Journal
PROTEINS-STRUCTURE FUNCTION AND BIOINFORMATICS
Volume 72, Issue 1, Pages 344-352Publisher
WILEY
DOI: 10.1002/prot.21930
Keywords
docking; protein recognition; structure prediction; structural bioinformatics
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Funding
- NIGMS NIH HHS [R01 GM074255] Funding Source: Medline
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Revealing the fundamental principles of protein interactions is essential for the basic knowledge of molecular processes and designing better predictive tools. Protein docking procedures allow systematic sampling of intermolecular energy landscapes, revealing the distribution of energy basins and their characteristics. A systematic search docking procedure GRAMM-X was applied to a comprehensive nonredundant database of nonobligate protein-protein complexes to determine the size of the intermolecular energy funnel. The unbound structures were simulated using rotamer library. The procedure generated grid-based matches, based on a smoothed Lennard-Jones potential, and minimized them off the grid with the same potential. The minimization generated a distribution of distances, based on a variety of metrics, between the grid-based and the minimized matches. The metric selected for the analysis, ligand interface RMSD, provided three independent estimates of the funnel size: based on the distribution amplitude for the near-native matches, deviation from random, and correlation with the energy values. The three methods converge to similar estimates of similar to 6-8 angstrom ligand interface RMSD. The results indicated dependence of the funnel size on the type of the complex (smaller wfor antigen-antibody, medium for enzyme-inhibitor, and larger for the rest of the complexes) and the funnel size correlation with the size of the interface. Guidelines for the optimal sampling of docking coordinates, based on the funnel size estimates, were explored.
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