RDOCK: Refinement of Rigid-body Protein Docking Predictions

Bioinformatics Program, Boston University, Boston, Massachusetts 02215, USA.
Proteins Structure Function and Bioinformatics (Impact Factor: 2.92). 11/2003; 53(3):693-707. DOI: 10.1002/prot.10460
Source: PubMed

ABSTRACT 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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    • "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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    ABSTRACT: The human anti-human immunodeficiency virus (HIV) antibody 2G12 (mAb 2G12) is one of the most broadly neutralizing antibodies against HIV that recognizes a unique epitope on the surface glycoprotein gp120. In the present work, a limited affinity-ligand library was synthesized and evaluated for its ability to bind and purify recombinant mAb 2G12 expressed in transgenic corn. The affinity ligands were structural fragments of polysulfonate triazine dye Cibacron Blue 3GA (CB3GA) and represent novel lead scaffolds for designing synthetic affinity ligands. Solid phase chemistry was used to synthesize variants of CB3GA lead ligand. One immobilized ligand, bearing 4-aminobenzyl sulfonic acid (4ABS) linked on two chlorine atoms of the triazine ring (4ABS-Trz-4ABS), displayed high affinity for mAb 2G12. Absorption equilibrium, 3D molecular modelling and molecular dynamics simulation studies were carried out to provide a detailed picture of the 4ABS-Trz-4ABS interaction with mAb 2G12. This biomimetic affinity ligand was exploited for the development of a facile two-step purification protocol for mAb 2G12. In the first step of the procedure, mAb 2G12 was purified on an S-Sepharose FF cation exchanger, and in the second step, mAb 2G12 was purified using affinity chromatography on 4ABS-Trz-4ABS affinity adsorbent. Analysis of the antibody preparation by sodium dodecyl sulfate-polyacrylamide gel electrophoresis and enzyme-linked immunosorbent assay showed that the mAb 2G12 was fully active and of sufficient purity suitable for analytical applications. Copyright © 2013 John Wiley & Sons, Ltd.
    Journal of Molecular Recognition 01/2014; 27(1):19-31. DOI:10.1002/jmr.2327 · 2.34 Impact Factor
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    • "However, specialized methodologies are required to estimate accurately the structural and thermodynamic properties of the surface-bound water molecules (Li and Lazaridis 2003, 2005; Di Lella et al. 2007; Gauto et al. 2009). One of the most potent methods for achieving this task is based on the inhomogeneous fluid solvation theory (IFST) as developed by Li and Lazaridis (Li and Lazaridis 2003, 2005). Using this methodology, we were recently able to show that solvent structure and dynamics at protein surfaces involved in carbohydrate-binding proteins are very different from those of the bulk solvent, allowing the identification of the so-called WS or hydration sites. "
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    ABSTRACT: Recognition and complex formation between protein and carbohydrates is a key issue for many important biological processes. Determination of the three-dimensional structure of such complexes is thus most relevant, but particularly challenging due to their usually low binding affinity. In-silico docking methods have a long standing tradition in predicting protein-ligand complexes, and allow the potentially fast exploration of a number of possible protein-carbohydrate complex structures. However, determining which of these predicted complexes represents the correct structure is not always straightforward.In this work, we present a modification of the scoring function provided by Autodock4, a widely used docking software, based on the analysis of the solvent structure adjacent to the protein surface, as derived from Molecular Dynamics simulations, that allows the definition and characterization of regions with higher water occupancy than the bulk solvent, called Water Sites. They mimic the interaction held between the carbohydrate -OH groups and the protein. We used this information for an improved docking method in relation to its capacity to correctly predict the protein-carbohydrate complexes for a number of tested proteins, whose ligands range from the mono- to the tetrasaccharide size. Our results show that the presented method significantly improves the docking predictions. The resulting solvent-structure-biased docking protocol therefore appears as a powerful tool for the design and optimization of glycomimetic drugs development, while providing a new insight for the basic understanding of protein carbohydrate interactions. Moreover, the achieved improvement also underscores the relevance of the solvent structure for the protein carbohydrate recognition process.
    Glycobiology 10/2012; DOI:10.1093/glycob/cws147 · 3.14 Impact Factor
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    • "This reduces the problem to a six-dimensional (6D) rotational-translational search space. Thus, most docking algorithms now use a two-step procedure, in which ab initio techniques are used to generate an initial list of putative complexes which are then rescored using available biophysical information or knowledge-based potentials derived from analyses of existing protein-protein interfaces [8] [9] [10]. Nonetheless, it can take several hours or even days to complete a docking calculation [7]. "
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    Studies in health technology and informatics 01/2010; 159:146-55.
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