Model Optimization and In Silico Analysis of Potential Dipeptidyl Peptidase IV Antagonists from GC-MS Identified Compounds in Leaf Extracts.

Abstract

Dipeptidyl peptidase IV (DPP-IV) is a pharmacotherapeutic target in type 2 diabetes. Inhibitors of this enzyme constitute a new class of drugs used in the treatment and management of type 2 diabetes. In this study, phytocompounds in (NL) leaf extracts, identified using gas chromatography-mass spectroscopy (GC-MS), were tested for potential antagonists of DPP-IV via in silico techniques. Phytocompounds present in aqueous (NLA) and ethanol (NLE) leaf extracts were identified using GC-MS. DPP-IV model optimization and molecular docking of the identified compounds/standard inhibitors in the binding pocket was simulated. Drug-likeness, pharmacokinetic and pharmacodynamic properties of promising docked leads were also predicted. Results showed the presence of 50 phytocompounds in NL extracts of which only 2--p-methylphenyl-1-thio-β-d-glucoside, 3-tosylsedoheptulose, 4-benzyloxy-6-hydroxymethyl-tetrahydropyran-2,3,5-triol and vitamin E exhibited comparable or better binding iGEMDOCK and AutoDock Vina scores than the clinically prescribed standards. These four compounds exhibited promising drug-likeness as well as absorption, distribution, metabolism, excretion and toxicity (ADMET) properties suggesting their candidature as novel leads for developing DPP-IV inhibitors