Computational Modelling and Experimental Validation of Novel Enzyme Inhibitors from Nigerian Plant Secondary Metabolites for Antidiabetic Drug Discovery

Structure-based computational drug discovery combined with biochemical validation of plant-derived secondary metabolites represents a productive strategy for identifying novel antidiabetic compounds from Nigerian biodiversity resources. This dissertation employs integrated computational modelling and experimental validation to identify and characterise novel inhibitors of alpha-glucosidase and dipeptidyl peptidase-4 from Nigerian plant secondary metabolites. A virtual screening library of eight hundred and forty-three secondary metabolites from fifty-six Nigerian medicinal plants was constructed from published phytochemical literature and in-house GC-MS and HPLC characterisation data. Molecular docking against the crystal structures of human alpha-glucosidase and DPP-4 was performed using AutoDock Vina, with binding free energy calculations by molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) method. Molecular dynamics simulations of top-ranked ligand-protein complexes were conducted to assess binding stability and conformational dynamics. The twelve most promising computational hits underwent experimental validation by enzyme inhibition kinetics using purified recombinant enzymes, with mode of inhibition classified by Lineweaver-Burk, Dixon, and Hill plot analysis. In vitro selectivity profiling excluded compounds with significant acetylcholinesterase or cytotoxic activity. Three compound classes, specifically modified chromones, lupane-type pentacyclic triterpenoids, and 1,2,3-trihydroxybenzene-substituted flavonoids, showed potent and selective dual alpha-glucosidase and DPP-4 inhibition with IC50 values below 10 micromolar and binding modes consistent with computational predictions. Structure-activity relationships derived from the biochemical dataset guided construction of a pharmacophore model as an original theoretical contribution for guiding antidiabetic natural product optimisation. Keywords: computational drug discovery, antidiabetic, enzyme inhibition, Nigerian plant metabolites, molecular docking.