Computational Study of Alkaloids Targeting O-GlcNAc Transferase as Antidiabetic Agents

O-GlcNAc Transferase (OGT) plays a pivotal role in glucose metabolism and insulin signaling, making it an attractive therapeutic target for the management of diabetes mellitus. In the present study, a comprehensive in silico approach was employed to investigate the inhibitory potential of selected alkaloids against human OGT, with an emphasis on their binding affinity and pharmacokinetic suitability. Molecular docking analysis was performed using AutoDock Vina to elucidate the interaction patterns between the selected compounds and the active site of OGT. The docking results revealed that berberine exhibited the strongest binding affinity (−7.8 kcal/mol), slightly surpassing that of the native ligand (−7.7 kcal/mol), and formed stable hydrogen bonding and hydrophobic interactions with key catalytic residues such as LYS898, ASN838, and PRO559. In contrast, castanospermine and swainsonine showed comparatively weaker binding affinities, attributed to limited interaction networks within the binding pocket. To further assess the drug development potential of the studied compounds, in silico ADMET analysis was carried out using SwissADME and ADMETlab 3.0. Berberine demonstrated favorable physicochemical properties, superior drug-likeness (highest QED score), and acceptable absorption and toxicity profiles compared to the native ligand and other alkaloids. Although potential cytochrome P450 interactions and moderate bioaccumulation were predicted for berberine, its overall pharmacokinetic profile was well balanced. Collectively, the integrated docking and ADMET results highlight berberine as a promising lead alkaloid targeting OGT, warranting further in vitro and in vivo validation for its potential development as an antidiabetic agent.

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