Abstract
Pharmacophore modelling, 3 D QSAR modelling, virtual screening, and molecular dynamics study, all-in-one combination were employed successfully design and develop an alpha-glucosidase inhibitor. To explain the structural prerequisites of biologically active components, 3 D-QSAR models were generated using the selected best hypothesis (AARRR) for compounds 55 included in the model C. The selection of 3 D-QSAR models showed that the Gaussian steric characteristic is crucial to alpha glucosidase’s inhibitory potential. The alpha-glucosidase inhibitory potency of the compound is enhanced by other components, including Gaussian hydrophobic groups, Gaussian hydrogen bond acceptor or donor groups, Gaussian electrostatic characteristics, and a Gaussian steric feature. An identification of structure-activity relationships can be obtained from the developed 3 D-QSAR, C model, with R2 = 0.77 and SD = 0.02 for training set, and Q2 = 0.66, RMSE 0.02, and Pearson R = 0.81 for testing set, corresponding to elevated predictive ability. Additionally, docking and MM/GBSA experiments on 1146023 showed that it interacts with critical amino acids in the binding site when coupled with acarbose. Further, five compounds that display a high affinity for alpha-glucosidase were found, and these compounds may serve as potent leads for alpha-glucosidase inhibitor development. Biological activity will be tested for these compounds in the future.
Communicated by Ramaswamy H. Sarma
Disclosure statement
No potential conflict of interest was reported by the authors.