QSAR modelling and docking analysis of some thiazole analogues as alfa-glucosidase inhibitors
QSAR modelling and docking studies on 45 thiazole analogues were carried out. The studied compounds in this research were optimized adopting DFT method at B3LYP function with a 6-31G* basis set. The QSAR models were generated in material studio by MLR analysis (GFA method). Based on its statistical...
| Autores: | , , , |
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2019 |
| País: | Brasil |
| Institución: | Universidade Federal de Viçosa (UFV) |
| Repositorio: | The Journal of Engineering and Exact Sciences |
| Idioma: | inglés |
| OAI Identifier: | oai:ojs.periodicos.ufv.br:article/8019 |
| Acceso en línea: | https://periodicos.ufv.br/jcec/article/view/8019 |
| Access Level: | acceso abierto |
| Palabra clave: | QSAR Molecular modelling docking Diabetes |
| Sumario: | QSAR modelling and docking studies on 45 thiazole analogues were carried out. The studied compounds in this research were optimized adopting DFT method at B3LYP function with a 6-31G* basis set. The QSAR models were generated in material studio by MLR analysis (GFA method). Based on its statistical fitness, the first model was selected and chosen as the studied model and assessed with R2 = 0.906134, R2 adj = 0.89049, Q2cv = 0.86149 and R2 pred = 0.82581. The ligand with the highest binding energy of -11.0 kcal/mol among the other ligands was ligand 13 as indicated by the molecular docking. The standard drug (acarbose) was also docked to the binding pocket of alfa-glucosidase with -9.5kcal/mole docking score. The most active compound was found to be better than standard drug. The outcome of this findings paved way for predicting novel ?-glucosidase inhibitors having improved potency toward the target enzyme. |
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