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Biologically enhanced sampling geometric docking and backbone flexibility treatment with multiconformational superposition
Author(s) -
Ma Xiao Hui,
Li Chun Hua,
Shen Long Zhu,
Gong Xin Qi,
Chen Wei Zu,
Wang Cun Xin
Publication year - 2005
Publication title -
proteins: structure, function, and bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.699
H-Index - 191
eISSN - 1097-0134
pISSN - 0887-3585
DOI - 10.1002/prot.20577
Subject(s) - docking (animal) , superposition principle , grid , biological system , algorithm , computer science , chemistry , geometry , mathematics , biology , medicine , mathematical analysis , nursing
Abstract An efficient biologically enhanced sampling geometric docking method is presented based on the FTDock algorithm to predict the protein–protein binding modes. The active site data from different sources, such as biochemical and biophysical experiments or theoretical analyses of sequence data, can be incorporated in the rotation–translation scan. When discretizing a protein onto a 3‐dimensional (3D) grid, a zero value is given to grid points outside a sphere centered on the geometric center of specified residues. In this way, docking solutions are biased toward modes where the interface region is inside the sphere. We also adopt a multiconformational superposition scheme to represent backbone flexibility in the proteins. When these procedures were applied to the targets of CAPRI, a larger number of hits and smaller ligand root‐mean‐square deviations (RMSDs) were obtained at the conformational search stage in all cases, and especially Target 19. With Target 18, only 1 near‐native structure was retained by the biologically enhanced sampling geometric docking method, but this number increased to 53 and the least ligand RMSD decreased from 8.1 Å to 2.9 Å after performing multiconformational superposition. These results were obtained after the CAPRI prediction deadlines. Proteins 2005;60:319–323. © 2005 Wiley‐Liss, Inc.