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An overview of data-driven HADDOCK strategies in CAPRI rounds 38-45
Authors:Panagiotis I Koukos  Jorge Roel-Touris  Francesco Ambrosetti  Cunliang Geng  Jörg Schaarschmidt  Mikael E Trellet  Adrien S J Melquiond  Li C Xue  Rodrigo V Honorato  Irina Moreira  Zeynep Kurkcuoglu  Anna Vangone  Alexandre M J J Bonvin
Institution:1. Faculty of Science, Department of Chemistry, Bijvoet Center for Biomolecular Research, Computational Structural Biology Group, Utrecht University, Utrecht, The Netherlands;2. Faculty of Science, Department of Chemistry, Bijvoet Center for Biomolecular Research, Computational Structural Biology Group, Utrecht University, Utrecht, The Netherlands

Department of Physics, Sapienza University, Rome, Italy;3. Faculty of Science, Department of Chemistry, Bijvoet Center for Biomolecular Research, Computational Structural Biology Group, Utrecht University, Utrecht, The Netherlands

Multiscale Materials Modelling and Virtual Design, Institute of Nanotechnology, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany;4. Faculty of Science, Department of Chemistry, Bijvoet Center for Biomolecular Research, Computational Structural Biology Group, Utrecht University, Utrecht, The Netherlands

CNC—Center for Neuroscience and Cell Biology, Rua Larga, FMUC, Polo I, 1° andar, Universidade de Coimbra, Coimbra, Portugal

Abstract:Our information-driven docking approach HADDOCK has demonstrated a sustained performance since the start of its participation to CAPRI. This is due, in part, to its ability to integrate data into the modeling process, and to the robustness of its scoring function. We participated in CAPRI both as server and manual predictors. In CAPRI rounds 38-45, we have used various strategies depending on the available information. These ranged from imposing restraints to a few residues identified from literature as being important for the interaction, to binding pockets identified from homologous complexes or template-based refinement/CA-CA restraint-guided docking from identified templates. When relevant, symmetry restraints were used to limit the conformational sampling. We also tested for a large decamer target a new implementation of the MARTINI coarse-grained force field in HADDOCK. Overall, we obtained acceptable or better predictions for 13 and 11 server and manual submissions, respectively, out of the 22 interfaces. Our server performance (acceptable or higher-quality models when considering the top 10) was better (59%) than the manual (50%) one, in which we typically experiment with various combinations of protocols and data sources. Again, our simple scoring function based on a linear combination of intermolecular van der Waals and electrostatic energies and an empirical desolvation term demonstrated a good performance in the scoring experiment with a 63% success rate across all 22 interfaces. An analysis of model quality indicates that, while we are consistently performing well in generating acceptable models, there is room for improvement for generating/identifying higher quality models.
Keywords:biomolecular interactions  complexes  integrative modeling  prediction  scoring
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