ABSTRACT
The infection by the new coronavirus SARS-CoV-2 (called as COVID-19 disease) is a worldwide emergency, however, there is no antiviral treatment or vaccine to date. 3C like protease (3CLpro) is the main protease of SARS-CoV-2 that involved in the process of translation of the polypeptide from the genomic RNA to protein components, which are required for virus replication. The crystal structure of this protease has been rapidly resolved and made publicly in the Protein Data Bank recently. Many efforts have been conducted by scientists including the use of several commercial medicines that are known for treatment of HIV and anti-malarial/antibiotic such as arbidol, chloroquine, hydroxychloroquine, azithromycin, darunavir, remdesivir and lopinavir/ritonavir. These drugs exhibited significant efficacy in clinical, however, the understanding at atomic level of how these compounds prevent SARS-CoV-2 protease is still lacking. Therefore, in this context docking protocol was employed to rapidly estimate the binding affinity and binding pose of six drugs on the main protease of SARS-CoV-2 virus. The obtained results might help to shed light on the interaction mechanism of these compounds toward the protein, and thus suggesting an efficient approach to drug discovery and treatments. © 2020, Publishing House of Natural Science and Technology, VAST. All rights reserved.
ABSTRACT
The worldwide pandemic caused by coronavirus SARS-CoV-2 (so called as COVID-19 disease) has affected 219 countries and territories, leading to numerous deaths and global financial crisis. The main protease (Mpro) of SARS-CoV-2 plays an important role in mediating the transcription and replication of virus, thus, one of the main therapeutic measures is to find compounds capable of inhibiting these enzymes as soon as possible. Nowadays, computer-aided drug design plays an important role in the field of drug discovery. In particular, molecular docking is one of the initial steps that effectively screen a numerous number of compounds for their interaction and binding affinity toward targeted enzyme, therefrom, suggesting a short list of potential inhibitors for further drug development processes. As part of our ongoing program to provide simple guideline for scientific community to utilize different docking tools for research purposes, in this article, a complete manual guideline of Autodock 4.2.6 is presented to demonstrate the simulation of interaction between compound PF-07321332 and the main protease of SARS-CoV-2, thereby suggesting an effective tool for scientists to conduct reseach on this disease. © 2022, Publishing House of Natural Science and Technology, VAST. All rights reserved.