Abstract
World Health Organization (WHO) reveals total number of coronavirus cases are 5,684,802 and 352,225 deaths till today worldwide. Coronavirus instances are nevertheless surging due to its speedy spreading through infected patients. Therefore, in order to find potent vaccine almost every researcher is doing hard work to find it. However, until today there is not any availability of effective vaccine or drug for the treatment of COVID-19. In this case, the computational approach is the good choice to identify effective drugs and could be very useful due to its low cost, less error and less time consumption. Here, Deketene curcumin has taken for docking study because of its lots of biological applications such as antiviral, antimicrobial, anti-inflammatory, antioxidant, antibiotic, and to a name of few, it is a derivative of curcumin. In this study, five main protease crystallized COVID-19 structures (PDB ID: 6LU7, 5R7Z, 5R7Y, 5R80, 5R81) have been taken for simulation against deketene curcumin. Required procedure for this in silico study done through Molegro virtual docker (MVD) and Molegro Molecular Viewer (MMV) used for visualization. The results showed H-bonding and steric interaction between Deketene Curcumin with COVID-19 (PDB ID: 6LU7, 5R7Z, 5R7Y, 5R80, 5R81). Moldock scores of Deketene Curcumin Observed -134.198 kcal/mol, -151.972 kcal/mol, -109.224 kcal/mol, -140.741 kcal/mol and -126.562 kcal/mol with PDB Id 6LU7, 5R7Z, 5R7Y, 5R80 and 5R81 respectively. As per our results, it can be say that Deketene Curcumin has effective as a lead compound to find new antiviral drug candidates against COVID-19 for possible medicinal agent.