liu.seSearch for publications in DiVA
Change search
ReferencesLink to record
Permanent link

Direct link
DockQ: A Quality Measure for Protein-Protein Docking Models
Linköping University, Department of Physics, Chemistry and Biology, Bioinformatics. Linköping University, Faculty of Science & Engineering.
Linköping University, Department of Physics, Chemistry and Biology, Bioinformatics. Linköping University, Faculty of Science & Engineering.ORCID iD: 0000-0002-3772-8279
2016 (English)In: PLoS ONE, ISSN 1932-6203, E-ISSN 1932-6203, Vol. 11, no 8, e0161879- p.Article in journal (Refereed) Published
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.

Place, publisher, year, edition, pages
PUBLIC LIBRARY SCIENCE , 2016. Vol. 11, no 8, e0161879- p.
National Category
Bioinformatics (Computational Biology)
Identifiers
URN: urn:nbn:se:liu:diva-132489DOI: 10.1371/journal.pone.0161879ISI: 000382258600111PubMedID: 27560519OAI: oai:DiVA.org:liu-132489DiVA: diva2:1046258
Note

Funding Agencies|Swedish Research Council [621-2012-5270]; Swedish e-Science Research Center

Available from: 2016-11-13 Created: 2016-11-12 Last updated: 2016-12-02

Open Access in DiVA

fulltext(1021 kB)5 downloads
File information
File name FULLTEXT01.pdfFile size 1021 kBChecksum SHA-512
d467b174c80788b6e0900b170c88a5b630f522dbfadda8f8e3b39c880c708f51c0bb90a39952445fe9b7bf578489ff11a59362c7d204277c20ad9245dc0dc879
Type fulltextMimetype application/pdf

Other links

Publisher's full textPubMed

Search in DiVA

By author/editor
Basu, Sankar ChandraWallner, Björn
By organisation
BioinformaticsFaculty of Science & Engineering
In the same journal
PLoS ONE
Bioinformatics (Computational Biology)

Search outside of DiVA

GoogleGoogle Scholar
Total: 5 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

Altmetric score

Total: 28 hits
ReferencesLink to record
Permanent link

Direct link