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Tracking Internal Frames of Reference for Consistent Molecular Distribution Functions
Linköping University, Department of Science and Technology, Media and Information Technology. Linköping University, Faculty of Science & Engineering. Swedish e-Science Research Centre (SeRC), Stockholm, Sweden. (Scientific Visualization Group)
Linköping University, Department of Science and Technology, Media and Information Technology. Linköping University, Faculty of Science & Engineering. Swedish e-Science Research Centre (SeRC), Stockholm, Sweden. (Scientific Visualization Group)ORCID iD: 0000-0003-1511-5006
Linköping University, Department of Science and Technology, Laboratory of Organic Electronics. Linköping University, Faculty of Science & Engineering. Swedish e-Science Research Centre (SeRC), Stockholm, Sweden. (Scientific Visualization Group)
Linköping University, Department of Science and Technology, Media and Information Technology. Linköping University, Faculty of Science & Engineering. Swedish e-Science Research Centre (SeRC), Stockholm, Sweden. (Scientific Visualization Group)ORCID iD: 0000-0002-9466-9826
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2022 (English)In: IEEE Transactions on Visualization and Computer Graphics, ISSN 1077-2626, E-ISSN 1941-0506, Vol. 28, no 9, p. 3126-3137Article in journal (Refereed) Published
Abstract [en]

In molecular analysis, Spatial Distribution Functions (SDF) are fundamental instruments in answering questions related to spatial occurrences and relations of atomic structures over time. Given a molecular trajectory, SDFs can, for example, reveal the occurrence of water in relation to particular structures and hence provide clues of hydrophobic and hydrophilic regions. For the computation of meaningful distribution functions, the definition of molecular reference structures is essential. Therefore we introduce the concept of an internal frame of reference (IFR) for labeled point sets that represent selected molecular structures, and we propose an algorithm for tracking the IFR over time and space using a variant of Kabschs algorithm. This approach lets us generate a consistent space for the aggregation of the SDF for molecular trajectories and molecular ensembles. We demonstrate the usefulness of the technique by applying it to temporal molecular trajectories as well as ensemble datasets. The examples include different docking scenarios with DNA, insulin, and aspirin.

Place, publisher, year, edition, pages
IEEE COMPUTER SOC , 2022. Vol. 28, no 9, p. 3126-3137
Keywords [en]
Distribution functions, Trajectory, Visualization, Graphical models, Numerical models, Shape, Periodic structures
National Category
Chemical Sciences Mathematics Computer and Information Sciences
Identifiers
URN: urn:nbn:se:liu:diva-174336DOI: 10.1109/TVCG.2021.3051632ISI: 000833767700005PubMedID: 33444141OAI: oai:DiVA.org:liu-174336DiVA, id: diva2:1538629
Note

Funding agencies: Excellence Center at Linkoping and Lund in Information Technology (ELLIIT); Swedish e-Science Research Centre (SeRC)

Available from: 2021-03-20 Created: 2021-03-20 Last updated: 2023-01-13

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Skånberg, RobinFalk, MartinLinares, MathieuYnnerman, AndersHotz, Ingrid

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