title: Computer-aided Drug Design: Using Numbers to your Advantage.
abstract: Computer-aided drug design could benefit from a greater understanding of how errors arise and propagate in biomolecular modeling. With such knowledge, model predictions could be associated with quantitative estimates of their uncertainty. In addition, novel algorithms could be designed to proactively reduce prediction errors. We investigated how errors propagate in statistical mechanical ensembles and found that free energy evaluations based on single molecular configurations yield maximum uncertainties in free energy. Furthermore, increasing the size of the ensemble by sampling and averaging over additional independent configurations reduces uncertainties in free energy dramatically. This finding suggests a general strategy that could be utilized as a post-hoc correction for improved precision in virtual screening and free energy estimation.
authors: Department of Chemistry and the Quantum Theory Project, 2328 New Physics Building, P.O. Box 118435, University of Florida, Gainesville, Florida 32611-8435.
authors: John C
authors: JC
authors: Faver
authors: M Nihan
authors: MN
authors: Ucisik
authors: Wei
authors: W
authors: Yang
authors: Kenneth M
authors: KM
authors: Merz
keywords: Computer-aided drug design; docking and scoring; error analysis; free energy; statistical mechanics; virtual screening