Investigation of Methyl-5-(pentan-3-yloxy)-7-oxabicyclo[4.1.0]hept-3-ene-3-carboxyhydrazide Derivatives as Potential Inhibitors of COVID-19 Main Protease: DFT and Molecular Docking Study.
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引用次数: 0
Abstract
The search for effective therapeutics to combat COVID-19 has led to the exploration of the biological activity of numerous compounds. In this study, hydrazones derived from oseltamivir intermediate, methyl 5-(pentan-3-yloxy)-7-oxabicyclo[4.1.0]hept-3-ene-3-carboxylate have been investigated for their potential as drug candidates against the COVID-19 virus using computational methods, including density functional theory (DFT) studies, molecular docking, and absorption, distribution, metabolism, excretion and toxicity (ADMET) analysis. The DFT studies provide information on the electronic properties of the compounds while the molecular docking results using AutoDock reported the binding energies between the main protease of COVID-19 and the compounds. The DFT results revealed that the energy gap of the compounds ranged from 4.32 to 5.82 eV while compound HC had the highest energy gap (5.82 eV) and chemical potential (2.90 eV). The electrophilicity index values of the 11 compounds ranged from 2.49 to 3.86, thus they were classified as strong electrophiles. The molecular electrostatic potential (MESP) revealed electron-rich and electron-deficient regions of the compounds. The docking results reveal that all the compounds had better docking scores than remdesivir and chloroquine, frontline drugs employed in combating COVID-19, with HC having the best docking score of -6.5. The results were visualized using Discovery studio, which revealed hydrogen bonding, pi-alkyl interaction, alkyl interaction, salt bridge interaction, halogen interaction as being responsible for the docking scores. The drug-likeness results showed that the compounds qualify as oral drug candidates as none of them violated Vebers and Lipinski's rule. Thus, they could serve as potential inhibitors of COVID-19.
期刊介绍:
Bioinformatics and Biology Insights is an open access, peer-reviewed journal that considers articles on bioinformatics methods and their applications which must pertain to biological insights. All papers should be easily amenable to biologists and as such help bridge the gap between theories and applications.