measure aromaticity on geometric grounds, it is therefore notable that this model is yet to be parameterized for excited states. Against this background, we here present a new parameterization of HOMA - termed HOMER - for the T-1 state of both carbocyclic and heterocyclic compounds based on high-level quantum-chemical calculations. Considering CC, CN, NN and CO bonds and testing the parametrization using calculated magnetic data as reference, we find that the description of ESA and ESAA by HOMER is superior to that afforded by the original HOMA scheme, and that it reaches the same overall quality as HOMA does for GSA and GSAA. Furthermore, we demonstrate that the derived HOMER parameters can be used for predictive modeling of ESA and ESAA at very different levels of theory. Altogether, the results highlight the potential of HOMER to facilitate future studies of ESA and ESAA.

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  • 14.
    Arpa Gonzalez, Enrique Manuel
    et al.
    Linköping University, Department of Physics, Chemistry and Biology, Bioinformatics. Linköping University, Faculty of Science & Engineering.
    Stafström, Sven
    Linköping University, Department of Physics, Chemistry and Biology, Theoretical Physics. Linköping University, Faculty of Science & Engineering.
    Durbeej, Bo
    Linköping University, Department of Physics, Chemistry and Biology, Bioinformatics. Linköping University, Faculty of Science & Engineering.
    A Proof-of-Principle Design for Through-Space Transmission of Unidirectional Rotary Motion by Molecular Photogears2023In: Chemistry - A European Journal, ISSN 0947-6539, E-ISSN 1521-3765Article in journal (Refereed)
    Abstract [en]

    The construction of molecular photogears that can achieve through-space transmission of the unidirectional double-bond rotary motion of light-driven molecular motors onto a remote single-bond axis is a formidable challenge in the field of artificial molecular machines. Here, we present a proof-of-principle design of such photogears that is based on the possibility of using stereogenic substituents to control both the relative stabilities of two helical forms of the photogear and the double-bond photoisomerization reaction that connects them. The potential of the design was verified by quantum-chemical modeling through which photogearing was found to be a favorable process compared to free-standing single-bond rotation ("slippage"). Overall, our study unveils a surprisingly simple approach to realizing unidirectional photogearing. A stereochemical approach to transmitting the directional double-bond rotary motion of light-driven molecular motors through space onto a remote single-bond axis is put forth and successfully tested by means of quantum-chemical modeling. A key result in the assessment of the approach is that the desired photogearing process is favorable compared to the undesired, free-standing single-bond rotation process ("slippage") with which it competes.**image

  • 15.
    Arpa González, Enrique Manuel
    et al.
    Linköping University, Department of Physics, Chemistry and Biology, Bioinformatics. Linköping University, Faculty of Science & Engineering.
    Durbeej, Bo
    Linköping University, Department of Physics, Chemistry and Biology, Bioinformatics. Linköping University, Faculty of Science & Engineering.
    In Silico Design of Dihydroazulene/Vinylheptafulvene Photoswitches for Solar-Energy Storage Guided by an All-Around Performance Descriptor2023In: Chemistry−Methods, ISSN 2628-9725, Vol. 3, article id e202200060Article in journal (Refereed)
    Abstract [en]

    A major challenge in the development of molecular photoswitches capable of storing and releasing solar energy is to simultaneously realize many of the performance criteria required of the switches for such applications. Here, we take on this challenge by introducing an all-around performance descriptor that combines three key criteria (related to energy density, storage time and light-absorption characteristics), and by using density functional theory methods to calculate its values for 52 newly designed dihydroazulene/vinylheptafulvene (DHA/VHF) switches. Thereby, we are able to identify several switches with excellent overall properties that contain a structural motif absent in all DHA/VHF compounds previously considered for solar-energy storage. For some of these switches, we also provide retrosynthetic analyses and demonstrate that they form the energy-storing VHF isomer through a facile DHA!VHF photoisomerization reaction. All in all, we conclude that these switches show great promise for further development towards applications in solar-energy storage.

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  • 16.
    Arpa González, Enrique Manuel
    et al.
    Linköping University, Department of Physics, Chemistry and Biology, Bioinformatics. Linköping University, Faculty of Science & Engineering.
    Durbeej, Bo
    Linköping University, Department of Physics, Chemistry and Biology, Bioinformatics. Linköping University, Faculty of Science & Engineering.
    Transient changes in aromaticity and their effect on excited-state proton transfer reactions2022In: Physical Chemistry, Chemical Physics - PCCP, ISSN 1463-9076, E-ISSN 1463-9084, Vol. 24, no 19, p. 11496-11500Article in journal (Refereed)
    Abstract [en]

    The common approach to investigate the impact of aromaticity on excited-state proton transfer by probing the (anti)aromatic character of reactants and products alone is scrutinized by modelling such reactions involving 2-pyridone. Thereby, it is found that energy barriers can be strongly influenced by transient changes in aromaticity unaccounted for by this approach, particularly when the photoexcited state interacts with a second excited state. Overall, the modelling identifies a pronounced effect overlooked by most studies on this topic.

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  • 17.
    Augusto Berrocal, Jose
    et al.
    Eindhoven University of Technology, Netherlands.
    Di Meo, Florent
    Linköping University, Department of Physics, Chemistry and Biology, Theoretical Chemistry. Linköping University, Faculty of Science & Engineering. University of Limoges, France.
    Garcia-Iglesias, Miguel
    Eindhoven University of Technology, Netherlands.
    Gosens, Ronald P. J.
    Eindhoven University of Technology, Netherlands.
    Meijer, E. W.
    Eindhoven University of Technology, Netherlands.
    Linares, Mathieu
    Linköping University, Department of Physics, Chemistry and Biology, Bioinformatics. Linköping University, Faculty of Science & Engineering.
    Palmans, Anja R. A.
    Eindhoven University of Technology, Netherlands.
    Consequences of conformational flexibility in hydrogen-bond-driven self-assembly processes2016In: Chemical Communications, ISSN 1359-7345, E-ISSN 1364-548X, Vol. 52, no 72, p. 10870-10873Article in journal (Refereed)
    Abstract [en]

    We report the synthesis and self-assembly of chiral, conformationally flexible C-3-symmetrical trisamides. A strong Cotton effect is observed for the supramolecular polymers in linear alkanes but not in cyclic alkanes. MD simulations suggest 2:1 conformations of the amides within the aggregates in both types of solvents, but a chiral bias in only linear alkanes.

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  • 18.
    Badam, Tejaswi
    et al.
    Linköping University, Department of Physics, Chemistry and Biology, Bioinformatics. Linköping University, Faculty of Science & Engineering. Univ Skovde, Sweden.
    de Weerd, Hendrik Arnold
    Linköping University, Department of Physics, Chemistry and Biology, Bioinformatics. Linköping University, Faculty of Science & Engineering. Univ Skovde, Sweden.
    Martinez, David
    Linköping University, Department of Physics, Chemistry and Biology, Bioinformatics. Linköping University, Faculty of Science & Engineering.
    Olsson, Tomas
    Karolinska Inst, Sweden.
    Alfredsson, Lars
    Karolinska Inst, Sweden; Karolinska Inst, Sweden.
    Kockum, Ingrid
    Karolinska Inst, Sweden.
    Jagodic, Maja
    Karolinska Inst, Sweden.
    Lubovac-Pilav, Zelmina
    Univ Skovde, Sweden.
    Gustafsson, Mika
    Linköping University, Department of Physics, Chemistry and Biology, Bioinformatics. Linköping University, Faculty of Science & Engineering.
    A validated generally applicable approach using the systematic assessment of disease modules by GWAS reveals a multi-omic module strongly associated with risk factors in multiple sclerosis2021In: BMC Genomics, E-ISSN 1471-2164, Vol. 22, no 1, article id 631Article in journal (Refereed)
    Abstract [en]

    Background There exist few, if any, practical guidelines for predictive and falsifiable multi-omic data integration that systematically integrate existing knowledge. Disease modules are popular concepts for interpreting genome-wide studies in medicine but have so far not been systematically evaluated and may lead to corroborating multi-omic modules. Result We assessed eight module identification methods in 57 previously published expression and methylation studies of 19 diseases using GWAS enrichment analysis. Next, we applied the same strategy for multi-omic integration of 20 datasets of multiple sclerosis (MS), and further validated the resulting module using both GWAS and risk-factor-associated genes from several independent cohorts. Our benchmark of modules showed that in immune-associated diseases modules inferred from clique-based methods were the most enriched for GWAS genes. The multi-omic case study using MS data revealed the robust identification of a module of 220 genes. Strikingly, most genes of the module were differentially methylated upon the action of one or several environmental risk factors in MS (n = 217, P = 10(- 47)) and were also independently validated for association with five different risk factors of MS, which further stressed the high genetic and epigenetic relevance of the module for MS. Conclusions We believe our analysis provides a workflow for selecting modules and our benchmark study may help further improvement of disease module methods. Moreover, we also stress that our methodology is generally applicable for combining and assessing the performance of multi-omic approaches for complex diseases.

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  • 19.
    Badam, Tejaswi
    et al.
    Linköping University, Department of Physics, Chemistry and Biology, Bioinformatics. Linköping University, Faculty of Science & Engineering. Skovde Univ, Sweden.
    Hellberg, Sandra
    Linköping University, Department of Physics, Chemistry and Biology, Bioinformatics. Linköping University, Faculty of Science & Engineering.
    Bhai Mehta, Ratnesh
    Linköping University, Department of Biomedical and Clinical Sciences, Division of Inflammation and Infection. Linköping University, Faculty of Medicine and Health Sciences.
    Lechner-Scott, Jeannette
    Univ Newcastle, Australia; Hunter Med Res Inst, Australia; John Hunter Hosp, Australia.
    Lea, Rodney A.
    Univ Newcastle, Australia; Hunter Med Res Inst, Australia; Queensland Univ Technol, Australia.
    Tost, Jorg
    CEA Inst Biol Francois Jacob, France.
    Mariette, Xavier
    Univ Paris Saclay, France.
    Svensson-Arvelund, Judit
    Linköping University, Department of Biomedical and Clinical Sciences, Division of Inflammation and Infection. Linköping University, Faculty of Medicine and Health Sciences.
    Nestor, Colm
    Linköping University, Department of Biomedical and Clinical Sciences, Division of Children's and Women's Health. Linköping University, Faculty of Medicine and Health Sciences.
    Benson, Mikael
    Linköping University, Department of Biomedical and Clinical Sciences, Division of Children's and Women's Health. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center of Paediatrics and Gynaecology and Obstetrics, H.K.H. Kronprinsessan Victorias barn- och ungdomssjukhus.
    Berg, Göran
    Linköping University, Department of Biomedical and Clinical Sciences, Division of Children's and Women's Health. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center of Paediatrics and Gynaecology and Obstetrics, Department of Gynaecology and Obstetrics in Linköping.
    Jenmalm, Maria
    Linköping University, Department of Biomedical and Clinical Sciences, Division of Inflammation and Infection. Linköping University, Faculty of Medicine and Health Sciences.
    Gustafsson, Mika
    Linköping University, Department of Physics, Chemistry and Biology, Bioinformatics. Linköping University, Faculty of Science & Engineering.
    Ernerudh, Jan
    Linköping University, Department of Biomedical and Clinical Sciences, Division of Inflammation and Infection. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Diagnostics, Department of Clinical Immunology and Transfusion Medicine.
    CD4(+) T-cell DNA methylation changes during pregnancy significantly correlate with disease-associated methylation changes in autoimmune diseases2022In: Epigenetics, ISSN 1559-2294, E-ISSN 1559-2308, Vol. 17, no 9, p. 1040-1055Article in journal (Refereed)
    Abstract [en]

    Epigenetics may play a central, yet unexplored, role in the profound changes that the maternal immune system undergoes during pregnancy and could be involved in the pregnancy-induced modulation of several autoimmune diseases. We investigated changes in the methylome in isolated circulating CD4(+) T-cells in non-pregnant and pregnant women, during the 1(st) and 2(nd) trimester, using the Illumina Infinium Human Methylation 450K array, and explored how these changes were related to autoimmune diseases that are known to be affected during pregnancy. Pregnancy was associated with several hundreds of methylation differences, particularly during the 2(nd) trimester. A network-based modular approach identified several genes, e.g., CD28, FYN, VAV1 and pathways related to T-cell signalling and activation, highlighting T-cell regulation as a central component of the observed methylation alterations. The identified pregnancy module was significantly enriched for disease-associated methylation changes related to multiple sclerosis, rheumatoid arthritis and systemic lupus erythematosus. A negative correlation between pregnancy-associated methylation changes and disease-associated changes was found for multiple sclerosis and rheumatoid arthritis, diseases that are known to improve during pregnancy whereas a positive correlation was found for systemic lupus erythematosus, a disease that instead worsens during pregnancy. Thus, the directionality of the observed changes is in line with the previously observed effect of pregnancy on disease activity. Our systems medicine approach supports the importance of the methylome in immune regulation of T-cells during pregnancy. Our findings highlight the relevance of using pregnancy as a model for understanding and identifying disease-related mechanisms involved in the modulation of autoimmune diseases.

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  • 20.
    Badam, Tejaswi Venkata Satya
    Linköping University, Department of Physics, Chemistry and Biology, Bioinformatics. Linköping University, Faculty of Science & Engineering.
    Omic Network Modules in Complex diseases2021Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Biological systems encompass various molecular entities such as genes, proteins, and other biological molecules, including interactions among those components. Understanding a given phenotype, the functioning of a cell or tissue, aetiology of disease, or cellular organization, requires accurate measurements of the abundance profiles of these molecular entities in the form of biomedical data. The analysis of the interplay between these different entities at various levels represented in the form of biological network provides a mechanistic understanding of the observed phenotype. In order to study this interplay, there is a requirement of a conceptual and intuitive framework which can model multiple omics such as genome, transcriptome, or a proteome. This can be addressed by application of network-based strategies.

    Translational bioinformatics deals with the development of analytic and interpretive methods to optimize the transformation of different omics and clinical data to understanding of complex diseases and improving human health. Complex diseases such as multiple sclerosis (MS), rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), and non-small cell lung cancer (NSCLC) etc., are hypothesized to be a result of a disturbance in the omic networks rendering the healthy cells to be in a state of malfunction. Even though there are numerous methods to layout the relation of the interactions among omics in complex diseases, the output network modules were not clearly interpreted.

    In this PhD thesis, we showed how different omic data such as transcriptome and methylome can be mapped to the network of interactions to extract highly interconnected gene sets relevant to the disease, so called disease modules. First, we selected common module identification methods and assembled them into a unified framework of the methods implemented in an Rpackage MODifieR (Paper I). Secondly, we showed that the concept of the network modules can be applied on the whole genome sequencing data for developing a tested model for predicting myelosuppressive toxicity (Paper II).

    Furthermore, we demonstrated that network modules extracted using the methylome data helped identifying several genes that were associated with pregnancy-induced pathways and were enriched for disease-associated methylation changes that were also shared by three auto-immune and inflammatory diseases, namely MS, RA, and SLE (Paper III). Remarkably, those methylation changes correlated with the expected outcome from clinical experience in those diseases. Last, we benchmarked the omic network modules on 19 different complex diseases using both transcriptomic and methylomic data. This led to the identification of a multi-omic MS module that was highly enriched disease-associated genes identified by genome-wide association studies, but also genes associated with the most common environmental risk factors of MS (Paper IV).

    The application of the network modules concept on different omics is the centrepiece of the research presented in this PhD thesis. The thesis represents the application of omic network modules in complex diseases and how these modules should be integrated and interpreted. In particular, it aimed to show the importance of networks owing to the incomplete knowledge of the genes dysregulated in complex diseases and the contribution of this thesis that provides tools and benchmarks for the methods as well as insights into how a network module can be extracted and interpreted from the omic data in complex diseases.

    List of papers
    1. MODifieR: an Ensemble R Package for Inference of Disease Modules from Transcriptomics Networks
    Open this publication in new window or tab >>MODifieR: an Ensemble R Package for Inference of Disease Modules from Transcriptomics Networks
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    2020 (English)In: Bioinformatics, ISSN 1367-4803, E-ISSN 1367-4811, Vol. 36, no 12, p. 3918-3919Article in journal (Refereed) Published
    Abstract [en]

    Motivation: Complex diseases are due to the dense interactions of many disease-associated factors that dysregulate genes that in turn form the so-called disease modules, which have shown to be a powerful concept for understanding pathological mechanisms. There exist many disease module inference methods that rely on somewhat different assumptions, but there is still no gold standard or best-performing method. Hence, there is a need for combining these methods to generate robust disease modules. Results: We developed MODule IdentiFIER (MODifieR), an ensemble R package of nine disease module inference methods from transcriptomics networks. MODifieR uses standardized input and output allowing the possibility to combine individual modules generated from these methods into more robust disease-specific modules, contributing to a better understanding of complex diseases.

    Place, publisher, year, edition, pages
    OXFORD UNIV PRESS, 2020
    National Category
    Bioinformatics and Systems Biology
    Identifiers
    urn:nbn:se:liu:diva-168277 (URN)10.1093/bioinformatics/btaa235 (DOI)000550127500051 ()32271876 (PubMedID)
    Note

    Funding Agencies|Knowledge Foundation; Swedish Research CouncilSwedish Research Council; Swedish foundation for strategic researchSwedish Foundation for Strategic Research

    Available from: 2020-08-21 Created: 2020-08-21 Last updated: 2023-01-19
    2. Whole-genome sequencing and gene network modules predict gemcitabine/carboplatin-induced myelosuppression in non-small cell lung cancer patients
    Open this publication in new window or tab >>Whole-genome sequencing and gene network modules predict gemcitabine/carboplatin-induced myelosuppression in non-small cell lung cancer patients
    Show others...
    2020 (English)In: npj Systems Biology and Applications, ISSN 2056-7189, Vol. 6, no 1, article id 25Article in journal (Refereed) Published
    Abstract [en]

    Gemcitabine/carboplatin chemotherapy commonly induces myelosuppression, including neutropenia, leukopenia, and thrombocytopenia. Predicting patients at risk of these adverse drug reactions (ADRs) and adjusting treatments accordingly is a long-term goal of personalized medicine. This study used whole-genome sequencing (WGS) of blood samples from 96 gemcitabine/carboplatin-treated non-small cell lung cancer (NSCLC) patients and gene network modules for predicting myelosuppression. Association of genetic variants in PLINK found 4594, 5019, and 5066 autosomal SNVs/INDELs with p ≤ 1 × 10−3 for neutropenia, leukopenia, and thrombocytopenia, respectively. Based on the SNVs/INDELs we identified the toxicity module, consisting of 215 unique overlapping genes inferred from MCODE-generated gene network modules of 350, 345, and 313 genes, respectively. These module genes showed enrichment for differentially expressed genes in rat bone marrow, human bone marrow, and human cell lines exposed to carboplatin and gemcitabine (p < 0.05). Then using 80% of the patients as training data, random LASSO reduced the number of SNVs/INDELs in the toxicity module into a feasible prediction model consisting of 62 SNVs/INDELs that accurately predict both the training and the test (remaining 20%) data with high (CTCAE 3–4) and low (CTCAE 0–1) maximal myelosuppressive toxicity completely, with the receiver-operating characteristic (ROC) area under the curve (AUC) of 100%. The present study shows how WGS, gene network modules, and random LASSO can be used to develop a feasible and tested model for predicting myelosuppressive toxicity. Although the proposed model predicts myelosuppression in this study, further evaluation in other studies is required to determine its reproducibility, usability, and clinical effect.

    Place, publisher, year, edition, pages
    Nature Publishing Group, 2020
    Keywords
    Cancer, Genetic interaction, Systems analysis
    National Category
    Medical Genetics Bioinformatics and Systems Biology Cancer and Oncology
    Identifiers
    urn:nbn:se:liu:diva-168465 (URN)10.1038/s41540-020-00146-6 (DOI)000568927100001 ()32839457 (PubMedID)2-s2.0-85089776223 (Scopus ID)
    Note

    Funding agencies: Swedish Cancer Society, the Swedish Research Council, Linköping University, ALF grants Region Östergötland, the Funds of Radiumhemmet, Marcus Borgströms stiftelse, Stiftelsen Assar Gabrielssons Fond

    Available from: 2020-08-24 Created: 2020-08-24 Last updated: 2021-01-15Bibliographically approved
    3. CD4(+) T-cell DNA methylation changes during pregnancy significantly correlate with disease-associated methylation changes in autoimmune diseases
    Open this publication in new window or tab >>CD4(+) T-cell DNA methylation changes during pregnancy significantly correlate with disease-associated methylation changes in autoimmune diseases
    Show others...
    2022 (English)In: Epigenetics, ISSN 1559-2294, E-ISSN 1559-2308, Vol. 17, no 9, p. 1040-1055Article in journal (Refereed) Published
    Abstract [en]

    Epigenetics may play a central, yet unexplored, role in the profound changes that the maternal immune system undergoes during pregnancy and could be involved in the pregnancy-induced modulation of several autoimmune diseases. We investigated changes in the methylome in isolated circulating CD4(+) T-cells in non-pregnant and pregnant women, during the 1(st) and 2(nd) trimester, using the Illumina Infinium Human Methylation 450K array, and explored how these changes were related to autoimmune diseases that are known to be affected during pregnancy. Pregnancy was associated with several hundreds of methylation differences, particularly during the 2(nd) trimester. A network-based modular approach identified several genes, e.g., CD28, FYN, VAV1 and pathways related to T-cell signalling and activation, highlighting T-cell regulation as a central component of the observed methylation alterations. The identified pregnancy module was significantly enriched for disease-associated methylation changes related to multiple sclerosis, rheumatoid arthritis and systemic lupus erythematosus. A negative correlation between pregnancy-associated methylation changes and disease-associated changes was found for multiple sclerosis and rheumatoid arthritis, diseases that are known to improve during pregnancy whereas a positive correlation was found for systemic lupus erythematosus, a disease that instead worsens during pregnancy. Thus, the directionality of the observed changes is in line with the previously observed effect of pregnancy on disease activity. Our systems medicine approach supports the importance of the methylome in immune regulation of T-cells during pregnancy. Our findings highlight the relevance of using pregnancy as a model for understanding and identifying disease-related mechanisms involved in the modulation of autoimmune diseases.

    Place, publisher, year, edition, pages
    Taylor & Francis Inc, 2022
    Keywords
    Pregnancy; epigenetics; methylation; CD4(+) T cells; module; rheumatoid arthritis; multiple sclerosis; systemic lupus erythematosus
    National Category
    Cell and Molecular Biology
    Identifiers
    urn:nbn:se:liu:diva-180368 (URN)10.1080/15592294.2021.1982510 (DOI)000703400700001 ()34605719 (PubMedID)
    Note

    Funding Agencies|Swedish Foundation for Strategic ResearchSwedish Foundation for Strategic Research [SB16-0011]; Swedish Research CouncilSwedish Research CouncilEuropean Commission [K2013-61X-22310-01-4, 2015-030807, 2018-02776]; Lions research grant [Liu-2012-01948]

    Available from: 2021-10-18 Created: 2021-10-18 Last updated: 2023-12-22
    4. A validated generally applicable approach using the systematic assessment of disease modules by GWAS reveals a multi-omic module strongly associated with risk factors in multiple sclerosis
    Open this publication in new window or tab >>A validated generally applicable approach using the systematic assessment of disease modules by GWAS reveals a multi-omic module strongly associated with risk factors in multiple sclerosis
    Show others...
    2021 (English)In: BMC Genomics, E-ISSN 1471-2164, Vol. 22, no 1, article id 631Article in journal (Refereed) Published
    Abstract [en]

    Background There exist few, if any, practical guidelines for predictive and falsifiable multi-omic data integration that systematically integrate existing knowledge. Disease modules are popular concepts for interpreting genome-wide studies in medicine but have so far not been systematically evaluated and may lead to corroborating multi-omic modules. Result We assessed eight module identification methods in 57 previously published expression and methylation studies of 19 diseases using GWAS enrichment analysis. Next, we applied the same strategy for multi-omic integration of 20 datasets of multiple sclerosis (MS), and further validated the resulting module using both GWAS and risk-factor-associated genes from several independent cohorts. Our benchmark of modules showed that in immune-associated diseases modules inferred from clique-based methods were the most enriched for GWAS genes. The multi-omic case study using MS data revealed the robust identification of a module of 220 genes. Strikingly, most genes of the module were differentially methylated upon the action of one or several environmental risk factors in MS (n = 217, P = 10(- 47)) and were also independently validated for association with five different risk factors of MS, which further stressed the high genetic and epigenetic relevance of the module for MS. Conclusions We believe our analysis provides a workflow for selecting modules and our benchmark study may help further improvement of disease module methods. Moreover, we also stress that our methodology is generally applicable for combining and assessing the performance of multi-omic approaches for complex diseases.

    Place, publisher, year, edition, pages
    BMC, 2021
    Keywords
    Benchmark; Multi-omics; Network modules; Multiple sclerosis; Risk factors; Disease modules; Network analysis; Protein network analysis; Transcriptomics; Methylomics; Data integration; Genome-wide association analysis
    National Category
    Bioinformatics and Systems Biology
    Identifiers
    urn:nbn:se:liu:diva-179166 (URN)10.1186/s12864-021-07935-1 (DOI)000692402600002 ()34461822 (PubMedID)
    Note

    Funding Agencies|Swedish Research CouncilSwedish Research CouncilEuropean Commission [201503807, 2018-02638]; Swedish foundation for strategic researchSwedish Foundation for Strategic Research [SB16-0095]; Center for Industrial IT (CENIIT); European Union Horizon 2020/European Research Council Consolidator grant (Epi4MS) [818170]; Knut and Alice Wallenberg FoundationKnut & Alice Wallenberg Foundation [2019.0089]; Knowledge Foundation [20170298]; Linkoping University

    Available from: 2021-09-14 Created: 2021-09-14 Last updated: 2024-01-17
  • 21.
    Bano-Polo, Manuel
    et al.
    University of Valencia, Spain .
    Martinez-Gill, Luis
    University of Valencia, Spain .
    Wallner, Björn
    Linköping University, Department of Physics, Chemistry and Biology, Bioinformatics. Linköping University, The Institute of Technology.
    Nieva, Jose L.
    University of Pais Vasco UPV EHU, Spain .
    Elofsson, Arne
    Stockholm University, Sweden .
    Mingarro, Ismael
    University of Valencia, Spain .
    Charge Pair Interactions in Transmembrane Helices and Turn Propensity of the Connecting Sequence Promote Helical Hairpin Insertion2013In: Journal of Molecular Biology, ISSN 0022-2836, E-ISSN 1089-8638, Vol. 425, no 4, p. 830-840Article in journal (Refereed)
    Abstract [en]

    alpha-Helical hairpins, consisting of a pair of closely spaced transmembrane (TM) helices that are connected by a short interfacial turn, are the simplest structural motifs found in multi-spanning membrane proteins. In naturally occurring hairpins, the presence of polar residues is common and predicted to complicate membrane insertion. We postulate that the pre-packing process offsets any energetic cost of allocating polar and charged residues within the hydrophobic environment of biological membranes. Consistent with this idea, we provide here experimental evidence demonstrating that helical hairpin insertion into biological membranes can be driven by electrostatic interactions between closely separated, poorly hydrophobic sequences. Additionally, we observe that the integral hairpin can be stabilized by a short loop heavily populated by turn-promoting residues. We conclude that the combined effect of TM-TM electrostatic interactions and tight turns plays an important role in generating the functional architecture of membrane proteins and propose that helical hairpin motifs can be acquired within the context of the Sec61 translocon at the early stages of membrane protein biosynthesis. Taken together, these data further underline the potential complexities involved in accurately predicting TM domains from primary structures.

  • 22.
    Barrientos-Somarribas, Mauricio
    et al.
    Karolinska Inst, Sweden.
    Messina, David N.
    Stockholm Univ, Sweden.
    Pou, Christian
    Karolinska Inst, Sweden.
    Lysholm, Fredrik
    Linköping University, Department of Physics, Chemistry and Biology, Bioinformatics. Linköping University, Faculty of Science & Engineering.
    Bjerkner, Annelie
    Karolinska Univ Hosp, Sweden.
    Allander, Tobias
    Karolinska Univ Hosp, Sweden.
    Andersson, Björn
    Karolinska Inst, Sweden.
    Sonnhammer, Erik L. L.
    Stockholm Univ, Sweden.
    Discovering viral genomes in human metagenomic data by predicting unknown protein families2018In: Scientific Reports, E-ISSN 2045-2322, Vol. 8, article id 28Article in journal (Refereed)
    Abstract [en]

    Massive amounts of metagenomics data are currently being produced, and in all such projects a sizeable fraction of the resulting data shows no or little homology to known sequences. It is likely that this fraction contains novel viruses, but identification is challenging since they frequently lack homology to known viruses. To overcome this problem, we developed a strategy to detect ORFan protein families in shotgun metagenomics data, using similarity-based clustering and a set of filters to extract bona fide protein families. We applied this method to 17 virus-enriched libraries originating from human nasopharyngeal aspirates, serum, feces, and cerebrospinal fluid samples. This resulted in 32 predicted putative novel gene families. Some families showed detectable homology to sequences in metagenomics datasets and protein databases after reannotation. Notably, one predicted family matches an ORF from the highly variable Torque Teno virus (TTV). Furthermore, follow-up from a predicted ORFan resulted in the complete reconstruction of a novel circular genome. Its organisation suggests that it most likely corresponds to a novel bacteriophage in the microviridae family, hence it was named bacteriophage HFM.

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  • 23.
    Basu, Sankar
    et al.
    Linköping University, Department of Physics, Chemistry and Biology, Bioinformatics.
    Bhattacharyya, Dhananjay
    Computational Science Division, Saha Insititute of Nuclear Physics, Kolkata 700064, India.
    Wallner, Björn
    Linköping University, Department of Physics, Chemistry and Biology, Bioinformatics.
    SARAMAint: The Complementarity Plot for Protein–Protein Interface2014In: Journal of Bioinformatics and Intelligent Control, Vol. 3Article in journal (Refereed)
  • 24.
    Basu, Sankar Chandra
    et al.
    Linköping University, Department of Physics, Chemistry and Biology, Bioinformatics. Linköping University, Faculty of Science & Engineering. University of Calcutta, India.
    Söderquist, Fredrik
    Linköping University, Department of Physics, Chemistry and Biology, Bioinformatics. Linköping University, Faculty of Science & Engineering.
    Wallner, Björn
    Linköping University, Department of Physics, Chemistry and Biology, Bioinformatics. Linköping University, Faculty of Science & Engineering.
    Proteus: a random forest classifier to predict disorder-to-order transitioning binding regions in intrinsically disordered proteins2017In: Journal of Computer-Aided Molecular Design, ISSN 0920-654X, E-ISSN 1573-4951, Vol. 31, no 5, p. 453-466Article in journal (Refereed)
    Abstract [en]

    The focus of the computational structural biology community has taken a dramatic shift over the past one-and-a-half decades from the classical protein structure prediction problem to the possible understanding of intrinsically disordered proteins (IDP) or proteins containing regions of disorder (IDPR). The current interest lies in the unraveling of a disorder-to-order transitioning code embedded in the amino acid sequences of IDPs/ IDPRs. Disordered proteins are characterized by an enormous amount of structural plasticity which makes them promiscuous in binding to different partners, multi-functional in cellular activity and atypical in folding energy landscapes resembling partially folded molten globules. Also, their involvement in several deadly human diseases (e.g. cancer, cardiovascular and neurodegenerative diseases) makes them attractive drug targets, and important for a biochemical understanding of the disease(s). The study of the structural ensemble of IDPs is rather difficult, in particular for transient interactions. When bound to a structured partner, an IDPR adapts an ordered conformation in the complex. The residues that undergo this disorder-to-order transition are called protean residues, generally found in short contiguous stretches and the first step in understanding the modus operandi of an IDP/IDPR would be to predict these residues. There are a few available methods which predict these protean segments from their amino acid sequences; however, their performance reported in the literature leaves clear room for improvement. With this background, the current study presents Proteus, a random forest classifier that predicts the likelihood of a residue undergoing a disorder-toorder transition upon binding to a potential partner protein. The prediction is based on features that can be calculated using the amino acid sequence alone. Proteus compares favorably with existing methods predicting twice as many true positives as the second best method (55 vs. 27%) with a much higher precision on an independent data set. The current study also sheds some light on a possible disorderto-order transitioning consensus, untangled, yet embedded in the amino acid sequence of IDPs. Some guidelines have also been suggested for proceeding with a real-life structural modeling involving an IDPR using Proteus.

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  • 25.
    Basu, Sankar Chandra
    et al.
    Linköping University, Department of Physics, Chemistry and Biology, Bioinformatics. Linköping University, Faculty of Science & Engineering.
    Wallner, Björn
    Linköping University, Department of Physics, Chemistry and Biology, Bioinformatics. Linköping University, Faculty of Science & Engineering.
    DockQ: A Quality Measure for Protein-Protein Docking Models2016In: PLOS ONE, E-ISSN 1932-6203, Vol. 11, no 8, p. e0161879-Article in journal (Refereed)
    Abstract [en]

    The state-of-the-art to assess the structural quality of docking models is currently based on three related yet independent quality measures: F-nat, LRMS, and iRMS as proposed and standardized by CAPRI. These quality measures quantify different aspects of the quality of a particular docking model and need to be viewed together to reveal the true quality, e.g. a model with relatively poor LRMS (amp;gt; 10 angstrom) might still qualify as acceptable with a descent F-nat (amp;gt; 0.50) and iRMS (amp;lt; 3.0 angstrom). This is also the reason why the so called CAPRI criteria for assessing the quality of docking models is defined by applying various ad-hoc cutoffs on these measures to classify a docking model into the four classes: Incorrect, Acceptable, Medium, or High quality. This classification has been useful in CAPRI, but since models are grouped in only four bins it is also rather limiting, making it difficult to rank models, correlate with scoring functions or use it as target function in machine learning algorithms. Here, we present DockQ, a continuous protein-protein docking model quality measure derived by combining F-nat, LRMS, and iRMS to a single score in the range [0, 1] that can be used to assess the quality of protein docking models. By using DockQ on CAPRI models it is possible to almost completely reproduce the original CAPRI classification into Incorrect, Acceptable, Medium and High quality. An average PPV of 94% at 90% Recall demonstrating that there is no need to apply predefined ad-hoc cutoffs to classify docking models. Since DockQ recapitulates the CAPRI classification almost perfectly, it can be viewed as a higher resolution version of the CAPRI classification, making it possible to estimate model quality in a more quantitative way using Z-scores or sum of top ranked models, which has been so valuable for the CASP community. The possibility to directly correlate a quality measure to a scoring function has been crucial for the development of scoring functions for protein structure prediction, and DockQ should be useful in a similar development in the protein docking field.

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  • 26.
    Basu, Sankar Chandra
    et al.
    Linköping University, Department of Physics, Chemistry and Biology, Bioinformatics. Linköping University, Faculty of Science & Engineering.
    Wallner, Björn
    Linköping University, Department of Physics, Chemistry and Biology, Bioinformatics. Linköping University, Faculty of Science & Engineering.
    Finding correct protein-protein docking models using ProQDock2016In: Bioinformatics, ISSN 1367-4803, E-ISSN 1367-4811, Vol. 32, no 12, p. 262-270Article in journal (Refereed)
    Abstract [en]

    Motivation: Protein-protein interactions are a key in virtually all biological processes. For a detailed understanding of the biological processes, the structure of the protein complex is essential. Given the current experimental techniques for structure determination, the vast majority of all protein complexes will never be solved by experimental techniques. In lack of experimental data, computational docking methods can be used to predict the structure of the protein complex. A common strategy is to generate many alternative docking solutions (atomic models) and then use a scoring function to select the best. The success of the computational docking technique is, to a large degree, dependent on the ability of the scoring function to accurately rank and score the many alternative docking models. Results: Here, we present ProQDock, a scoring function that predicts the absolute quality of docking model measured by a novel protein docking quality score (DockQ). ProQDock uses support vector machines trained to predict the quality of protein docking models using features that can be calculated from the docking model itself. By combining different types of features describing both the protein-protein interface and the overall physical chemistry, it was possible to improve the correlation with DockQ from 0.25 for the best individual feature (electrostatic complementarity) to 0.49 for the final version of ProQDock. ProQDock performed better than the state-of-the-art methods ZRANK and ZRANK2 in terms of correlations, ranking and finding correct models on an independent test set. Finally, we also demonstrate that it is possible to combine ProQDock with ZRANK and ZRANK2 to improve performance even further.

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  • 27.
    Beecham, Ashley H.
    et al.
    University of Miami, FL USA .
    Patsopoulos, Nikolaos A.
    Brigham and Womens Hospital, MA USA .
    Xifara, Dionysia K.
    University of Oxford, England .
    Davis, Mary F.
    Vanderbilt University, TN USA .
    Kemppinen, Anu
    University of Cambridge, England .
    Cotsapas, Chris
    Broad Institute Harvard and MIT, MA USA .
    Shah, Tejas S.
    Wellcome Trust Sanger Institute, England .
    Spencer, Chris
    University of Oxford, England .
    Booth, David
    University of Sydney, Australia .
    Goris, An
    Katholieke University of Leuven, Belgium .
    Oturai, Annette
    Copenhagen University Hospital, Denmark .
    Saarela, Janna
    University of Helsinki, Finland .
    Fontaine, Bertrand
    University of Paris 06, France .
    Hemmer, Bernhard
    Technical University of Munich, Germany .
    Martin, Claes
    Danderyd Hospital, Sweden .
    Zipp, Frauke
    Johannes Gutenberg University of Mainz, Germany .
    DAlfonso, Sandra
    University of Piemonte Orientale, Italy .
    Martinelli-Boneschi, Filippo
    Ist Science San Raffaele, Italy .
    Taylor, Bruce
    University of Tasmania, Australia .
    Harbo, Hanne F.
    Oslo University Hospital, Norway .
    Kockum, Ingrid
    Karolinska Institute, Sweden .
    Hillert, Jan
    Karolinska Institute, Sweden .
    Olsson, Tomas
    Karolinska Institute, Sweden .
    Ban, Maria
    University of Cambridge, England .
    Oksenberg, Jorge R.
    University of Calif San Francisco, CA USA .
    Hintzen, Rogier
    Erasmus University, Netherlands .
    F Barcellos, Lisa
    University of Calif Berkeley, CA 94720 USA .
    Agliardi, Cristina
    IRCCS Santa Maria Nascente, Italy .
    Alfredsson, Lars
    Karolinska Institute, Sweden .
    Alizadeh, Mehdi
    University of Rennes 1, France .
    Anderson, Carl
    Wellcome Trust Sanger Institute, England .
    Andrews, Robert
    Wellcome Trust Sanger Institute, England .
    Bach Sondergaard, Helle
    Copenhagen University Hospital, Denmark .
    Baker, Amie
    University of Cambridge, England .
    Band, Gavin
    University of Oxford, England .
    Baranzini, Sergio E.
    University of Calif San Francisco, CA USA .
    Barizzone, Nadia
    University of Piemonte Orientale, Italy .
    Barrett, Jeffrey
    Wellcome Trust Sanger Institute, England .
    Bellenguez, Celine
    University of Oxford, England .
    Bergamaschi, Laura
    University of Piemonte Orientale, Italy .
    Bernardinelli, Luisa
    MRC, England .
    Berthele, Achim
    Technical University of Munich, Germany .
    Biberacher, Viola
    Technical University of Munich, Germany .
    Binder, Thomas M C.
    University of Medical Centre Hamburg Eppendorf, Germany .
    Blackburn, Hannah
    Wellcome Trust Sanger Institute, England .
    Bomfim, Izaura L.
    Karolinska Institute, Sweden .
    Brambilla, Paola
    Ist Science San Raffaele, Italy .
    Broadley, Simon
    Griffith University, Australia .
    Brochet, Bruno
    University of Bordeaux 2, France .
    Brundin, Lou
    Karolinska Institute, Sweden .
    Buck, Dorothea
    Technical University of Munich, Germany .
    Butzkueven, Helmut
    University of Melbourne, Australia .
    Caillier, Stacy J.
    University of Calif San Francisco, CA USA .
    Camu, William
    Centre Hospital University of Regional Montpellier, France .
    Carpentier, Wassila
    University of Paris 06, France .
    Cavalla, Paola
    Azienda Osped Citta Salute and Science Torino, Italy .
    Celius, Elisabeth G.
    Oslo University Hospital, Norway .
    Coman, Irene
    Hop Avicenne, France .
    Comi, Giancarlo
    Ist Science San Raffaele, Italy .
    Corrado, Lucia
    University of Piemonte Orientale, Italy .
    Cosemans, Leentje
    Katholieke University of Leuven, Belgium .
    Cournu-Rebeix, Isabelle
    University of Paris 06, France .
    Cree, Bruce A C.
    University of Calif San Francisco, CA USA .
    Cusi, Daniele
    University of Milan, Italy .
    Damotte, Vincent
    University of Paris 06, France .
    Defer, Gilles
    CHU Caen, France .
    Delgado, Silvia R.
    University of Miami, FL USA .
    Deloukas, Panos
    Wellcome Trust Sanger Institute, England .
    di Sapio, Alessia
    University of San Luigi, Italy .
    Dilthey, Alexander T.
    University of Oxford, England .
    Donnelly, Peter
    University of Oxford, England .
    Dubois, Benedicte
    Katholieke University of Leuven, Belgium .
    Duddy, Martin
    Royal Victoria Infirm, England .
    Edkins, Sarah
    Wellcome Trust Sanger Institute, England .
    Elovaara, Irina
    University of Tampere, Finland .
    Esposito, Federica
    Ist Science San Raffaele, Italy .
    Evangelou, Nikos
    University of Nottingham Hospital, England .
    Fiddes, Barnaby
    University of Cambridge, England .
    Field, Judith
    University of Melbourne, Australia .
    Franke, Andre
    University of Kiel, Germany .
    Freeman, Colin
    University of Oxford, England .
    Frohlich, Irene Y.
    Brigham and Womens Hospital, MA USA .
    Galimberti, Daniela
    University of Milan, Italy .
    Gieger, Christian
    German Research Centre Environm Heatlh, Germany .
    Gourraud, Pierre-Antoine
    University of Calif San Francisco, CA USA .
    Graetz, Christiane
    Johannes Gutenberg University of Mainz, Germany .
    Graham, Andrew
    Ipswich Hospital National Health Serv NHS Trust, England .
    Grummel, Verena
    Technical University of Munich, Germany .
    Guaschino, Clara
    Ist Science San Raffaele, Italy .
    Hadjixenofontos, Athena
    University of Miami, FL USA .
    Hakonarson, Hakon
    Childrens Hospital Philadelphia, PA USA .
    Halfpenny, Christopher
    Southampton Gen Hospital, England .
    Hall, Gillian
    Aberdeen Royal Infirm, Scotland .
    Hall, Per
    Karolinska Institute, Sweden .
    Hamsten, Anders
    Karolinska University Hospital Solna, Sweden .
    Harley, James
    Hull Royal Infirm, England .
    Harrower, Timothy
    Royal Devon and Exeter Fdn Trust Hospital, England .
    Hawkins, Clive
    Keele University, England .
    Hellenthal, Garrett
    UCL, England .
    Hillier, Charles
    Poole Gen Hospital, England .
    Hobart, Jeremy
    University of Plymouth, England .
    Hoshi, Muni
    Technical University of Munich, Germany .
    Hunt, Sarah E.
    Wellcome Trust Sanger Institute, England .
    Jagodic, Maja
    Karolinska Institute, Sweden .
    Jelcic, Ilijas
    University of Medical Centre Hamburg Eppendorf, Germany .
    Jochim, Angela
    Technical University of Munich, Germany .
    Kendall, Brian
    Leicester Royal Infirm, England .
    Kermode, Allan
    University of Western Australia, Australia .
    Kilpatrick, Trevor
    University of Melbourne, Australia .
    Koivisto, Keijo
    Seinajoki Central Hospital, Finland .
    Konidari, Ioanna
    University of Miami, FL USA .
    Korn, Thomas
    Technical University of Munich, Germany .
    Kronsbein, Helena
    Technical University of Munich, Germany .
    Langford, Cordelia
    Wellcome Trust Sanger Institute, England .
    Larsson, Malin
    Linköping University, Department of Physics, Chemistry and Biology, Bioinformatics. Linköping University, The Institute of Technology.
    Lathrop, Mark
    Centre Etud Polymorphisme Humain, France .
    Lebrun-Frenay, Christine
    CHRU Nice, France .
    Lechner-Scott, Jeannette
    University of Newcastle, Australia .
    Lee, Michelle H.
    Brigham and Womens Hospital, MA USA .
    Leone, Maurizio A.
    Osped Maggiore Novara, Italy .
    Leppa, Virpi
    University of Helsinki, Finland .
    Liberatore, Giuseppe
    Ist Science San Raffaele, Italy .
    Lie, Benedicte A.
    University of Oslo, Norway .
    Lill, Christina M.
    Johannes Gutenberg University of Mainz, Germany .
    Linden, Magdalena
    Karolinska Institute, Sweden .
    Link, Jenny
    Karolinska Institute, Sweden .
    Luessi, Felix
    Johannes Gutenberg University of Mainz, Germany .
    Lycke, Jan
    University of Gothenburg, Sweden .
    Macciardi, Fabio
    University of Calif Irvine, CA USA .
    Mannisto, Satu
    National Institute Health and Welf, Finland .
    Manrique, Clara P.
    University of Miami, FL USA .
    Martin, Roland
    University of Medical Centre Hamburg Eppendorf, Germany .
    Martinelli, Vittorio
    Ist Science San Raffaele, Italy .
    Mason, Deborah
    Canterbury Dist Health Board, New Zealand .
    Mazibrada, Gordon
    Queen Elizabeth Medical Centre, England .
    McCabe, Cristin
    Broad Institute Harvard and MIT, MA USA .
    Mero, Inger-Lise
    Oslo University Hospital, Norway .
    Mescheriakova, Julia
    Erasmus University, Netherlands .
    Moutsianas, Loukas
    University of Oxford, England .
    Myhr, Kjell-Morten
    Haukeland Hospital, Norway .
    Nagels, Guy
    National Multiple Sclerosis Centre Melsbroek, Belgium .
    Nicholas, Richard
    Charing Cross Hospital, England .
    Nilsson, Petra
    Lund University, Sweden .
    Piehl, Fredrik
    Karolinska Institute, Sweden .
    Pirinen, Matti
    University of Oxford, England .
    Price, Sian E.
    Royal Hallamshire Hospital, England .
    Quach, Hong
    University of Calif Berkeley, CA USA .
    Reunanen, Mauri
    University of Oulu, Finland .
    Robberecht, Wim
    Vesalius Research Centre, Belgium .
    Robertson, Neil P.
    Cardiff University, Wales .
    Rodegher, Mariaemma
    Ist Science San Raffaele, Italy .
    Rog, David
    Salford Royal NHS Fdn Trust, England .
    Salvetti, Marco
    University of Roma La Sapienza, Italy .
    Schnetz-Boutaud, Nathalie C.
    Vanderbilt University, TN USA .
    Sellebjerg, Finn
    Copenhagen University Hospital, Denmark .
    Selter, Rebecca C.
    Technical University of Munich, Germany .
    Schaefer, Catherine
    Kaiser Permanente Div Research, CA USA .
    Shaunak, Sandip
    Royal Preston Hospital, England .
    Shen, Ling
    Kaiser Permanente Div Research, CA USA .
    Shields, Simon
    Norfolk and Norwich Hospital, England .
    Siffrin, Volker
    Johannes Gutenberg University of Mainz, Germany .
    Slee, Mark
    Flinders University of S Australia, Australia .
    Soelberg Sorensen, Per
    Copenhagen University Hospital, Denmark .
    Sorosina, Melissa
    Ist Science San Raffaele, Italy .
    Sospedra, Mireia
    University of Medical Centre Hamburg Eppendorf, Germany .
    Spurkland, Anne
    University of Oslo, Norway .
    Strange, Amy
    University of Oxford, England .
    Sundqvist, Emilie
    Karolinska Institute, Sweden .
    Thijs, Vincent
    Vesalius Research Centre, Belgium .
    Thorpe, John
    Peterborough City Hospital, England .
    Ticca, Anna
    San Francesco Hospital, Italy .
    Tienari, Pentti
    University of Helsinki, Finland .
    van Duijn, Cornelia
    Erasmus MC, Netherlands .
    Visser, Elizabeth M.
    University of Aberdeen, Scotland .
    Vucic, Steve
    University of Sydney, Australia .
    Westerlind, Helga
    Karolinska Institute, Sweden .
    Wiley, James S.
    University of Melbourne, Australia .
    Wilkins, Alastair
    University of Bristol, England .
    Wilson, James F.
    University of Edinburgh, Scotland .
    Winkelmann, Juliane
    Technical University of Munich, Germany .
    Zajicek, John
    University of Plymouth, England .
    Zindler, Eva
    Johannes Gutenberg University of Mainz, Germany .
    Haines, Jonathan L.
    Vanderbilt University, TN USA .
    Pericak-Vance, Margaret A.
    University of Miami, FL USA .
    Ivinson, Adrian J.
    Harvard University, MA USA .
    Stewart, Graeme
    University of Sydney, Australia .
    Hafler, David
    Broad Institute Harvard and MIT, MA USA .
    Hauser, Stephen L.
    University of Calif San Francisco, CA USA .
    Compston, Alastair
    University of Cambridge, England .
    McVean, Gil
    University of Oxford, England .
    De Jager, Philip
    Brigham and Womens Hospital, MA USA .
    Sawcer, Stephen J.
    University of Cambridge, England .
    McCauley, Jacob L.
    University of Miami, FL USA .
    Analysis of immune-related loci identifies 48 new susceptibility variants for multiple sclerosis2013In: Nature Genetics, ISSN 1061-4036, E-ISSN 1546-1718, Vol. 45, no 11, p. 1353-+Article in journal (Refereed)
    Abstract [en]

    Using the ImmunoChip custom genotyping array, we analyzed 14,498 subjects with multiple sclerosis and 24,091 healthy controls for 161,311 autosomal variants and identified 135 potentially associated regions (P andlt; 1.0 x 10(-4)). In a replication phase, we combined these data with previous genome-wide association study (GWAS) data from an independent 14,802 subjects with multiple sclerosis and 26,703 healthy controls. In these 80,094 individuals of European ancestry, we identified 48 new susceptibility variants (P andlt; 5.0 x 10(-8)), 3 of which we found after conditioning on previously identified variants. Thus, there are now 110 established multiple sclerosis risk variants at 103 discrete loci outside of the major histocompatibility complex. With high-resolution Bayesian fine mapping, we identified five regions where one variant accounted for more than 50% of the posterior probability of association. This study enhances the catalog of multiple sclerosis risk variants and illustrates the value of fine mapping in the resolution of GWAS signals.

  • 28.
    Bensberg, Maike
    et al.
    Linköping University, Department of Biomedical and Clinical Sciences, Division of Children's and Women's Health. Linköping University, Faculty of Medicine and Health Sciences.
    Rundquist, Olof
    Linköping University, Department of Physics, Chemistry and Biology, Bioinformatics. Linköping University, Faculty of Science & Engineering.
    Selimovic, Aida
    Linköping University, Department of Biomedical and Clinical Sciences, Division of Children's and Women's Health. Linköping University, Faculty of Medicine and Health Sciences.
    Lagerwall, Cathrine
    Linköping University, Department of Biomedical and Clinical Sciences, Division of Surgery, Orthopedics and Oncology. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center of Paediatrics and Gynaecology and Obstetrics, H.K.H. Kronprinsessan Victorias barn- och ungdomssjukhus.
    Benson, Mikael
    Linköping University, Department of Biomedical and Clinical Sciences, Division of Children's and Women's Health. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center of Paediatrics and Gynaecology and Obstetrics, H.K.H. Kronprinsessan Victorias barn- och ungdomssjukhus.
    Gustafsson, Mika
    Linköping University, Department of Physics, Chemistry and Biology, Bioinformatics. Linköping University, Faculty of Science & Engineering.
    Vogt, Hartmut
    Linköping University, Department of Biomedical and Clinical Sciences, Division of Children's and Women's Health. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center of Paediatrics and Gynaecology and Obstetrics, H.K.H. Kronprinsessan Victorias barn- och ungdomssjukhus.
    Lentini, Antonio
    Karolinska Inst, Sweden.
    Nestor, Colm
    Linköping University, Department of Biomedical and Clinical Sciences, Division of Children's and Women's Health. Linköping University, Faculty of Medicine and Health Sciences.
    TET2 as a tumor suppressor and therapeutic target in T-cell acute lymphoblastic leukemia2021In: Proceedings of the National Academy of Sciences of the United States of America, ISSN 0027-8424, E-ISSN 1091-6490, Vol. 118, no 34, article id e2110758118Article in journal (Refereed)
    Abstract [en]

    Pediatric T-cell acute lymphoblastic leukemia (T-ALL) is an aggres-sive malignancy resulting from overproduction of immature T-cells in the thymus and is typified by widespread alterations in DNA methyl-ation. As survival rates for relapsed T-ALL remain dismal (10 to 25%), development of targeted therapies to prevent relapse is key to improv-ing prognosis. Whereas mutations in the DNA demethylating enzyme TET2 are frequent in adult T-cell malignancies, TET2 mutations in T-ALL are rare. Here, we analyzed RNA-sequencing data of 321 primary T-ALLs, 20 T-ALL cell lines, and 25 normal human tissues, revealing that TET2 is transcriptionally repressed or silenced in 71% and 17% of T-ALL, respec-tively. Furthermore, we show that TET2 silencing is often associated with hypermethylation of the TET2 promoter in primary T-ALL. Impor-tantly, treatment with the DNA demethylating agent, 5-azacytidine (5-aza), was significantly more toxic to TET2-silenced T-ALL cells and resulted in stable re-expression of the TET2 gene. Additionally, 5-aza led to up-regulation of methylated genes and human endogenous ret-roviruses (HERVs), which was further enhanced by the addition of phys-iological levels of vitamin C, a potent enhancer of TET activity. Together, our results clearly identify 5-aza as a potential targeted therapy for TET2-silenced T-ALL.

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  • 29.
    Berggren, Karl-Fredrik
    et al.
    Linköping University, Department of Physics, Chemistry and Biology, Theoretical Physics . Linköping University, The Institute of Technology.
    Persson, Bengt
    Linköping University, Department of Physics, Chemistry and Biology, Bioinformatics . Linköping University, The Institute of Technology.
    20 years in HPC 1989-20092009Other (Other (popular science, discussion, etc.))
  • 30.
    Bergqvist, Jonathan
    Linköping University, Department of Physics, Chemistry and Biology, Bioinformatics.
    Study of Protein Interfaces with Clustering2018Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    Protein-protein interactions occur in nature and have different functions. The interacting surface between two interacting proteins contains the respective protein's interface residues.

    In this thesis, a series of Python scripts are presented which can perform interface-interface comparisons with the method InterComp, to obtain a distance matrix of different protein interfaces. The distance matrix can be studied with the use of clustering algorithms such as DBSCAN.

    The result from clustering using DBSCAN shows that for the 77,017 protein interfaces studied, a majority of the protein interfaces are part of a single cluster while most of the remaining interfaces are noise for the tested parameters Eps and MinPts.

    The conclusion of this thesis is the effect on the number of clusters for the tested parameters Eps and MinPts when performing DBSCAN.

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  • 31.
    Bhattacharyya, Dhananjay
    et al.
    Saha Institute Nucl Phys, India.
    Halder, Sukanya
    Saha Institute Nucl Phys, India.
    Basu, Sankar Chandra
    Linköping University, Department of Physics, Chemistry and Biology, Bioinformatics. Linköping University, Faculty of Science & Engineering. University of Calcutta, India.
    Mukherjee, Debasish
    Saha Institute Nucl Phys, India.
    Kumar, Prasun
    Indian Institute Science, India.
    Bansal, Manju
    Indian Institute Science, India.
    RNAHelix: computational modeling of nucleic acid structures with Watson-Crick and non-canonical base pairs2017In: Journal of Computer-Aided Molecular Design, ISSN 0920-654X, E-ISSN 1573-4951, Vol. 31, no 2, p. 219-235Article in journal (Refereed)
    Abstract [en]

    Comprehensive analyses of structural features of non-canonical base pairs within a nucleic acid double helix are limited by the availability of a small number of three dimensional structures. Therefore, a procedure for model building of double helices containing any given nucleotide sequence and base pairing information, either canonical or non-canonical, is seriously needed. Here we describe a program RNAHelix, which is an updated version of our widely used software, NUCGEN. The program can regenerate duplexes using the dinucleotide step and base pair orientation parameters for a given double helical DNA or RNA sequence with defined Watson-Crick or non-Watson-Crick base pairs. The original structure and the corresponding regenerated structure of double helices were found to be very close, as indicated by the small RMSD values between positions of the corresponding atoms. Structures of several usual and unusual double helices have been regenerated and compared with their original structures in terms of base pair RMSD, torsion angles and electrostatic potentials and very high agreements have been noted. RNAHelix can also be used to generate a structure with a sequence completely different from an experimentally determined one or to introduce single to multiple mutation, but with the same set of parameters and hence can also be an important tool in homology modeling and study of mutation induced structural changes.

  • 32.
    Bil, Andrzej
    et al.
    Univ Wroclaw, Poland.
    Kochman, Michal
    Linköping University, Department of Physics, Chemistry and Biology, Bioinformatics. Linköping University, Faculty of Science & Engineering. Univ Coll London UCL, England.
    Photoinduced Double Proton Transfer in the Glyoxal-Methanol Complex Revisited: The Role of the Excited States2020In: Journal of Chemical Theory and Computation, ISSN 1549-9618, E-ISSN 1549-9626, Vol. 16, no 5, p. 3273-3286Article in journal (Refereed)
    Abstract [en]

    Under irradiation in the visible range, the glyoxal-methanol complex in a cryogenic argon matrix undergoes a double proton transfer (DPT) reaction through which the glyoxal molecule isomerizes into hydroxyketene. In this work, we employ electronic structure simulations in order to shed more light on the underlying mechanism. Rewardingly, we find that the lowest singlet excited state (S-1) of the complex acts as a gateway to two previously unknown isomerization pathways, of which one takes place entirely in the singlet manifold and the other also involves the lowest triplet state (T-1). Both of these pathways are fully compatible with the available experimental data, implying that either or both are operative under experimental conditions. In either pathway, the methanol molecule acts as a proton shuttle between the proton-donating and proton-accepting sites of glyoxal, resulting in a dramatic lowering of the potential energy barrier to isomerization with respect to the case of isolated glyoxal. The occurrence of DPT in the singlet manifold is demonstrated directly with the use of nonadiabatic molecular dynamics simulations at the spin-flip time-dependent density functional theory level.

  • 33.
    Bil, Andrzej
    et al.
    Univ Wroclaw, Poland.
    Kochman, Michal
    Linköping University, Department of Physics, Chemistry and Biology, Bioinformatics. Linköping University, Faculty of Science & Engineering. Univ Coll London UCL, England.
    Mierzwicki, Krzysztof
    independent researcher.
    Photoinduced double proton transfer in the glyoxal-methanol complex along T-1 reaction path - a quantum chemical topological study2021In: Journal of Molecular Structure, ISSN 0022-2860, E-ISSN 1872-8014, Vol. 1227, article id 129426Article in journal (Refereed)
    Abstract [en]

    The experimentally confirmed double proton transfer (DPT) reaction in glyoxal-methanol complex follows a complicated mechanism triggered by the excitation of the complex to the lowest singlet excited electronic state. The mechanism involves two complementary pathways, the first of which proceeds exclusively in the singlet manifold. The competing one, which is studied here with the use of quantum chemical topological methods, involves the lowest triplet state. Both Atoms-in-Molecules approach and Electron Localizability Indicator based approach demonstrate that protons dressed with some amount of electron density migrate to and from the methanol, which leads to the rearrangement of four covalent bonds. The transition structure nearly coincides with the dissociation of the covalent C-H bond in glyoxal. DPT proceeds through a structure formed by the protonated [MeOH2](+0.)(66), with H atoms equidistant to O atom, and deprotonated [C2O2H](-0.)(66). The key stages of the evolution of the crucial covalent bonds along the intrinsic reaction path have been demonstrated. (C) 2020 Elsevier B.V. All rights reserved.

  • 34.
    Bittmann, Simon F.
    et al.
    Max Planck Inst Struct and Dynam Matter, Germany.
    Dsouza, Raison
    Max Planck Inst Struct and Dynam Matter, Germany; Univ Hamburg, Germany.
    Siddiqui, Khalid M.
    Max Planck Inst Struct and Dynam Matter, Germany.
    Hayes, Stuart A.
    Max Planck Inst Struct and Dynam Matter, Germany.
    Rossos, Andreas
    Max Planck Inst Struct and Dynam Matter, Germany.
    Corthey, Gaston
    Max Planck Inst Struct and Dynam Matter, Germany; Univ Nacl San Martin, Argentina.
    Kochman, Michal
    Linköping University, Department of Physics, Chemistry and Biology, Bioinformatics. Linköping University, Faculty of Science & Engineering. Max Planck Inst Struct and Dynam Matter, Germany.
    Prokhorenko, Valentyn I.
    Max Planck Inst Struct and Dynam Matter, Germany.
    Murphy, R. Scott
    Univ Regina, Canada.
    Schwoerer, Heinrich
    Max Planck Inst Struct and Dynam Matter, Germany.
    Miller, R. J. Dwayne
    Max Planck Inst Struct and Dynam Matter, Germany; Univ Toronto, Canada; Univ Toronto, Canada.
    Ultrafast ring-opening and solvent-dependent product relaxation of photochromic spironaphthopyran2019In: Physical Chemistry, Chemical Physics - PCCP, ISSN 1463-9076, E-ISSN 1463-9084, Vol. 21, no 33, p. 18119-18127Article in journal (Refereed)
    Abstract [en]

    The ultrafast dynamics of unsubstituted spironaphthopyran (SNP) were investigated using femtosecond transient UV and visible absorption spectroscopy in three different solvents and by semi-classical nuclear dynamics simulations. The primary ring-opening of the pyran unit was found to occur in 300 fs yielding a non-planar intermediate in the first singlet excited state (S-1). Subsequent planarisation and relaxation to the product ground state proceed through barrier crossing on the S-1 potential energy surface (PES) and take place within 1.1 ps after excitation. Simulations show that more than 90% of the trajectories involving C-O bond elongation lead to the planar, open-ring product, while relaxation back to the S-0 of the closed-ring form is accompanied by C-N elongation. All ensuing spectral dynamics are ascribed to vibrational relaxation and thermalisation of the product with a time constant of 13 ps. The latter shows dependency on characteristics of the solvent with solvent relaxation kinetics playing a role.

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  • 35.
    Björn, Niclas
    et al.
    Linköping University, Department of Biomedical and Clinical Sciences, Division of Drug Research. Linköping University, Faculty of Medicine and Health Sciences.
    Badam, Tejaswi Venkata Satya
    Linköping University, Department of Physics, Chemistry and Biology, Bioinformatics. Linköping University, Faculty of Science & Engineering. School of Bioscience, Systems Biology Research Centre, University of Skövde.
    Spalinskas, Rapolas
    Science for Life Laboratory, School of Engineering Sciences in Chemistry, Biotechnology and Health, Department of Gene Technology, KTH Royal Institute of Technology.
    Brandén, Eva
    Department of Respiratory Medicine, Gävle Hospital; Centre for Research and Development, Uppsala University/Region Gävleborg, Gävle.
    Koyi, Hirsh
    Department of Respiratory Medicine, Gävle Hospital; Centre for Research and Development, Uppsala University/Region Gävleborg, Gävle.
    Lewensohn, Rolf
    Thoracic Oncology Unit, Tema Cancer, Karolinska University Hospital; Department of Oncology-Pathology, Karolinska Institutet.
    De Petris, Luigi
    Thoracic Oncology Unit, Tema Cancer, Karolinska University Hospital; Department of Oncology-Pathology, Karolinska Institutet.
    Lubovac-Pilav, Zelmina
    School of Bioscience, Systems Biology Research Centre, University of Skövde.
    Sahlén, Pelin
    Science for Life Laboratory, School of Engineering Sciences in Chemistry, Biotechnology and Health, Department of Gene Technology, KTH Royal Institute of Technology.
    Lundeberg, Joakim
    Science for Life Laboratory, School of Engineering Sciences in Chemistry, Biotechnology and Health, Department of Gene Technology, KTH Royal Institute of Technology.
    Gustafsson, Mika
    Linköping University, Department of Physics, Chemistry and Biology, Bioinformatics. Linköping University, Faculty of Science & Engineering.
    Gréen, Henrik
    Linköping University, Department of Biomedical and Clinical Sciences, Division of Drug Research. Linköping University, Faculty of Medicine and Health Sciences. Science for Life Laboratory, School of Engineering Sciences in Chemistry, Biotechnology and Health, Department of Gene Technology, KTH Royal Institute of Technology; Department of Forensic Genetics and Forensic Toxicology, National Board of Forensic Medicine, Linköping.
    Whole-genome sequencing and gene network modules predict gemcitabine/carboplatin-induced myelosuppression in non-small cell lung cancer patients2020In: npj Systems Biology and Applications, ISSN 2056-7189, Vol. 6, no 1, article id 25Article in journal (Refereed)
    Abstract [en]

    Gemcitabine/carboplatin chemotherapy commonly induces myelosuppression, including neutropenia, leukopenia, and thrombocytopenia. Predicting patients at risk of these adverse drug reactions (ADRs) and adjusting treatments accordingly is a long-term goal of personalized medicine. This study used whole-genome sequencing (WGS) of blood samples from 96 gemcitabine/carboplatin-treated non-small cell lung cancer (NSCLC) patients and gene network modules for predicting myelosuppression. Association of genetic variants in PLINK found 4594, 5019, and 5066 autosomal SNVs/INDELs with p ≤ 1 × 10−3 for neutropenia, leukopenia, and thrombocytopenia, respectively. Based on the SNVs/INDELs we identified the toxicity module, consisting of 215 unique overlapping genes inferred from MCODE-generated gene network modules of 350, 345, and 313 genes, respectively. These module genes showed enrichment for differentially expressed genes in rat bone marrow, human bone marrow, and human cell lines exposed to carboplatin and gemcitabine (p < 0.05). Then using 80% of the patients as training data, random LASSO reduced the number of SNVs/INDELs in the toxicity module into a feasible prediction model consisting of 62 SNVs/INDELs that accurately predict both the training and the test (remaining 20%) data with high (CTCAE 3–4) and low (CTCAE 0–1) maximal myelosuppressive toxicity completely, with the receiver-operating characteristic (ROC) area under the curve (AUC) of 100%. The present study shows how WGS, gene network modules, and random LASSO can be used to develop a feasible and tested model for predicting myelosuppressive toxicity. Although the proposed model predicts myelosuppression in this study, further evaluation in other studies is required to determine its reproducibility, usability, and clinical effect.

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  • 36.
    Björnsson, Bergthor
    et al.
    Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Surgery, Orthopaedics and Cancer Treatment, Department of Surgery in Linköping. Linköping University, Department of Biomedical and Clinical Sciences, Division of Surgery, Orthopedics and Oncology.
    Borrebaeck, Carl
    Lund Univ, Sweden.
    Elander, Nils
    Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Surgery, Orthopaedics and Cancer Treatment, Department of Oncology. Linköping University, Department of Biomedical and Clinical Sciences, Division of Surgery, Orthopedics and Oncology.
    Gasslander, Thomas
    Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Surgery, Orthopaedics and Cancer Treatment, Department of Surgery in Linköping. Linköping University, Department of Biomedical and Clinical Sciences, Division of Surgery, Orthopedics and Oncology.
    Gawel, Danuta
    Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Department of Biomedical and Clinical Sciences, Division of Children's and Women's Health.
    Gustafsson, Mika
    Linköping University, Department of Physics, Chemistry and Biology, Bioinformatics. Linköping University, Faculty of Science & Engineering.
    Jornsten, Rebecka
    Univ Gothenburg, Sweden; Chalmers Univ Technol, Sweden.
    Jung Lee, Eun Jung
    Linköping University, Department of Clinical and Experimental Medicine, Division of Children's and Women's health. Linköping University, Faculty of Medicine and Health Sciences. Yonsei Univ, South Korea.
    Li, Xinxiu
    Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Department of Biomedical and Clinical Sciences, Division of Children's and Women's Health.
    Lilja, Sandra
    Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Department of Biomedical and Clinical Sciences, Division of Children's and Women's Health.
    Martinez, David
    Linköping University, Department of Physics, Chemistry and Biology, Bioinformatics. Linköping University, Faculty of Science & Engineering.
    Matussek, Andreas
    Karolinska Univ Hosp, Sweden; Dept Lab Med, Sweden.
    Sandström, Per
    Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Surgery, Orthopaedics and Cancer Treatment, Department of Surgery in Linköping. Linköping University, Department of Biomedical and Clinical Sciences, Division of Surgery, Orthopedics and Oncology.
    Schäfer, Samuel
    Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Department of Biomedical and Clinical Sciences, Division of Children's and Women's Health.
    Stenmarker, Margaretha
    Futurum Acad Hlth and Care, Sweden; Inst Clin Sci, Sweden.
    Sun, Xiao-Feng
    Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Surgery, Orthopaedics and Cancer Treatment, Department of Oncology. Linköping University, Department of Biomedical and Clinical Sciences, Division of Surgery, Orthopedics and Oncology.
    Sysoev, Oleg
    Linköping University, Department of Computer and Information Science, The Division of Statistics and Machine Learning. Linköping University, Faculty of Arts and Sciences.
    Zhang, Huan
    Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Department of Biomedical and Clinical Sciences, Division of Children's and Women's Health.
    Benson, Mikael
    Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center of Paediatrics and Gynaecology and Obstetrics, H.K.H. Kronprinsessan Victorias barn- och ungdomssjukhus. Linköping University, Department of Biomedical and Clinical Sciences, Division of Children's and Women's Health.
    Digital twins to personalize medicine2020In: Genome Medicine, ISSN 1756-994X, E-ISSN 1756-994X, Vol. 12, no 1, article id 4Article in journal (Other academic)
    Abstract [en]

    Personalized medicine requires the integration and processing of vast amounts of data. Here, we propose a solution to this challenge that is based on constructing Digital Twins. These are high-resolution models of individual patients that are computationally treated with thousands of drugs to find the drug that is optimal for the patient.

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  • 37.
    Borgmastars, Emmy
    et al.
    Umea Univ, Sweden.
    de Weerd, Hendrik Arnold
    Linköping University, Department of Physics, Chemistry and Biology, Bioinformatics. Linköping University, Faculty of Science & Engineering. Univ Skovde, Sweden.
    Lubovac-Pilav, Zelmina
    Univ Skovde, Sweden.
    Sund, Malin
    Umea Univ, Sweden.
    miRFA: an automated pipeline for microRNA functional analysis with correlation support from TCGA and TCPA expression data in pancreatic cancer2019In: BMC Bioinformatics, E-ISSN 1471-2105, Vol. 20, article id 393Article in journal (Refereed)
    Abstract [en]

    BackgroundMicroRNAs (miRNAs) are small RNAs that regulate gene expression at a post-transcriptional level and are emerging as potentially important biomarkers for various disease states, including pancreatic cancer. In silico-based functional analysis of miRNAs usually consists of miRNA target prediction and functional enrichment analysis of miRNA targets. Since miRNA target prediction methods generate a large number of false positive target genes, further validation to narrow down interesting candidate miRNA targets is needed. One commonly used method correlates miRNA and mRNA expression to assess the regulatory effect of a particular miRNA.The aim of this study was to build a bioinformatics pipeline in R for miRNA functional analysis including correlation analyses between miRNA expression levels and its targets on mRNA and protein expression levels available from the cancer genome atlas (TCGA) and the cancer proteome atlas (TCPA). TCGA-derived expression data of specific mature miRNA isoforms from pancreatic cancer tissue was used.ResultsFifteen circulating miRNAs with significantly altered expression levels detected in pancreatic cancer patients were queried separately in the pipeline. The pipeline generated predicted miRNA target genes, enriched gene ontology (GO) terms and Kyoto encyclopedia of genes and genomes (KEGG) pathways. Predicted miRNA targets were evaluated by correlation analyses between each miRNA and its predicted targets. MiRNA functional analysis in combination with Kaplan-Meier survival analysis suggest that hsa-miR-885-5p could act as a tumor suppressor and should be validated as a potential prognostic biomarker in pancreatic cancer.ConclusionsOur miRNA functional analysis (miRFA) pipeline can serve as a valuable tool in biomarker discovery involving mature miRNAs associated with pancreatic cancer and could be developed to cover additional cancer types. Results for all mature miRNAs in TCGA pancreatic adenocarcinoma dataset can be studied and downloaded through a shiny web application at https://emmbor.shinyapps.io/mirfa/.

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  • 38.
    Bresel, Anders
    et al.
    Linköping University, Department of Physics, Chemistry and Biology, Biomolecular and Organic Electronics . Linköping University, The Institute of Technology.
    Persson, Bengt
    Linköping University, Department of Physics, Chemistry and Biology, Bioinformatics . Linköping University, The Institute of Technology.
    GenomeLKPG: A comprehensive proteome sequencedatabase for taxonomy studies2008Article in journal (Refereed)
    Abstract [en]

    Background: In order to perform taxonomically unbiased analyses of protein relationships, there is a need ofcomplete proteomes rather than databases with bias towards well characterized protein families. However, nocomprehensive resource of completed proteomes is currently available. Instead, the proteomes need to be down-loaded manually from di®erent servers, all using different filename conventions and fasta header formats.

    Results: We have developed a semi-automatic algorithm that retrieves complete proteomes from multiple FTP-servers and maps the species-speci¯c sequence entries to the NCBI taxonomy. The compiled data is provided ina sequence database named genomeLKPG.

    Conclusions: The usefulness of genomeLKPG is proven in several published taxonomical studies.

  • 39. Order onlineBuy this publication >>
    Bresell, Anders
    Linköping University, Department of Physics, Chemistry and Biology, Bioinformatics. Linköping University, The Institute of Technology.
    Characterization of protein families, sequence patterns, and functional annotations in large data sets2008Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Bioinformatics involves storing, analyzing and making predictions on massive amounts of protein and nucleotide sequence data. The thesis consists of six papers and is focused on proteins. It describes the utilization of bioinformatics techniques to characterize protein families and to detect patterns in gene expression and in polypeptide occurrences. Two protein families were bioinformatically characterized - the membrane associated proteins in eicosanoid and glutathione metabolism (MAPEG) and the Tripartite motif (TRIM) protein families.

    In the study of the MAPEG super-family, application of different bioinformatic methods made it possible to characterize many new members leading to a doubling of the family size. Furthermore, the MAPEG members were subdivided into families. Remarkably, in six families with previously predominantly mammalian members, fish representatives were also now detected, which dated the origin of these families back to the Cambrium ”species explosion”, thus earlier than previously anticipated. Sequence comparisons made it possible to define diagnostic sequence patterns that can be used in genome annotations. Upon publication of several MAPEG structures, these patterns were confirmed to be part of the active sites.

    In the TRIM study, the bioinformatic analyses made it possible to subdivide the proteins into three subtypes and to characterize a large number of members. In addition, the analyses showed crucial structural dependencies between the RING and the B-box domains of the TRIM member

    Ro52. The linker region between the two domains, denoted RBL, is known

    to be disease associated. Now, an amphipathic helix was found to be a

    characteristic feature of the RBL region, which also was used to divide the family into three subtypes.

    The ontology annotation treebrowser (OAT) tool was developed to detect functional similarities or common concepts in long lists of proteins or genes, typically generated from proteomics or microarray experiments. OAT was the first annotation browser to include both Gene Ontology (GO) and Medical Subject Headings (MeSH) into the same framework. The complementarity of these two ontologies was demonstrated. OAT was used in the TRIM study to detect differences in functional annotations between the subtypes.

    In the oligopeptide study, we investigated pentapeptide patterns that were over- or under-represented in the current de facto standard database of protein knowledge and a set of completed genomes, compared to what could be expected from amino acid compositions. We found three predominant categories of patterns: (i) patterns originating from frequently occurring families, e.g. respiratory chain-associated proteins and translation machinery proteins; (ii) proteins with structurally and/or functionally favored patterns; (iii) multicopy species-specific retrotransposons, only found in the genome set. Such patterns may influence amino acid residue based prediction algorithms. These findings in the oligopeptide study were utilized for development of a new method that detects translated introns in unverified protein predictions, which are available in great numbers due to the many completed and ongoing genome projects.

    A new comprehensive database of protein sequences from completed genomes was developed, denoted genomeLKPG. This database was of central importance in the MAPEG, TRIM and oligopeptide studies. The new sequence database has also been proven useful in several other studies.

    List of papers
    1. Bioinformatic and enzymatic characterization of the MAPEG superfamily
    Open this publication in new window or tab >>Bioinformatic and enzymatic characterization of the MAPEG superfamily
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    2005 (English)In: The FEBS Journal, ISSN 1742-464X, E-ISSN 1742-4658, Vol. 272, no 7, p. 1688-1703Article in journal (Refereed) Published
    Abstract [en]

    The membrane associated proteins in eicosanoid and glutathione metabolism (MAPEG) superfamily includes structurally related membrane proteins with diverse functions of widespread origin. A total of 136 proteins belonging to the MAPEG superfamily were found in database and genome screenings. The members were found in prokaryotes and eukaryotes, but not in any archaeal organism. Multiple sequence alignments and calculations of evolutionary trees revealed a clear subdivision of the eukaryotic MAPEG members, corresponding to the six families of microsomal glutathione transferases (MGST) 1, 2 and 3, leukotriene C4 synthase (LTC4), 5-lipoxygenase activating protein (FLAP), and prostaglandin E synthase. Prokaryotes contain at least two distinct potential ancestral subfamilies, of which one is unique, whereas the other most closely resembles enzymes that belong to the MGST2/FLAP/LTC4 synthase families. The insect members are most similar to MGST1/prostaglandin E synthase. With the new data available, we observe that fish enzymes are present in all six families, showing an early origin for MAPEG family differentiation. Thus, the evolutionary origins and relationships of the MAPEG superfamily can be defined, including distinct sequence patterns characteristic for each of the subfamilies. We have further investigated and functionally characterized representative gene products from Escherichia coli, Synechocystis sp., Arabidopsis thaliana and Drosophila melanogaster, and the fish liver enzyme, purified from pike (Esox lucius). Protein overexpression and enzyme activity analysis demonstrated that all proteins catalyzed the conjugation of 1-chloro-2,4-dinitrobenzene with reduced glutathione. The E. coli protein displayed glutathione transferase activity of 0.11 µmol·min−1·mg−1 in the membrane fraction from bacteria overexpressing the protein. Partial purification of the Synechocystis sp. protein yielded an enzyme of the expected molecular mass and an N-terminal amino acid sequence that was at least 50% pure, with a specific activity towards 1-chloro-2,4-dinitrobenzene of 11 µmol·min−1·mg−1. Yeast microsomes expressing the Arabidopsis enzyme showed an activity of 0.02 µmol·min−1·mg−1, whereas the Drosophila enzyme expressed in E. coli was highly active at 3.6 µmol·min−1·mg−1. The purified pike enzyme is the most active MGST described so far with a specific activity of 285 µmol·min−1·mg−1. Drosophila and pike enzymes also displayed glutathione peroxidase activity towards cumene hydroperoxide (0.4 and 2.2 µmol·min−1·mg−1, respectively). Glutathione transferase activity can thus be regarded as a common denominator for a majority of MAPEG members throughout the kingdoms of life whereas glutathione peroxidase activity occurs in representatives from the MGST1, 2 and 3 and PGES subfamilies.

    Keywords
    MAPEG, microsomal glutathione transferase, prostaglandin, leukotriene
    National Category
    Natural Sciences
    Identifiers
    urn:nbn:se:liu:diva-12886 (URN)10.1111/j.1742-4658.2005.04596.x (DOI)
    Available from: 2008-01-28 Created: 2008-01-28 Last updated: 2017-12-14Bibliographically approved
    2. The fellowship of the RING: The RING-B-box linker region (RBL) interacts with the RING in TRIM21/Ro52, contributes to an autoantigenic epitope in Sjögren's syndrome, and is an integral and conserved region in TRIM proteins
    Open this publication in new window or tab >>The fellowship of the RING: The RING-B-box linker region (RBL) interacts with the RING in TRIM21/Ro52, contributes to an autoantigenic epitope in Sjögren's syndrome, and is an integral and conserved region in TRIM proteins
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    2008 (English)In: Journal of Molecular Biology, ISSN 0022-2836, E-ISSN 1089-8638, Vol. 377, no 2, p. 431-449Article in journal (Refereed) Published
    Abstract [en]

    Ro52 is a major autoantigen that is targeted in the autoimmune disease Sjögren syndrome and belongs to the tripartite motif (TRIM) protein family. Disease-related antigenic epitopes are mainly found in the coiled-coil domain of Ro52, but one such epitope is located in the Zn2+-binding region, which comprises an N-terminal RING followed by a B-box, separated by a ∼40-residue linker peptide. In the present study, we extend the structural, biophysical, and immunological knowledge of this RING-B-box linker (RBL) by employing an array of methods. Our bioinformatic investigations show that the RBL sequence motif is unique to TRIM proteins and can be classified into three distinct subtypes. The RBL regions of all three subtypes are as conserved as their known flanking domains, and all are predicted to comprise an amphipathic helix. This helix formation is confirmed by circular dichroism spectroscopy and is dependent on the presence of the RING. Immunological studies show that the RBL is part of a conformation-dependent epitope, and its antigenicity is likewise dependent on a structured RING domain. Recombinant Ro52 RING-RBL exists as a monomer in vitro, and binding of two Zn2+ increases its stability. Regions stabilized by Zn2+ binding are identified by limited proteolysis and matrix-assisted laser desorption/ionization mass spectrometry. Furthermore, the residues of the RING and linker that interact with each other are identified by analysis of protection patterns, which, together with bioinformatic and biophysical data, enabled us to propose a structural model of the RING-RBL based on modeling and docking experiments. Sequence similarities and evolutionary sequence patterns suggest that the results obtained from Ro52 are extendable to the entire TRIM protein family.

    Keywords
    Ro52; TRIM21; RING; linker; zinc binding
    National Category
    Natural Sciences
    Identifiers
    urn:nbn:se:liu:diva-12887 (URN)10.1016/j.jmb.2008.01.005 (DOI)
    Available from: 2008-01-28 Created: 2008-01-28 Last updated: 2017-12-14Bibliographically approved
    3. Ontology annotation treebrowser: an interactive tool where the complementarity of medical subject headings and gene ontology improves the interpretation of gene lists
    Open this publication in new window or tab >>Ontology annotation treebrowser: an interactive tool where the complementarity of medical subject headings and gene ontology improves the interpretation of gene lists
    2006 (English)In: Applied Bioinformatics, ISSN 1175-5636, Vol. 5, no 4, p. 225-236Article in journal (Refereed) Published
    Abstract [en]

    Gene expression and proteomics analysis allow the investigation of thousands of biomolecules in parallel. This results in a long list of interesting genes or proteins and a list of annotation terms in the order of thousands. It is not a trivial task to understand such a gene list and it would require extensive efforts to bring together the overwhelming amounts of associated information from the literature and databases. Thus, it is evident that we need ways of condensing and filtering this information. An excellent way to represent knowledge is to use ontologies, where it is possible to group genes or terms with overlapping context, rather than studying one-dimensional lists of keywords. Therefore, we have built the ontology annotation treebrowser (OAT) to represent, condense, filter and summarise the knowledge associated with a list of genes or proteins.

    The OAT system consists of two disjointed parts; a MySQL® database named OATdb, and a treebrowser engine that is implemented as a web interface. The OAT system is implemented using Perl scripts on an Apache web server and the gene, ontology and annotation data is stored in a relational MySQL® database. In OAT, we have harmonized the two ontologies of medical subject headings (MeSH) and gene ontology (GO), to enable us to use knowledge both from the literature and the annotation projects in the same tool. OAT includes multiple gene identifier sets, which are merged internally in the OAT database. We have also generated novel MeSH annotations by mapping accession numbers to MEDLINE entries.

    The ontology browser OAT was created to facilitate the analysis of gene lists. It can be browsed dynamically, so that a scientist can interact with the data and govern the outcome. Test statistics show which branches are enriched. We also show that the two ontologies complement each other, with surprisingly low overlap, by mapping annotations to the Unified Medical Language System®.

    We have developed a novel interactive annotation browser that is the first to incorporate both MeSH and GO for improved interpretation of gene lists. With OAT, we illustrate the benefits of combining MeSH and GO for understanding gene lists. OAT is available as a public web service at: http://www.ifm.liu.se/bioinfo/oat

    National Category
    Engineering and Technology
    Identifiers
    urn:nbn:se:liu:diva-12888 (URN)
    Available from: 2008-01-28 Created: 2008-01-28 Last updated: 2009-11-07Bibliographically approved
    4. Characterization of oligopeptide patterns in large protein sets
    Open this publication in new window or tab >>Characterization of oligopeptide patterns in large protein sets
    2007 (English)In: BMC Genomics, E-ISSN 1471-2164, Vol. 8, no 346, p. 1-15Article in journal (Refereed) Published
    Abstract [en]

    Background: Recent sequencing projects and the growth of sequence data banks enable oligopeptide patterns to be characterized on a genome or kingdom level. Several studies have focused on kingdom or habitat classifications based on the abundance of short peptide patterns. There have also been efforts at local structural prediction based on short sequence motifs. Oligopeptide patterns undoubtedly carry valuable information content. Therefore, it is important to characterize these informational peptide patterns to shed light on possible new applications and the pitfalls implicit in neglecting bias in peptide patterns.

    Results: We have studied four classes of pentapeptide patterns (designated POP, NEP, ORP and URP) in the kingdoms archaea, bacteria and eukaryotes. POP are highly abundant patterns statistically not expected to exist; NEP are patterns that do not exist but are statistically expected to; ORP are patterns unique to a kingdom; and URP are patterns excluded from a kingdom. We used two data sources: the de facto standard of protein knowledge Swiss-Prot, and a set of 386 completely sequenced genomes. For each class of peptides we looked at the 100 most extreme and found both known and unknown sequence features. Most of the known sequence motifs can be explained on the basis of the protein families from which they originate.

    Conclusion: We find an inherent bias of certain oligopeptide patterns in naturally occurring proteins that cannot be explained solely on the basis of residue distribution in single proteins, kingdoms or databases. We see three predominant categories of patterns: (i) patterns widespread in a kingdom such as those originating from respiratory chain-associated proteins and translation machinery; (ii) proteins with structurally and/or functionally favored patterns, which have not yet been ascribed this role; (iii) multicopy species-specific retrotransposons, only found in the genome set. These categories will affect the accuracy of sequence pattern algorithms that rely mainly on amino acid residue usage. Methods presented in this paper may be used to discover targets for antibiotics, as we identify numerous examples of kingdom-specific antigens among our peptide classes. The methods may also be useful for detecting coding regions of genes.

    National Category
    Natural Sciences
    Identifiers
    urn:nbn:se:liu:diva-12889 (URN)10.1186/1471-2164-8-346 (DOI)
    Available from: 2008-01-28 Created: 2008-01-28 Last updated: 2024-01-17Bibliographically approved
    5. Using SVM and tripeptide patterns to detect translated introns
    Open this publication in new window or tab >>Using SVM and tripeptide patterns to detect translated introns
    2007 (English)In: BMC Bioinformatics, E-ISSN 1471-2105Article in journal (Refereed) Submitted
    National Category
    Natural Sciences
    Identifiers
    urn:nbn:se:liu:diva-12890 (URN)
    Available from: 2008-01-28 Created: 2008-01-28 Last updated: 2024-01-17
    6. GenomeLKPG: A comprehensive proteome sequencedatabase for taxonomy studies
    Open this publication in new window or tab >>GenomeLKPG: A comprehensive proteome sequencedatabase for taxonomy studies
    2008 (English)Article in journal (Refereed) Submitted
    Abstract [en]

    Background: In order to perform taxonomically unbiased analyses of protein relationships, there is a need ofcomplete proteomes rather than databases with bias towards well characterized protein families. However, nocomprehensive resource of completed proteomes is currently available. Instead, the proteomes need to be down-loaded manually from di®erent servers, all using different filename conventions and fasta header formats.

    Results: We have developed a semi-automatic algorithm that retrieves complete proteomes from multiple FTP-servers and maps the species-speci¯c sequence entries to the NCBI taxonomy. The compiled data is provided ina sequence database named genomeLKPG.

    Conclusions: The usefulness of genomeLKPG is proven in several published taxonomical studies.

    National Category
    Natural Sciences
    Identifiers
    urn:nbn:se:liu:diva-52933 (URN)
    Available from: 2010-01-13 Created: 2010-01-13 Last updated: 2010-01-13
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  • 40.
    Bresell, Anders
    et al.
    Linköping University, Department of Physics, Chemistry and Biology, Bioinformatics . Linköping University, The Institute of Technology.
    Persson, Bengt
    Linköping University, Department of Physics, Chemistry and Biology, Bioinformatics . Linköping University, The Institute of Technology.
    Characterization of oligopeptide patterns in large protein sets2007In: BMC Genomics, E-ISSN 1471-2164, Vol. 8, no 346, p. 1-15Article in journal (Refereed)
    Abstract [en]

    Background: Recent sequencing projects and the growth of sequence data banks enable oligopeptide patterns to be characterized on a genome or kingdom level. Several studies have focused on kingdom or habitat classifications based on the abundance of short peptide patterns. There have also been efforts at local structural prediction based on short sequence motifs. Oligopeptide patterns undoubtedly carry valuable information content. Therefore, it is important to characterize these informational peptide patterns to shed light on possible new applications and the pitfalls implicit in neglecting bias in peptide patterns.

    Results: We have studied four classes of pentapeptide patterns (designated POP, NEP, ORP and URP) in the kingdoms archaea, bacteria and eukaryotes. POP are highly abundant patterns statistically not expected to exist; NEP are patterns that do not exist but are statistically expected to; ORP are patterns unique to a kingdom; and URP are patterns excluded from a kingdom. We used two data sources: the de facto standard of protein knowledge Swiss-Prot, and a set of 386 completely sequenced genomes. For each class of peptides we looked at the 100 most extreme and found both known and unknown sequence features. Most of the known sequence motifs can be explained on the basis of the protein families from which they originate.

    Conclusion: We find an inherent bias of certain oligopeptide patterns in naturally occurring proteins that cannot be explained solely on the basis of residue distribution in single proteins, kingdoms or databases. We see three predominant categories of patterns: (i) patterns widespread in a kingdom such as those originating from respiratory chain-associated proteins and translation machinery; (ii) proteins with structurally and/or functionally favored patterns, which have not yet been ascribed this role; (iii) multicopy species-specific retrotransposons, only found in the genome set. These categories will affect the accuracy of sequence pattern algorithms that rely mainly on amino acid residue usage. Methods presented in this paper may be used to discover targets for antibiotics, as we identify numerous examples of kingdom-specific antigens among our peptide classes. The methods may also be useful for detecting coding regions of genes.

  • 41.
    Bresell, Anders
    et al.
    Linköping University, Department of Physics, Chemistry and Biology, Bioinformatics . Linköping University, The Institute of Technology.
    Persson, Bengt
    Linköping University, Department of Physics, Chemistry and Biology, Bioinformatics . Linköping University, The Institute of Technology.
    Using SVM and tripeptide patterns to detect translated introns2007In: BMC Bioinformatics, E-ISSN 1471-2105Article in journal (Refereed)
  • 42.
    Bresell, Anders
    et al.
    Linköping University, Department of Physics, Chemistry and Biology, Bioinformatics . Linköping University, The Institute of Technology.
    Servenius, Bo
    Biological Sciences, AstraZeneca R&D Lund, Sweden.
    Persson, Bengt
    Linköping University, Department of Physics, Chemistry and Biology, Bioinformatics . Linköping University, The Institute of Technology.
    Ontology annotation treebrowser: an interactive tool where the complementarity of medical subject headings and gene ontology improves the interpretation of gene lists2006In: Applied Bioinformatics, ISSN 1175-5636, Vol. 5, no 4, p. 225-236Article in journal (Refereed)
    Abstract [en]

    Gene expression and proteomics analysis allow the investigation of thousands of biomolecules in parallel. This results in a long list of interesting genes or proteins and a list of annotation terms in the order of thousands. It is not a trivial task to understand such a gene list and it would require extensive efforts to bring together the overwhelming amounts of associated information from the literature and databases. Thus, it is evident that we need ways of condensing and filtering this information. An excellent way to represent knowledge is to use ontologies, where it is possible to group genes or terms with overlapping context, rather than studying one-dimensional lists of keywords. Therefore, we have built the ontology annotation treebrowser (OAT) to represent, condense, filter and summarise the knowledge associated with a list of genes or proteins.

    The OAT system consists of two disjointed parts; a MySQL® database named OATdb, and a treebrowser engine that is implemented as a web interface. The OAT system is implemented using Perl scripts on an Apache web server and the gene, ontology and annotation data is stored in a relational MySQL® database. In OAT, we have harmonized the two ontologies of medical subject headings (MeSH) and gene ontology (GO), to enable us to use knowledge both from the literature and the annotation projects in the same tool. OAT includes multiple gene identifier sets, which are merged internally in the OAT database. We have also generated novel MeSH annotations by mapping accession numbers to MEDLINE entries.

    The ontology browser OAT was created to facilitate the analysis of gene lists. It can be browsed dynamically, so that a scientist can interact with the data and govern the outcome. Test statistics show which branches are enriched. We also show that the two ontologies complement each other, with surprisingly low overlap, by mapping annotations to the Unified Medical Language System®.

    We have developed a novel interactive annotation browser that is the first to incorporate both MeSH and GO for improved interpretation of gene lists. With OAT, we illustrate the benefits of combining MeSH and GO for understanding gene lists. OAT is available as a public web service at: http://www.ifm.liu.se/bioinfo/oat

  • 43.
    Bresell, Anders
    et al.
    Linköping University, Department of Physics, Chemistry and Biology, Bioinformatics . Linköping University, The Institute of Technology.
    Weinander, Rolf
    Department of Medicine, Division of Rheumatology Unit, Karolinska Institutet, Stockholm.
    Wiklund, Ronney
    Department of Plant Biology & Forestry Genetics, Swedish Agricultural University, Uppsala.
    Eriksson, Jan
    Department of Plant Biology & Forestry Genetics, Swedish Agricultural University, Uppsala.
    Jansson, Christer
    Department of Plant Biology & Forestry Genetics, Swedish Agricultural University, Uppsala.
    Persson, Bengt
    Linköping University, Department of Physics, Chemistry and Biology, Bioinformatics . Linköping University, The Institute of Technology.
    Jakobsson, Per-Johan
    Department of Medicine, Division of Rheumatology Unit, Karolinska Institutet, Stockholm.
    Morgenstern, Ralf
    Institute of Environmental Medicine Karolinska Institutet, Stockholm.
    Lundqvist, Gerd
    Institute of Environmental Medicine Karolinska Institutet, Stockholm.
    Raza, Haider
    Institute of Environmental Medicine Karolinska Institutet, Stockholm.
    Shimoji, Miyuki
    Institute of Environmental Medicine Karolinska Institutet, Stockholm.
    Sun, Tie-Hua
    Institute of Environmental Medicine Karolinska Institutet, Stockholm.
    Balk, Lennart
    Stockholm Marine Research Centre, University of Stockholm.
    Bioinformatic and enzymatic characterization of the MAPEG superfamily2005In: The FEBS Journal, ISSN 1742-464X, E-ISSN 1742-4658, Vol. 272, no 7, p. 1688-1703Article in journal (Refereed)
    Abstract [en]

    The membrane associated proteins in eicosanoid and glutathione metabolism (MAPEG) superfamily includes structurally related membrane proteins with diverse functions of widespread origin. A total of 136 proteins belonging to the MAPEG superfamily were found in database and genome screenings. The members were found in prokaryotes and eukaryotes, but not in any archaeal organism. Multiple sequence alignments and calculations of evolutionary trees revealed a clear subdivision of the eukaryotic MAPEG members, corresponding to the six families of microsomal glutathione transferases (MGST) 1, 2 and 3, leukotriene C4 synthase (LTC4), 5-lipoxygenase activating protein (FLAP), and prostaglandin E synthase. Prokaryotes contain at least two distinct potential ancestral subfamilies, of which one is unique, whereas the other most closely resembles enzymes that belong to the MGST2/FLAP/LTC4 synthase families. The insect members are most similar to MGST1/prostaglandin E synthase. With the new data available, we observe that fish enzymes are present in all six families, showing an early origin for MAPEG family differentiation. Thus, the evolutionary origins and relationships of the MAPEG superfamily can be defined, including distinct sequence patterns characteristic for each of the subfamilies. We have further investigated and functionally characterized representative gene products from Escherichia coli, Synechocystis sp., Arabidopsis thaliana and Drosophila melanogaster, and the fish liver enzyme, purified from pike (Esox lucius). Protein overexpression and enzyme activity analysis demonstrated that all proteins catalyzed the conjugation of 1-chloro-2,4-dinitrobenzene with reduced glutathione. The E. coli protein displayed glutathione transferase activity of 0.11 µmol·min−1·mg−1 in the membrane fraction from bacteria overexpressing the protein. Partial purification of the Synechocystis sp. protein yielded an enzyme of the expected molecular mass and an N-terminal amino acid sequence that was at least 50% pure, with a specific activity towards 1-chloro-2,4-dinitrobenzene of 11 µmol·min−1·mg−1. Yeast microsomes expressing the Arabidopsis enzyme showed an activity of 0.02 µmol·min−1·mg−1, whereas the Drosophila enzyme expressed in E. coli was highly active at 3.6 µmol·min−1·mg−1. The purified pike enzyme is the most active MGST described so far with a specific activity of 285 µmol·min−1·mg−1. Drosophila and pike enzymes also displayed glutathione peroxidase activity towards cumene hydroperoxide (0.4 and 2.2 µmol·min−1·mg−1, respectively). Glutathione transferase activity can thus be regarded as a common denominator for a majority of MAPEG members throughout the kingdoms of life whereas glutathione peroxidase activity occurs in representatives from the MGST1, 2 and 3 and PGES subfamilies.

  • 44.
    Bunkoczi, Gabor
    et al.
    University of Cambridge, England.
    Wallner, Björn
    Linköping University, Department of Physics, Chemistry and Biology, Bioinformatics. Linköping University, The Institute of Technology.
    Read, Randy J.
    University of Cambridge, England.
    Local Error Estimates Dramatically Improve the Utility of Homology Models for Solving Crystal Structures by Molecular Replacement2015In: Structure, ISSN 0969-2126, E-ISSN 1878-4186, Vol. 23, no 2, p. 397-406Article in journal (Refereed)
    Abstract [en]

    Predicted structures submitted for CASP10 have been evaluated as molecular replacement models against the corresponding sets of structure factor amplitudes. It has been found that the log- likelihood gain score computed for each prediction correlates well with common structure quality indicators but is more sensitive when the accuracy of the models is high. In addition, it was observed that using coordinate error estimates submitted by predictors to weight the model can improve its utility in molecular replacement dramatically, and several groups have been identified who reliably provide accurate error estimates that could be used to extend the application of molecular replacement for low-homology cases.

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  • 45.
    Bzhalava, David
    et al.
    Karolinska Institutet and Karolinska University Hospital, Stockholm.
    Ekström, Johanna
    Lund University, Malmö.
    Lysholm, Fredrik
    Linköping University, Department of Physics, Chemistry and Biology, Bioinformatics. Linköping University, The Institute of Technology.
    Hultin, Emilie
    Karolinska Institutet and Karolinska University Hospital, Stockholm.
    Faust, Helena
    Lund University, Malmö.
    Persson, Bengt
    Linköping University, Department of Physics, Chemistry and Biology, Bioinformatics. Linköping University, The Institute of Technology.
    Lehtinen, Matti
    National Institute for Health and Welfare, Oulu, Finland.
    de Villiers, Ethel-Michele
    Deutsches Krebsforschungszentrum, Heidelberg, Germany.
    Dillner, Joakim
    Karolinska Institutet and Karolinska University Hospital, Stockholm.
    Phylogenetically diverse TT virus viremia among pregnant women2012In: Virology, ISSN 0042-6822, E-ISSN 1096-0341, Vol. 432, no 2, p. 427-434Article in journal (Refereed)
    Abstract [en]

    Infections during pregnancy have been suggested to be involved in childhood leukemias. We used high-throughput sequencing to describe the viruses most readily detectable in serum samples of pregnantwomen. Serum DNA of 112 mothers to leukemic children was amplified using whole genome amplification. Sequencing identified one TTvirus (TTV) isolate belonging to a known type and two putatively new TTVs. For 22 mothers, we also performed TTV amplification by general primer PCR before sequencing. This detected 39 TTVs, two of which were identical to the TTVs found after whole genome amplification.

    Altogether, we found 40 TTV isolates, 29 of which were putatively new types (similarities ranging from 89% to 69%). In conclusion, high throughput sequencing is useful to describe the known or unknown viruses that are present in serum samples of pregnantwomen.

  • 46.
    Bzhalava, Davit
    et al.
    Karolinska Institutet, Stockholm, Sweden.
    Johansson, Hanna
    Lund University, Malmö, Sweden.
    Ekstrom, Johanna
    Karolinska Institutet, Stockholm, Sweden.
    Faust, Helena
    Lund University, Malmö, Sweden.
    Moller, Birgitta
    Karolinska Institutet, Stockholm, Sweden.
    Eklund, Carina
    Karolinska Institutet, Stockholm, Sweden.
    Nordin, Peter
    Läkarhuset, Gothenburg, Sweden.
    Stenquist, Bo
    University of Gothenburg, Sweden.
    Paoli, John
    University of Gothenburg, Sweden.
    Persson, Bengt
    Linköping University, Department of Physics, Chemistry and Biology, Bioinformatics. Linköping University, The Institute of Technology.
    Forslund, Ola
    Lund University, Malmö, Sweden.
    Dillner, Joakim
    Karolinska Institutet, Stockholm, Sweden.
    Unbiased Approach for Virus Detection in Skin Lesions2013In: PLOS ONE, E-ISSN 1932-6203, Vol. 8, no 6Article in journal (Refereed)
    Abstract [en]

    To assess presence of virus DNA in skin lesions, swab samples from 82 squamous cell carcinomas of the skin (SCCs), 60 actinic keratoses (AKs), paraffin-embedded biopsies from 28 SCCs and 72 kerathoacanthomas (KAs) and fresh-frozen biopsies from 92 KAs, 85 SCCs and 92 AKs were analyzed by high throughput sequencing (HTS) using 454 or Ion Torrent technology. We found total of 4,284 viral reads, out of which 4,168 were Human Papillomavirus (HPV)-related, belonging to 15 known (HPV8, HPV12, HPV20, HPV36, HPV38, HPV45, HPV57, HPV59, HPV104, HPV105, HPV107, HPV109, HPV124, HPV138, HPV147), four previously described putative (HPV 915 F 06 007 FD1, FA73, FA101, SE42) and two putatively new HPV types (SE46, SE47). SE42 was cloned, sequenced, designated as HPV155 and found to have 76% similarity to the most closely related known HPV type. In conclusion, an unbiased approach for viral DNA detection in skin tumors has found that, although some new putative HPVs were found, known HPV types constituted most of the viral DNA.

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  • 47.
    Bäck, Marcus
    et al.
    Linköping University, Department of Physics, Chemistry and Biology, Chemistry. Linköping University, Faculty of Science & Engineering.
    Selegård, Robert
    Linköping University, Department of Physics, Chemistry and Biology, Biophysics and bioengineering. Linköping University, Faculty of Science & Engineering.
    Todarwal, Yogesh
    KTH Royal Inst Technol, Sweden.
    Nyström, Sofie
    Linköping University, Department of Physics, Chemistry and Biology, Chemistry. Linköping University, Faculty of Science & Engineering.
    Norman, Patrick
    KTH Royal Inst Technol, Sweden.
    Linares, Mathieu
    Linköping University, Department of Physics, Chemistry and Biology, Bioinformatics. Linköping University, Faculty of Science & Engineering.
    Hammarström, Per
    Linköping University, Department of Physics, Chemistry and Biology, Chemistry. Linköping University, Faculty of Science & Engineering.
    Lindgren, Mikael
    Linköping University, Department of Physics, Chemistry and Biology, Chemistry. Linköping University, Faculty of Science & Engineering. Norwegian Univ Sci & Technol, Norway.
    Nilsson, Peter
    Linköping University, Department of Physics, Chemistry and Biology, Chemistry. Linköping University, Faculty of Science & Engineering.
    Tyrosine Side-Chain Functionalities at Distinct Positions Determine the Chirooptical Properties and Supramolecular Structures of Pentameric Oligothiophenes2020In: ChemistryOpen, ISSN 2191-1363, Vol. 9, no 11, p. 1100-1108Article in journal (Refereed)
    Abstract [en]

    Control over the photophysical properties and molecular organization of pi-conjugated oligothiophenes is essential to their use in organic electronics. Herein we synthesized and characterized a variety of anionic pentameric oligothiophenes with different substitution patterns of L- or D-tyrosine at distinct positions along the thiophene backbone. Spectroscopic, microscopic, and theoretical studies of L- or D-tyrosine substituted pentameric oligothiophene conjugates revealed the formation of optically active pi-stacked self-assembled aggregates under acid conditions. The distinct photophysical characteristics, as well as the supramolecular structures of the assemblies, were highly influenced by the positioning of the L- or D-tyrosine moieties along the thiophene backbone. Overall, the obtained results clearly demonstrate how fundamental changes in the position of the enantiomeric side-chain functionalities greatly affect the optical properties as well as the architecture of the self-assembled supramolecular structures.

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  • 48.
    Caporaletti, Francesca
    et al.
    Linköping University, Department of Physics, Chemistry and Biology, Chemistry. Linköping University, Faculty of Science & Engineering. Large Scale Structure, Institute Laue Langevin, Grenoble, France.
    Pietras, Zuzanna
    Linköping University, Department of Physics, Chemistry and Biology, Chemistry. Linköping University, Faculty of Science & Engineering.
    Morad, Vivian
    Linköping University, Department of Physics, Chemistry and Biology, Chemistry. Linköping University, Faculty of Science & Engineering.
    Mårtensson, Lars-Göran
    Linköping University, Department of Physics, Chemistry and Biology, Chemistry. Linköping University, Faculty of Science & Engineering.
    Gabel, Frank
    University Grenoble Alpes, CEA, CNRS, IBS, Grenoble, France.
    Wallner, Björn
    Linköping University, Department of Physics, Chemistry and Biology, Bioinformatics. Linköping University, Faculty of Science & Engineering.
    Martel, Anne
    Large Scale Structure, Institute Laue Langevin, Grenoble, France.
    Sunnerhagen, Maria
    Linköping University, Department of Physics, Chemistry and Biology, Chemistry. Linköping University, Faculty of Science & Engineering.
    Small-angle X-ray and neutron scattering of MexR and its complex with DNA supports a conformational selection binding model.2023In: Biophysical Journal, ISSN 0006-3495, E-ISSN 1542-0086, Vol. 122, no 2, p. 408-418Article in journal (Refereed)
    Abstract [en]

    In this work, we used Small-angle X-ray and neutron scattering (SAS) to reveal the shape of the protein-DNA complex of the Pseudomonas aeruginosa (P.aeruginosa) transcriptional regulator MexR, a member of the MarR family, when bound to one of its native DNA binding sites. Several MarR-like proteins, including MexR, repress the expression of efflux pump proteins by binding to DNA on regulatory sites overlapping with promoter regions. When expressed, efflux-proteins self-assemble to form multiprotein complexes and actively expel highly toxic compounds out of the host organism. The mutational pressure on efflux-regulating MarR family proteins is high since deficient DNA binding leads to constitutive expression of efflux pumps and thereby supports acquired multidrug resistance. Understanding the functional outcome of such mutations and their effects on DNA binding has been hampered by the scarcity of structural and dynamic characterisation of both free and DNA-bound MarR proteins. Here, we show how combined neutron and X-ray small-angle scattering (SAS) of both states in solution support a conformational selection model that enhances MexR asymmetry in binding to one of its promoter-overlapping DNA binding sites.

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  • 49. Order onlineBuy this publication >>
    Carlsson, Jonas
    Linköping University, Department of Physics, Chemistry and Biology, Bioinformatics. Linköping University, The Institute of Technology.
    Mutational effects on protein structure and function2009Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    In this thesis several important proteins are investigated from a structural perspective. Some of the proteins are disease related while other have important but not completely characterised functions. The techniques used are general as demonstrated by applications on metabolic proteins (CYP21, CYP11B1, IAPP, ADH3), regulatory proteins (p53, GDNF) and a transporter protein (ANTR1).

    When the protein CYP21 (steroid 21-hydroxylase) is deficient it causes CAH (congenital adrenal hyperplasia). For this protein, there are about 60 known mutations with characterised clinical phenotypes. Using manual structural analysis we managed to explain the severity of all but one of the mutations. By observing the properties of these mutations we could perform good predictions on, at the time, not classified mutations.

    For the cancer suppressor protein p53, there are over thousand mutations with known activity. To be able to analyse such a large number of mutations we developed an automated method for evaluation of the mutation effect called PREDMUT. In this method we include twelve different prediction parameters including two energy parameters calculated using an energy minimization procedure. The method manages to differentiate severe mutations from non-severe mutations with 77% accuracy on all possible single base substitutions and with 88% on mutations found in breast cancer patients.

    The automated prediction was further applied to CYP11B1 (steroid 11-beta-hydroxylase), which in a similar way as CYP21 causes CAH when deficient. A generalized method applicable to any kind of globular protein was developed. The method was subsequently evaluated on nine additional proteins for which mutants were known with annotated disease phenotypes. This prediction achieved 84% accuracy on CYP11B1 and 81% accuracy in total on the evaluation proteins while leaving 8% as unclassified. By increasing the number of unclassified mutations the accuracy of the remaining mutations could be increased on the evaluation proteins and substantially increase the classification quality as measured by the Matthews correlation coefficient. Servers with predictions for all possible single based substitutions are provided for p53, CYP21 and CYP11B1.

    The amyloid formation of IAPP (islet amyloid polypeptide) is strongly connected to diabetes and has been studied using both molecular dynamics and Monte Carlo energy minimization. The effects of mutations on the amount and speed of amyloid formation were investigated using three approaches. Applying a consensus of the three methods on a number of interesting mutations, 94% of the mutations could be correctly classified as amyloid forming or not, evaluated with in vitro measurements.

    In the brain there are many proteins whose functions and interactions are largely unknown. GDNF (glial cell line-derived neurotrophic factor) and NCAM (neural cell adhesion molecule) are two such neuron connected proteins that are known to interact. The form of interaction was studied using protein--protein docking where a docking interface was found mediated by four oppositely charged residues in respective protein. This interface was subsequently confirmed by mutagenesis experiments. The NCAM dimer interface upon binding to the GDNF dimer was also mapped as well as an additional interacting protein, GFRα1, which was successfully added to the protein complex without any clashes.

    A large and well studied protein family is the alcohol dehydrogenase family, ADH. A class of this family is ADH3 (alcohol dehydrogenase class III) that has several known substrates and inhibitors. By using virtual screening we tried to characterize new ligands. As some ligands were already known we could incorporate this knowledge when the compound docking simulations were scored and thereby find two new substrates and two new inhibitors which were subsequently successfully tested in vitro.

    ANTR1 (anion transporter 1) is a membrane bound transporter important in the photosynthesis in plants. To be able to study the amino acid residues involved in inorganic phosphate transportation a homology model of the protein was created. Important residues were then mapped onto the structure using conservation analysis and we were in this way able to propose roles of amino acid residues involved in the transportation of inorganic phosphate. Key residues were subsequently mutated in vitro and a transportation process could be postulated.

    To conclude, we have used several molecular modelling techniques to find functional clues, interaction sites and new ligands. Furthermore, we have investigated the effect of muations on the function and structure of a multitude of disease related proteins.

     

    List of papers
    1. Molecular Model of Human CYP21 Based onMammalian CYP2C5: Structural Features Correlatewith Clinical Severity of Mutations CausingCongenital Adrenal Hyperplasia
    Open this publication in new window or tab >>Molecular Model of Human CYP21 Based onMammalian CYP2C5: Structural Features Correlatewith Clinical Severity of Mutations CausingCongenital Adrenal Hyperplasia
    Show others...
    2006 (English)In: Molecular Endocrinology, ISSN 0888-8809, E-ISSN 1944-9917, Vol. 20, no 11, p. 2946-2964Article in journal (Refereed) Published
    Abstract [en]

    Enhanced understanding of structure-function relationshipsof human 21-hydroxylase, CYP21, is requiredto better understand the molecular causesof congenital adrenal hyperplasia. To this end, astructural model of human CYP21 was calculatedbased on the crystal structure of rabbit CYP2C5.All but two known allelic variants of missense type,a total of 60 disease-causing mutations and sixnormal variants, were analyzed using this model. Astructural explanation for the corresponding phenotypewas found for all but two mutants for whichavailable clinical data are also discrepant with invitro enzyme activity. Calculations of protein stabilityof modeled mutants were found to correlateinversely with the corresponding clinical severity.Putative structurally important residues were identifiedto be involved in heme and substrate binding,redox partner interaction, and enzyme catalysisusing docking calculations and analysis of structurallydetermined homologous cytochrome P450s(CYPs). Functional and structural consequences ofseven novel mutations, V139E, C147R, R233G,T295N, L308F, R366C, and M473I, detected inScandinavian patients with suspected congenitaladrenal hyperplasia of different severity, were predictedusing molecular modeling. Structural featuresdeduced from the models are in good correlationwith clinical severity of CYP21 mutants,which shows the applicability of a modeling approachin assessment of new CYP21 mutations.

    Place, publisher, year, edition, pages
    Stanford: The endocrin society, 2006
    Keywords
    Mutations, prediction, CAH, CYP21, homology model
    National Category
    Bioinformatics and Systems Biology
    Identifiers
    urn:nbn:se:liu:diva-21305 (URN)10.1210/me.2006-0172 (DOI)
    Available from: 2009-09-30 Created: 2009-09-30 Last updated: 2017-12-13Bibliographically approved
    2. Investigation and prediction of the severity of p53 mutants using parameters from structural calculations
    Open this publication in new window or tab >>Investigation and prediction of the severity of p53 mutants using parameters from structural calculations
    2009 (English)In: The FEBS Journal, ISSN 1742-464X, E-ISSN 1742-4658, Vol. 276, no 15, p. 4142-4155Article in journal (Refereed) Published
    Abstract [en]

    A method has been developed to predict the effects of mutations in the p53 cancer suppressor gene. The new method uses novel parameters combined with previously established parameters. The most important parameter is the stability measure of the mutated structure calculated using molecular modelling. For each mutant, a severity score is reported, which can be used for classification into deleterious and nondeleterious. Both structural features and sequence properties are taken into account. The method has a prediction accuracy of 77% on all mutants and 88% on breast cancer mutations affecting WAF1 promoter binding. When compared with earlier methods, using the same dataset, our method clearly performs better. As a result of the severity score calculated for every mutant, valuable knowledge can be gained regarding p53, a protein that is believed to be involved in over 50% of all human cancers.

    Keywords
    Cancer; molecular modelling; mutations; p53; structural prediction
    National Category
    Medical and Health Sciences
    Identifiers
    urn:nbn:se:liu:diva-20141 (URN)10.1111/j.1742-4658.2009.07124.x (DOI)
    Available from: 2009-08-31 Created: 2009-08-31 Last updated: 2017-12-13Bibliographically approved
    3. A structural model of human steroid 11-betahydroxylase,CYP11B1, used to predict consequences of mutations
    Open this publication in new window or tab >>A structural model of human steroid 11-betahydroxylase,CYP11B1, used to predict consequences of mutations
    2009 (English)Article in journal (Other academic) Submitted
    Abstract [en]

    A prediction method has been developed to estimate the severity of amino acid residue exchanges in human steroid 11-beta-hydroxylase, CYP11B1, due to mutations in the corresponding gene. The prediction is based both on structural and on sequence dependent parameters. The method uses two approaches; one with general molecular property weights and one with a consensus voting strategy based upon distribution of molecular properties, which does not require any training. Both methods are tested on known mutations in CYP11B1 and result in 85% prediction accuracy. The consensus voting method is then further evaluated on 9 proteins with an average of 81% prediction accuracy. A server utilizing the results from the consensus voting on CYP11B1 is provided where the user can extract information about new mutants. A similar server is also provided for mutants in human steroid 21-hydroxylase (CYP21).

    Keywords
    CYP11B1, steroid 11-beta-hydroxylase, molecular modeling, structural prediction, mutations
    National Category
    Natural Sciences
    Identifiers
    urn:nbn:se:liu:diva-51118 (URN)
    Available from: 2009-10-19 Created: 2009-10-19 Last updated: 2009-10-19Bibliographically approved
    4. Disruption of the GDNF Binding Site in NCAM DissociatesLigand Binding and Homophilic Cell Adhesion
    Open this publication in new window or tab >>Disruption of the GDNF Binding Site in NCAM DissociatesLigand Binding and Homophilic Cell Adhesion
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    2007 (English)In: Journal of Biological Chemistry, ISSN 0021-9258, E-ISSN 1083-351X, Vol. 282, no 17, p. 12734-12740Article in journal (Refereed) Published
    Abstract [en]

    Most plasma membrane proteins are capable of sensing multiple cell-cell and cell-ligand interactions, but the extent towhich this functional versatility is founded on their modular design is less clear. We have identified the third immunoglobulin domain of the Neural Cell Adhesion Molecule (NCAM) as the necessary and sufficient determinant for its interaction with Glial Cell Line-derived Neurotrophic Factor (GDNF). Four charged contacts were identified by molecular modeling as the main contributors to binding energy. Their mutation abolished GDNF binding to NCAM but left intact the ability of NCAM tomediate cell adhesion, indicating that the two functions are genetically separable. The GDNF-NCAM interface allows complex formation with the GDNF family receptor α1, shedding light on the molecular architecture of a multicomponent GDNF receptor.

    Place, publisher, year, edition, pages
    Bethesda, MD: American Society for Biochemistry and Molecular Biology, 2007
    Keywords
    homology model, protein complex, interaction interface, mutagenesis
    National Category
    Bioinformatics and Systems Biology
    Identifiers
    urn:nbn:se:liu:diva-21306 (URN)10.1074/jbc.M701588200 (DOI)
    Available from: 2009-09-30 Created: 2009-09-30 Last updated: 2017-12-13Bibliographically approved
    5. Functionally Important Amino Acids in the Arabidopsis Thylakoid Phosphate Transporter: Homology Modeling and Site-directed Mutagenesis
    Open this publication in new window or tab >>Functionally Important Amino Acids in the Arabidopsis Thylakoid Phosphate Transporter: Homology Modeling and Site-directed Mutagenesis
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    2010 (English)In: Biochemistry, ISSN 0006-2960, E-ISSN 1520-4995, Vol. 49, no 30, p. 6430-6439Article in journal (Other academic) Published
    Abstract [en]

    The anion transporter 1 (ANTR1) from Arabidopsis thaliana, homologous to the mammalian SLC17 family, has recently been localized to the chloroplast thylakoid membrane. When expressed heterologously in Escherichia coli, ANTR1 mediates a Na+-dependent active transport of inorganic phosphate (Pi). The aim of this study was to identify amino acids involved in substrate binding/translocation by ANTR1 and in the Na+-dependence of its activity. A threedimensional structural model of ANTR1 was constructed using the crystal structure of glycerol-3-phosphate/phosphate antiporter (GlpT) from E.coli as a template. Based on this model and multiple sequence alignments, five highly conserved residues in plant ANTRs and mammalian SLC17 homologues have been selected for site-directed mutagenesis, namely Arg-120, Ser-124 and Arg-201 inside the putative translocation pathway, Arg-228 and Asp-382 exposed at the cytosolic surface of the protein. The activities of the wild type and mutant proteins have been analyzed using expression in E. coli and radioactive transport assays, and compared with bacterial cells carrying an empty plasmid. Based on Pi- and Na+-dependent kinetics, we propose that Arg-120, Arg-201 and Arg-228 are involved in binding and translocation of the substrate, Ser-124 functions as a periplasmic gate for Na+ ions, and finally Asp-382 participates in the turnover of the transporter via ionic interaction with either Arg-228 or Na+ ions. We also propose that the corresponding residues may have a similar function in other plant and mammalian SLC17 homologous transporters.

    National Category
    Medical and Health Sciences
    Identifiers
    urn:nbn:se:liu:diva-51119 (URN)10.1021/bi100239j (DOI)
    Note
    On the day of the defence day the status of this article was ManuscriptAvailable from: 2009-10-19 Created: 2009-10-19 Last updated: 2017-12-12Bibliographically approved
    6. A folding study on IAPP (Islet Amyloid Polypeptide) using molecular dynamics simulations
    Open this publication in new window or tab >>A folding study on IAPP (Islet Amyloid Polypeptide) using molecular dynamics simulations
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    (English)Manuscript (preprint) (Other academic)
    Abstract [en]

    Amyloidosis is the largest group among the protein misfolding diseases, and includes well known diseases such as Alzheimer’s disease and type 2 diabetes. In the latter, islet amyloid is present in the pancreas in almost all individuals. Today, more than 25 different proteins have been isolated from amyloid deposits in human. Even though these proteins differ in size, charge and sequence they all have the capacity to assemble in to fibrillar structures with inseparable morphological appearance. Therefore, it can be assumed that the fibril process is based upon principles that are general for all proteins and knowledge derived from one protein can be used for other amyloid proteins. In this paper, we study the process of amyloid formation in parts of islet amyloid polypeptide (residues 18-29 and 11-37) by analyzing mutations using three different in silico methods. Finally, we use the methods to predict the amyloidogenic properties of the native IAPP and 16 variants thereof and compare the result with in vitro measurements. Using a consensus prediction of the three methods we managed to correctly classify all but two peptides. We have also given further evidence to the importance of S28P for inhibiting amyloid fibre formation, found evidence for antiparallel stacking, and identified important regions for beta sheet stability.

    Keywords
    IAPP, molecular modeling, amyloid, prediction, molecular dynamics, Monte Carlo
    National Category
    Natural Sciences
    Identifiers
    urn:nbn:se:liu:diva-51120 (URN)
    Available from: 2009-10-19 Created: 2009-10-19 Last updated: 2010-01-14Bibliographically approved
    7. Virtual screening for ligands to human alcohol dehydrogenase 3
    Open this publication in new window or tab >>Virtual screening for ligands to human alcohol dehydrogenase 3
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    (English)Manuscript (preprint) (Other academic)
    Abstract [en]

    Alcohol dehydrogenase 3 (ADH3) has been suggested a role in nitric oxide homeostasis due to its function as a S-nitrosoglutathione (GSNO) reductase. This has requested a modulator of the ADH3 activity for control of GSNO levels. Today virtual screenings are frequently used in drug discovery to dock and rank a large number of compounds. With molecular dockings of more than 40,000 compounds into the active site pocket of human ADH3 we ranked compounds with a novel method. Six top ranked compounds that were not known to interact with ADH3 were tested in vitro, where two showed substrate activity (9-decen-1-ol and dodecyltetraglycol), two showed inhibition capacity (deoxycholic acid and doxorubicin) and two did not have any detectable effect. For the substrates, site specific interactions and calculated binding scoring energies were determined with an extended docking simulation including flexible side chains of amino acids residues. The binding scoring energies correlated well with the logarithm of the substrates kcat over Km values. Furthermore, with these computational and experimental data three different lines for specific inhibitors for ADH3 are suggested: fatty acids, glutathione analogs and in addition deoxycholic acids.

    Keywords
    Alcohol dehydrogenase, Enzyme kinetics, Molecular docking, Virtual screening
    National Category
    Natural Sciences
    Identifiers
    urn:nbn:se:liu:diva-51121 (URN)
    Available from: 2009-10-19 Created: 2009-10-19 Last updated: 2010-01-14Bibliographically approved
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    Mutational effects on protein structure and function
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    Cover
  • 50.
    Carlsson, Jonas
    et al.
    Linköping University, Department of Physics, Chemistry and Biology, Bioinformatics. Linköping University, The Institute of Technology.
    Persson, Bengt
    Linköping University, Department of Physics, Chemistry and Biology, Bioinformatics. Linköping University, The Institute of Technology.
    Investigating protein variants using structural calculation techniques2012In: Homology Modeling: Methods and Protocols / [ed] Andrew J. W. Orry and Ruben Abagyan, Springer, 2012, Vol. 857, p. 313-330Chapter in book (Other academic)
    Abstract [en]

    Knowledge about protein tertiary structure can guide experiments, assist in the understanding of structure-function relationships, and aid the design of new therapeutics for disease. Homology modeling is an in silico method that predicts the tertiary structure of an amino acid sequence based on a homologous experimentally determined structure. In, Homology Modeling: Methods and Protocols experts in the field describe each homology modeling step from first principles, provide case studies for challenging modeling targets and describe methods for the prediction of how other molecules such as drugs can interact with the protein. Written in the highly successful Methods in Molecular Biology series format, the chapters include the kind of detailed description and implementation advice that is crucial for getting optimal results in the laboratory. Thorough and intuitive, Homology Modeling: Methods and Protocols guides scientists in the available homology modeling methods.

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