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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    Insect biochemistry and molecular biology 08/2015; 65. DOI:10.1016/j.ibmb.2015.07.017 · 3.45 Impact Factor
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    • "The charges and atom types were assigned using the CHARMm force field [26]. IL-34 and M-CSF binding were assessed using the ZDOCK [27] [28] protein–protein docking software. The best 2000 poses were re-scored using ZRANK, a scoring function with detailed and weighted electrostatics, van der Waals and desolvation terms [29], and then clustered with an RMSD cutoff of 1 nm. "
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    ABSTRACT: Interleukin-34 (IL-34) is a newly-discovered homodimeric cytokine that regulates, like Macrophage Colony-Stimulating Factor (M-CSF), the differentiation of the myeloid lineage through M-CSF receptor (M-CSFR) signaling pathways. To date, both cytokines have been considered as competitive cytokines with regard to the M-CSFR. The aim of the present work was to study the functional relationships of these cytokines on cells expressing the M-CSFR. We demonstrate that simultaneous addition of M-CSF and IL-34 led to a specific activation pattern on the M-CSFR, with higher phosphorylation of the tyrosine residues at low concentrations. Similarly, both cytokines showed an additive effect on cellular proliferation or viability. In addition, BIAcore experiments demonstrated that M-CSF binds to IL-34, and molecular docking studies predicted the formation of a heteromeric M-CSF/IL-34 cytokine. A proximity ligation assay confirmed this interaction between the cytokines. Finally, co-expression of the M-CSFR and its ligands differentially regulated M-CSFR trafficking into the cell. This study establishes a new foundation for the understanding of the functional relationship between IL-34 and M-CSF, and gives a new vision for the development of therapeutic approaches targeting the IL-34/M-CSF/M-CSFR axis. Copyright © 2015 Elsevier Ltd. All rights reserved.
    Cytokine 06/2015; 76(2). DOI:10.1016/j.cyto.2015.05.029 · 2.66 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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