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Binding Estimation after Refinement, a New Automated Procedure for the Refinement and Rescoring of Docked Ligands in Virtual Screening
Author(s) -
Rastelli Giulio,
Degliesposti Gianluca,
Del Rio Alberto,
Sgobba Miriam
Publication year - 2009
Publication title -
chemical biology and drug design
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.59
H-Index - 77
eISSN - 1747-0285
pISSN - 1747-0277
DOI - 10.1111/j.1747-0285.2009.00780.x
Subject(s) - virtual screening , computer science , docking (animal) , molecular dynamics , data mining , computational biology , chemistry , computational chemistry , biology , medicine , nursing
Binding estimation after refinement (BEAR) is a novel automated computational procedure suitable for correcting and overcoming limitations of docking procedures such as poor scoring function and the generation of unreasonable ligand conformations. BEAR makes use of molecular dynamics simulation followed by MM‐PBSA and MM‐GBSA binding free energy estimates as tools to refine and rescore the structures obtained from docking virtual screenings. As binding estimation after refinement relies on molecular dynamics, the entire procedure can be tailored to the needs of the end‐user in terms of computational time and the desired accuracy of the results. In a validation test, binding estimation after refinement and rescoring resulted in a significant enrichment of known ligands among top scoring compounds compared with the original docking results. Binding estimation after refinement has direct and straightforward application in virtual screening for correcting both false‐positive and false‐negative hits, and should facilitate more reliable selection of biologically active molecules from compound databases.