title: BEAR, a novel virtual screening methodology for drug discovery.
abstract: BEAR (binding estimation after refinement) is a new virtual screening technology based on the conformational refinement of docking poses through molecular dynamics and prediction of binding free energies using accurate scoring functions. Here, the authors report the results of an extensive benchmark of the BEAR performance in identifying a smaller subset of known inhibitors seeded in a large (1.5 million) database of compounds. BEAR performance proved strikingly better if compared with standard docking screening methods. The validations performed so far showed that BEAR is a reliable tool for drug discovery. It is fast, modular, and automated, and it can be applied to virtual screenings against any biological target with known structure and any database of compounds.
authors.affiliation: Dipartimento di Scienze Farmaceutiche, Università di Modena e Reggio Emilia, Modena, Italy.
authors.forename: Gianluca
authors.initials: G
authors.lastname: Degliesposti
authors.forename: Corinne
authors.initials: C
authors.lastname: Portioli
authors.forename: Marco Daniele
authors.initials: MD
authors.lastname: Parenti
authors.forename: Giulio
authors.initials: G
authors.lastname: Rastelli
mesh_terms: D003198:Computer Simulation; D015195:Drug Design; D055808:Drug Discovery / Q000379:methods*; D004791:Enzyme Inhibitors / Q000737:chemistry*; D008024:Ligands; D008958:Models, Molecular; D056004:Molecular Dynamics Simulation; D011485:Protein Binding; D054852:Small Molecule Libraries / Q000737:chemistry*; D013762:Tetrahydrofolate Dehydrogenase / Q000378:metabolism
chemical_list: D004791:Enzyme Inhibitors; D008024:Ligands; D054852:Small Molecule Libraries; D013762:Tetrahydrofolate Dehydrogenase