Computational study of some potential inhibitors of COVID‐19: A DFT analysis

Background There is an urgent demand of drug or therapy to control the COVID‐19. Until July 22, 2021 the worldwide total number of cases reported is more than 192 million and the total number of deaths reported is more than 4.12 million. Several countries have given emergency permission for use of repurposed drugs for the treatment of COVID‐19 patients. This report presents a computational analysis on repurposing drugs—tenofovir, bepotastine, epirubicin, epoprostenol, tirazavirin, aprepitant and valrubicin, which can be potential inhibitors of the COVID‐19. Method Density functional theory (DFT) technique is applied for computation of these repurposed drug. For geometry optimization, functional B3LYP/6‐311G (d, p) is selected within DFT framework. Results DFT based descriptors—highest occupied molecular orbital (HOMO)‐lowest unoccupied molecular orbital (LUMO) gap, molecular hardness, softness, electronegativity, electrophilicity index, nucleophilicity index and dipole moment of these species are computed. IR and Raman activities are also analysed and studied. The result shows that the HOMO‐LUMO gap of these species varies from 1.061 eV to 5.327 eV. Compound aprepitant with a HOMO‐LUMO gap of 1.419 eV shows the maximum intensity of IR (786.176 km mol ‒1 ) and Raman spectra (15036.702 a.u.). Conclusion Some potential inhibitors of COVID‐19 are studied by using DFT technique. This study shows that epirubicin is the most reactive compound whereas tenofovir is found to be the most stable. Further analysis and clinical trials of these compounds will provide more insight.