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Identification of novel pyrazole containing ɑ-glucosidase inhibitors: insight into pharmacophore, 3D-QSAR, virtual screening, and molecular dynamics study.

Jannat Ul FirdausNadeem SiddiquiOzair AlamAjay ManaithiyaKailash Chandra
Published in: Journal of biomolecular structure & dynamics (2022)
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 R 2 = 0.77 and SD = 0.02 for training set, and Q 2 = 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.
Keyphrases
  • molecular dynamics
  • molecular docking
  • molecular dynamics simulations
  • density functional theory
  • machine learning
  • amino acid
  • ionic liquid