Docking and scoring protein interactions: CAPRI 2009
Abstract
Protein docking algorithms are assessed by evaluating blind predictions performed during 2007–2009 in Rounds 13–19 of the community‐wide experiment on critical assessment of predicted interactions (CAPRI). We evaluated the ability of these algorithms to sample docking poses and to single out specific association modes in 14 targets, representing 11 distinct protein complexes. These complexes play important biological roles in RNA maturation, G‐protein signal processing, and enzyme inhibition and function. One target involved protein–RNA interactions not previously considered in CAPRI, several others were hetero‐oligomers, or featured multiple interfaces between the same protein pair. For most targets, predictions started from the experimentally determined structures of the free (unbound) components, or from models built from known structures of related or similar proteins. To succeed they therefore needed to account for conformational changes and model inaccuracies. In total, 64 groups and 12 web‐servers submitted docking predictions of which 4420 were evaluated. Overall our assessment reveals that 67% of the groups, more than ever before, produced acceptable models or better for at least one target, with many groups submitting multiple high‐ and medium‐accuracy models for two to six targets. Forty‐one groups including four web‐servers participated in the scoring experiment with 1296 evaluated models. Scoring predictions also show signs of progress evidenced from the large proportion of correct models submitted. But singling out the best models remains a challenge, which also adversely affects the ability to correctly rank docking models. With the increased interest in translating abstract protein interaction networks into realistic models of protein assemblies, the growing CAPRI community is actively developing more efficient and reliable docking and scoring methods for everyone to use. Proteins 2010. © 2010 Wiley‐Liss, Inc.
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The atom-atom contact energy AACE is used to score and rank all poses, as this has been shown to provide better results than shape-complementarity alone.
“The atom-atom contact energy AACE18 is used to score and rank all poses, as this has been shown to provide better results than shape-complementarity alone54.”
From Improved prediction of protein-protein interactions using AlphaFold2 (2021) · cites this paper as [54]
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- Authors
- Lensink, M. F., & Wodak, S. J.
- Affiliations
- Université Libre de Bruxelles (BE)
- University of Toronto (CA)
- Corresponding author
- Wodak, Shoshana J.
- Venue
- Proteins: Structure, Function, and Bioinformatics
- Publisher
- Wiley
- Published
- 2010-07-14
- Volume
- 78
- Issue
- 15
- Pages
- 3073-3084
- ISSN
- 0887-3585 (ISSN-L)
- 1097-0134
- OpenAlex
- W2027403155
- Cited by
- 226
- References
- 44
- Citations by year
- 2026: 4 · 2025: 6 · 2024: 5 · 2023: 3 · 2022: 8 · 2021: 6 · 2020: 11 · 2019: 20 · 2018: 8 · 2017: 14 · 2016: 22 · 2015: 14 · 2014: 19 · 2013: 30 · 2012: 28
- FWCI
- 11.18
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Proteins Structure Function and Bioinformatics (publishedVersion)
- PubMed (publishedVersion)
- Dépôt institutionnel de l'Université libre de Bruxelles (Université Libre de Bruxelles) (submittedVersion)
- Funders
- Canada Institute of Health Research, Sickkids Foundation
- Ontario Research Fund
- PrioNet Network of Excellence, Canada
- Région Wallonne of Belgium (DGTRE 515993)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
- Physical Sciences › Materials Science › Materials Chemistry › Enzyme Structure and Function
- Physical Sciences › Computer Science › Computational Theory and Mathematics › Computational Drug Discovery Methods
- Keywords
- protein docking, protein-protein interaction, Capri, docking scoring, protein complexes, RNA-protein interactions, conformational change, model accuracy, protein assembly
- MeSH terms
- Algorithms, Bacterial Proteins, Models, Molecular, Protein Binding, Proteins, Software, Computational Biology, Internet, Protein Interaction Mapping, Saccharomyces cerevisiae Proteins, Databases, Protein, Protein Interaction Domains and Motifs
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