Advancements in Drug Design Technology and Its Impact on COVID-19 Treatment - Mohd. Wasiullah; Piyush Yadav; Raj Aryan Prajapati; Satish Kumar Yadav; Neha Parveen (International Journal of Virus Studies, 2024)
The deadly coronavirus disease 19 (COVID-19) pandemic has recently spread, raising concerns about global health. The search for novel therapeutic compounds is made more necessary by the persistent problem of the absence of licensed medications or vaccinations. By saving money and time, computer-aided drug design has sped up the process of finding and developing new drugs. The structured-based and ligand-based drug discovery subcategories of computer-aided drug design (CADD) are the main topics of this review study. In ligand-based drug design, pharmacophoremodeling, quantitative structure-activity relationships (QSARs), and artificial intelligence (AI) are commonly employed molecular modeling techniques, whereas structure-based drug design often involves molecular docking and molecular dynamic simulation. We have touched on the importance of computer-aided drug design in relation to COVID-19 and how scientists are still depending on these computational methods to quickly identify molecules that show promise as potential drugs against different targets connected to the pathophysiology of SARS-CoV-2, or severe acute respiratory syndrome coronavirus. Cross-species viruses known as coronaviruses (CoVs) can quickly move from their original host species into other ones, whereupon they can cause epidemic diseases. This article provides a comprehensive examination of computational methodologies and their utilization in the realm of drug development. Chemogenomics and drug discovery (DR) are highlighted as novel and developing system-based fields that are focused on modeling protein networks versus a library of chemicals in CoV infections. Furthermore, a number of recent successes based on chemogenomics,and molecular docking are given, thoroughly examined, and interpreted to highlight the unique benefits of CADD approaches in quickly developing a treatment for this deadly virus. The review's findings should help researchers who are creating energy-harvesting materials and systems identify new, unanticipated CoV strains or other variations in the future.
Keywords: COVID-19; Chemogenomics; Computer-aided drug design (CADD); Pharmacophore modelling; molecular docking