چكيده لاتين
The identification of the novel coronavirus (SARS-CoV-2), the latest known virus from the coronavirus family, was carried out in late December 2019 in the city of Wuhan, China. This virus is the cause of a respiratory disease and has affected more than 219 countries to date, causing countless unintended deaths among people in recent global pandemic situations. Therefore, there is a need to understand the function of this new virus and to develop preventive and therapeutic drugs. Since drug development is a highly expensive and time-consuming process, the use of bioinformatics approaches for predicting relative responses to treatment and for research solutions such as genomics, and molecular modeling provide valuable insights. The primary treatment for this virus has been the use of antiviral drugs, which weaken the ability of viruses to enter cells and prevent their replication or transmission from infected cells to other cells. Today, therapeutic peptides have played a significant role in medical science, and with the latest advances in peptide research, the use of these therapies has increased in recent years, and peptide drugs have received much attention. The main aim of this research was to design inhibitory peptides against the Mpro protein using using uni- and bi-directional incremental construction method for use in the treatment of coronavirus disease. To achieve this, bioinformatics software such as molecular docking and virtual screening were used. For this purpose, the Mpro protein of the coronavirus, which plays a role in the treatment of coronavirus disease, was investigated and entered into docking studies. After obtaining and optimizing the ligand and receptor, molecular docking was performed, and each time this was done, different dimensions were set for the adjustment box. Ultimately, the docking with the most desirable binding energy and the most suitable position was selected as the final positive control. Then, peptide libraries with lengths of 2 to 10 amino acids were designed and screened, and subsequently, the protein-peptide complex resulting from screening was compared with the protein-inhibitor complex (positive control). Then, three graphs were plotted based on various parameters such as peptide length, maximum, minimum, and average binding energies of the peptides were analyzed and explained in more detail. The results showed that with an increase in peptide length, better connections were established, and more negative energy was obtained. In other words, with an increase in peptide length, their inhibitory effect also increased, which can be used for the design of new and improved drugs.
