In the drug discovery process, accurate methods of computing the affinity of small molecules with a desired biological target are strongly needed. To this end, we developed Binding Estimation After Refinement (BEAR), a new and automated post-docking procedure for the conformational refinement of docking poses through molecular dynamics (MD) followed by accurate prediction of binding free energies using MM-PBSA and MM-GBSA. The BEAR performance in virtual screening was evaluated on several macromolecular targets and related sets of known ligands, determining the enrichment factors and assessing the correlation between predicted and experimental binding affinities. Moreover, when applied in virtual screening campaigns, BEAR was able to discover novel and potent inhibitors of Plasmodium falciparum plasmepsin II with an impressive hit rate, and has been successful in identifying promising scaffolds for the design of irreversible protein kinase inhibitors. The BEAR virtual screening procedure is reliable and strongly automated, and can be tailored to the needs of the end-user in terms of computational time and the desired accuracy of the results.
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