title: PRL-Dock: protein-ligand docking based on hydrogen bond matching and probabilistic relaxation labeling.
abstract: Protein-ligand docking is widely applied to structure-based virtual screening for drug discovery. This article presents a novel docking technique, PRL-Dock, based on hydrogen bond matching and probabilistic relaxation labeling. It deals with multiple hydrogen bonds and can match many acceptors and donors simultaneously. In the matching process, the initial probability of matching an acceptor with a donor is estimated by an efficient scoring function and the compatibility coefficients are assigned according to the coexisting condition of two hydrogen bonds. After hydrogen bond matching, the geometric complementarity of the interacting donor and acceptor sites is taken into account for displacement of the ligand. It is reduced to an optimization problem to calculate the optimal translation and rotation matrixes that minimize the root mean square deviation between two sets of points, which can be solved using the Kabsch algorithm. In addition to the van der Waals interaction, the contribution of intermolecular hydrogen bonds in a complex is included in the scoring function to evaluate the docking quality. A modified Lennard-Jones 12-6 dispersion-repulsion term is used to estimate the van der Waals interaction to make the scoring function fairly "soft" so that ligands are not heavily penalized for small errors in the binding geometry. The calculation of this scoring function is very convenient. The evaluation is carried out on 278 rigid complexes and 93 flexible ones where there is at least one intermolecular hydrogen bond. The experiment results of docking accuracy and prediction of binding affinity demonstrate that the proposed method is highly effective.
authors.affiliation: Center for Computer Vision, Department of Mathematics, Sun Yat-Sen University, Guangzhou 510275, China.
authors.forename: Meng-Yun
authors.initials: MY
authors.lastname: Wu
authors.forename: Dao-Qing
authors.initials: DQ
authors.lastname: Dai
authors.forename: Hong
authors.initials: H
authors.lastname: Yan
mesh_terms: D000465:Algorithms; D019295:Computational Biology; D003198:Computer Simulation; D030562:Databases, Protein; D006860:Hydrogen Bonding; D008956:Models, Chemical; D008958:Models, Molecular; D011485:Protein Binding; D011506:Proteins / Q000737:chemistry* / Q000378:metabolism*; D015203:Reproducibility of Results
chemical_list: D011506:Proteins