A holistic approach to protein docking.
Docking of unbound protein structures into a complex has gained significant progress in recent years, but nonetheless still poses a great challenge. We have pursued a holistic approach to docking which brings together effective methods at different stages. First, protein-protein interaction sites are predicted or obtained from experimental studies in the literature. Interface prediction/experimental data are then used to guide the generation of docked poses or to rank docked poses generated from an unbiased search. Finally, selected models are refined by lengthy molecular dynamics (MD) simulations in explicit water. For CAPRI target T27, we used information on interaction sites as input to drive docking and as a filter to rank docked poses. Lead candidates were then clustered according to RMSD among them. From the clustering, 10 models were selected and subject to refinement by MD simulations. Our Model 7 is rated number one among all submissions according to L_rmsd. Six of our other submissions are rated acceptable. As scorer, eight of our submissions are rated acceptable.
Qin
Sanbo
S
Institute of Molecular Biophysics, Florida State University, Tallahassee, Florida 32306, USA.
Zhou
Huan-Xiang
HX
D000465:Algorithms; D000818:Animals; D019295:Computational Biology / Q000379:methods*; D003198:Computer Simulation; D018360:Crystallography, X-Ray / Q000379:methods; D030562:Databases, Protein; D019281:Dimerization; D023281:Genomics; D006801:Humans; D008968:Molecular Conformation; D011485:Protein Binding; D011487:Protein Conformation; D025941:Protein Interaction Mapping; D011506:Proteins / Q000737:chemistry*; D040901:Proteomics / Q000379:methods*; D012984:Software