RDOCK: Refinement of Rigid-body Protein Docking Predictions

Bioinformatics Program, Boston University, Boston, Massachusetts 02215, USA.
Proteins Structure Function and Bioinformatics (Impact Factor: 2.63). 11/2003; 53(3):693-707. DOI: 10.1002/prot.10460
Source: PubMed


We present a simple and effective algorithm RDOCK for refining unbound predictions generated by a rigid-body docking algorithm ZDOCK, which has been developed earlier by our group. The main component of RDOCK is a three-stage energy minimization scheme, followed by the evaluation of electrostatic and desolvation energies. Ionic side chains are kept neutral in the first two stages of minimization, and reverted to their full charge states in the last stage of brief minimization. Without side chain conformational search or filtering/clustering of resulting structures, RDOCK represents the simplest approach toward refining unbound docking predictions. Despite its simplicity, RDOCK makes substantial improvement upon the top predictions by ZDOCK with all three scoring functions and the improvement is observed across all three categories of test cases in a large benchmark of 49 non-redundant unbound test cases. RDOCK makes the most powerful combination with ZDOCK2.1, which uses pairwise shape complementarity as the scoring function. Collectively, they rank a near-native structure as the number-one prediction for 18 test cases (37% of the benchmark), and within the top 4 predictions for 24 test cases (49% of the benchmark). To various degrees, funnel-like energy landscapes are observed for these 24 test cases. To the best of our knowledge, this is the first report of binding funnels starting from global searches for a broad range of test cases. These results are particularly exciting, given that we have not used any biological information that is specific to individual test cases and the whole process is entirely automated. Among three categories of test cases, the best results are seen for enzyme/inhibitor, with a near-native structure ranked as the number-one prediction for 48% test cases, and within the top 10 predictions for 78% test cases. RDOCK is freely available to academic users at approximately rong/dock.

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    • "Poses with the highest Z-scores were compared to the solved crystal structure of human cathepsin L interacting with human stefin A (PDB 3KSE) to validate the relative binding position and orientation of the two proteins in the predicted complex. Five complexes were chosen and refined through energy minimization using the R-Dock algorithm (Li et al., 2003). The top ranking model was selected for complex visualization and inference of protease and cystatin interacting residues at the binding interface (Sainsbury et al., 2012a). "
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    ABSTRACT: Positive selection is thought to contribute to the functional diversification of insect-inducible protease inhibitors in plants in response to selective pressures exerted by the digestive proteases of their herbivorous enemies. Here we assessed whether a reciprocal evolutionary process takes place on the insect side, and whether ingestion of a positively selected plant inhibitor may translate into a measurable rebalancing of midgut proteases in vivo. Midgut Cys proteases of herbivorous Coleoptera, including the major pest Colorado potato beetle (Leptinotarsa decemlineata), were first compared using a codon-based evolutionary model to look for the occurrence of hypervariable, positively selected amino acid sites among the tested sequences. Hypervariable sites were found, distributed within -or close to- amino acid regions interacting with Cys-type inhibitors of the plant cystatin protein family. A close examination of L. decemlineata sequences indicated a link between their assignment to protease functional families and amino acid identity at positively selected sites. A function-diversifying role for positive selection was further suggested empirically by in vitro protease assays and a shotgun proteomic analysis of L. decemlineata Cys proteases showing a differential rebalancing of protease functional family complements in larvae fed single variants of a model cystatin mutated at positively selected amino acid sites. These data confirm overall the occurrence of hypervariable, positively selected amino acid sites in herbivorous Coleoptera digestive Cys proteases. They also support the idea of an adaptive role for positive selection, useful to generate functionally diverse proteases in insect herbivores ingesting functionally diverse, rapidly evolving dietary cystatins. Copyright © 2015. Published by Elsevier Ltd.
    Insect biochemistry and molecular biology 08/2015; 65. DOI:10.1016/j.ibmb.2015.07.017 · 3.45 Impact Factor
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    • "Since docking software produce 100’s to 1000’s of putative models, their exploitation requires the ability to score them accurately [62-64]. Intuitively, physical-based scoring functions are particularly attractive since they can be applied to any model by exploiting physiochemical features of the atoms. "
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    BMC Bioinformatics 06/2014; 15(1):171. DOI:10.1186/1471-2105-15-171 · 2.58 Impact Factor
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    • "Moreover, it uses the contact propensities of transient complexes of proteins to perform an evaluation of a pairwise atomic statistical potential for the docking molecular system. RDOCK was utilized to refine and quickly evaluate the results obtained by ZDOCK (Li et al., 2003). RDOCK performs a fast minimization step to the ZDOCK molecular complex outputs and ranks them according to their re-calculated binding free energies. "
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    Journal of Molecular Recognition 01/2014; 27(1):19-31. DOI:10.1002/jmr.2327 · 2.15 Impact Factor
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