The CAPRI experiment (Critical Assessment of Predicted Interactions) simulates realistic and diverse docking challenges, each case having specific properties that may be exploited by docking algorithms. Motivated by the different CAPRI challenges, we developed and implemented a comprehensive suite of docking algorithms. These were incorporated into a dynamic docking protocol, consisting of four main stages: (1) Biological and bioinformatics research aiming to predict the binding site residues, to define distance constraints between interface atoms and to analyze the flexibility of molecules; (2) Rigid or flexible docking, performed by the PatchDock or FlexDock method, which utilizes the information gathered in the previous step. Symmetric complexes are predicted by the SymmDock method; (3) Flexible refinement and reranking of the rigid docking solution candidates, performed by FiberDock; and finally, (4) clustering and filtering the results based on energy funnels. We analyzed the performance of our docking protocol on a large benchmark and on recent CAPRI targets. The analysis has demonstrated the importance of biological information gathering prior to docking, which significantly increased the docking success rate, and of the refinement and rescoring stage that significantly improved the ranking of the rigid docking solutions. Our failures were mostly a result of mishandling backbone flexibility, inaccurate homology modeling, or incorrect biological assumptions. Most of the methods are available at http://bioinfo3d.cs.tau.ac.il/.
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