Abstract

IN SILICO EVALUATION OF ANTIDIABETIC ACTIVITY USING MOLECULAR DOCKING AND ADMET PREDICTION OF COMPOUNDS FROM FICUS BENGALENSIS LINN

Dr. Fegade Sachin*, Gunjegaonkar Manjushree, Khot Suchita

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Abstract

Diabetes mellitus is a prevalent metabolic disorder requiring safer and more effective therapeutic alternatives. The present study aimed to investigate the antidiabetic potential of phytochemical derived from Ficus bengalensis Linn through in silico molecular docking and ADMET prediction. Phytoconstituents were collected from F. bengalensis extract and subjected to molecular docking studies using PyRx with AutoDock Vina. The crystal structures of key diabetesrelated protein targets, α-amylase (PDB: 4A5S) and α-glucosidase (PDB: 6FZP), were employed for binding affinity evaluation. The interaction profiles were analyzed to determine binding scores and key amino acid interactions. To assess drug-likeness and pharmacokinetic feasibility, ADMET properties were predicted using Swiss ADME. Compound displayed favorable binding affinities toward both target enzymes, suggesting inhibitory potential. Docking analysis revealed stable interactions with active site residues, indicating possible modulation of carbohydrate metabolism. ADMET predictions demonstrated that the extracted compounds complied with Lipinski’s rule of five and showed acceptable pharmacokinetic and safety profiles. The findings suggest that bioactive constituents from Ficus bengalensis may serve as promising antidiabetic lead molecules. Further in vitro and in vivo validation is warranted to substantiate their therapeutic potential.

Keywords: α-glucosidase, DPP4, ADMET prediction, diabetes, molecular docking, Ficus bengalensis.