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.
Highlights
In recent years, molecular simulation techniques have been gaining traction as alternative methods for the elucidation of structural details underpinning cellular mechanisms.[1]
Note: The first column is the target and interface number as reported by CAPRI and the fourth through sixth columns refer to the number of high(***)/medium-(**)/acceptable-(*)quality models generated during the server, manual and scoring experiments, respectively, when considering the top 10 models submitted for evaluation
HADDOCK was able to generate near-native models for these systems as well as most of the traditional protein-protein systems that featured in the remaining targets, including the peptide ones
Summary
Molecular simulation techniques have been gaining traction as alternative methods for the elucidation of structural details underpinning cellular mechanisms.[1]. For protein-protein complexes, and to a lesser extent protein-peptide ones, the performance of various docking codes has been continuously evaluated over a period spanning almost 20 years in the worldwide CAPRI experiment.[7,8,9,10,11,12,13] We participated in all three experiments (server, manual, and scoring) for all targets of rounds 38-45 with HADDOCK—our data-driven integrative modeling platform.[14,15] HADDOCK (High Ambiguity Driven DOCKing) makes use of biochemical/biophysical experimental information which is translated into distance restraints that drive the docking toward conformations that satisfy the experimentally available data This cuts down on the need to exhaustively sample the conformational space and instead allows focusing on flexibly refining a subset of the models generated. Data-driven approaches have, downsides as well, most prominently the fact that if the information that is provided to HADDOCK is incorrect, it will likely not sample the region of the conformational landscape close to the native state
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