title: Surflex-Dock 2.1: robust performance from ligand energetic modeling, ring flexibility, and knowledge-based search.
abstract: The Surflex flexible molecular docking method has been generalized and extended in two primary areas related to the search component of docking. First, incorporation of a small-molecule force-field extends the search into Cartesian coordinates constrained by internal ligand energetics. Whereas previous versions searched only the alignment and acyclic torsional space of the ligand, the new approach supports dynamic ring flexibility and all-atom optimization of docked ligand poses. Second, knowledge of well established molecular interactions between ligand fragments and a target protein can be directly exploited to guide the search process. This offers advantages in some cases over the search strategy where ligand alignment is guided solely by a "protomol" (a pre-computed molecular representation of an idealized ligand). Results are presented on both docking accuracy and screening utility using multiple publicly available benchmark data sets that place Surflex's performance in the context of other molecular docking methods. In terms of docking accuracy, Surflex-Dock 2.1 performs as well as the best available methods. In the area of screening utility, Surflex's performance is extremely robust, and it is clearly superior to other methods within the set of cases for which comparative data are available, with roughly double the screening enrichment performance.
authors: Department of Biopharmaceutical Sciences, UCSF Cancer Research Institute, University of California-San Francisco, Box 0128, San Francisco, CA 94143-0128, USA. ajain@jainlab.org
authors: Ajay N
authors: AN
authors: Jain
mesh_terms: D000465:Algorithms; D015195:Drug Design; D008024:Ligands; D008956:Models, Chemical; D011083:Polycyclic Compounds / Q000737:chemistry*; D012984:Software; D013816:Thermodynamics
chemical_list: D008024:Ligands; D011083:Polycyclic Compounds