title: Predicting protein interactions by Brownian dynamics simulations.
abstract: We present a newly adapted Brownian-Dynamics (BD)-based protein docking method for predicting native protein complexes. The approach includes global BD conformational sampling, compact complex selection, and local energy minimization. In order to reduce the computational costs for energy evaluations, a shell-based grid force field was developed to represent the receptor protein and solvation effects. The performance of this BD protein docking approach has been evaluated on a test set of 24 crystal protein complexes. Reproduction of experimental structures in the test set indicates the adequate conformational sampling and accurate scoring of this BD protein docking approach. Furthermore, we have developed an approach to account for the flexibility of proteins, which has been successfully applied to reproduce the experimental complex structure from the structure of two unbounded proteins. These results indicate that this adapted BD protein docking approach can be useful for the prediction of protein-protein interactions.
authors.affiliation: Department of Physiology and Biophysics, Virginia Commonwealth University, Richmond, VA 23298, USA.
authors.forename: Xuan-Yu
authors.initials: XY
authors.lastname: Meng
authors.forename: Yu
authors.initials: Y
authors.lastname: Xu
authors.forename: Hong-Xing
authors.initials: HX
authors.lastname: Zhang
authors.forename: Mihaly
authors.initials: M
authors.lastname: Mezei
authors.forename: Meng
authors.initials: M
authors.lastname: Cui
mesh_terms: D000465:Algorithms; D056004:Molecular Dynamics Simulation; D011485:Protein Binding; D025941:Protein Interaction Mapping / Q000379:methods*; D011506:Proteins / Q000737:chemistry* / Q000378:metabolism*; D055672:Static Electricity; D013816:Thermodynamics
chemical_list: D011506:Proteins