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ABSTRACT:
SUBMITTER: Karges J
PROVIDER: S-EPMC8919381 | biostudies-literature | 2022 Mar
REPOSITORIES: biostudies-literature
Karges Johannes J Stokes Ryjul W RW Cohen Seth M SM
ACS medicinal chemistry letters 20220224 3
Computational modeling of inhibitors for metalloenzymes in virtual drug development campaigns has proven challenging. To overcome this limitation, a technique for predicting the binding pose of metal-binding pharmacophores (MBPs) is presented. Using a combination of density functional theory (DFT) calculations and docking using a genetic algorithm, inhibitor binding was evaluated in silico and compared with inhibitor-enzyme cocrystal structures. The predicted binding poses were found to be consi ...[more]