Mohammad Nasir Movahhedi Ali Ahmad yousefi Zaman Nourozi
Abstract
Introduction: the rapid spread of the SARS-CoV-2 virus and the extensive global impact of COVID-19 have underscored the urgent need for discovering and developing new drugs. In silico methods, utilizing molecular simulations and computational techniques, have emerged as effective tools for identifying potential therapeutic compounds. These methods allow for the rapid assessment of drug effects before proceeding to laboratory and clinical testing. Objective: this study aims to investigate the role of in silico methods in simulating and evaluating potential therapeutic compounds for the treatment of COVID-19, with a particular focus on identifying drugs such as Remdesivir as effective treatment options. Methodology: this research was conducted using a library-based and systematic review approach. Data were collected from reputable scientific databases such as PubMed, Scopus, and Web of Science. The analysis of existing data from these sources was used to better understand the application of in silico methods in discovering new drugs. Results: the findings of this study indicate that in silico methods have been highly effective in identifying drugs like Remdesivir. These methods have successfully reduced the time and cost of drug research and have facilitated the identification of potential therapeutic compounds prior to clinical trials.