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

Iheagwam, Franklyn Nonso and Ogunlana, Olubanke Olujoke and Chinedu, Shalom Nwodo (2019) Model Optimization and In Silico Analysis of Potential Dipeptidyl Peptidase IV Antagonists from GC-MS Identified Compounds in Leaf Extracts. International journal of molecular sciences, 20 (23). ISSN 1422-0067

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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.

Item Type:	Article
Subjects:	Q Science > Q Science (General)
Divisions:	UNSPECIFIED
Depositing User:	Franklyn N IHEAGWAM
Date Deposited:	20 Jun 2021 21:49
Last Modified:	20 Jun 2021 21:49
URI:	http://eprints.covenantuniversity.edu.ng/id/eprint/14763

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