Computational modeling of 4-Phenoxynicotinamide and 4-Phenoxypyrimidine-5-carboxamide derivatives as potent anti-diabetic agent against TGR5 receptor

• Main Authors: Shola Elijah Adeniji, David Ebuka Arthur, Adedirin Oluwaseye
• Format: Article
• Language: English
• Published: Elsevier 2020-01-01
• Series: Journal of King Saud University: Science
• Online Access: http://www.sciencedirect.com/science/article/pii/S1018364718302428

Computational study was carried out to develop a Quantitative structure-activity relationship (QSAR) model and molecular docking studies on 4-Phenoxynicotinamide and 4-Phenoxypyrimidine-5-carboxamide derivatives as potent anti-diabetic agent. Chemical structure of these molecules were optimized with Density Functional Theory (DFT) utilizing the B3LYP with 6-31G∗ basis set. Five QSAR models were generated using Multi-Linear Regression and Genetic Function Approximation (GFA). Model one was selected as the optimum model and reported based on validation parameters which were found to be statistically significant with squared correlation coefficient (R2) of 0.9460, adjusted squared correlation coefficient (R2 adj) value of 0.9352 and cross validation coefficient (Qcv2) value of 0.9252. The chosen model was subjected to external validations and the model was found to have (R2test) of 0.8642. Molecular docking studies revealed that the binding affinities of the compounds correlate with their pEC50 and the best compound has binding affinity of −10.4 kcal/mol which formed hydrogen bond and hydrophobic interaction and with amino acid residues of TGR5 receptor. QSAR model generated and molecular docking results propose the direction for the design of new anti-diabetic agent with better activity against TGR5 target site. Keywords: Anti-diabetic, Applicability domain, Binding affinity, Molecular docking, QSAR