Computational Approaches in the Discovery and Development of Therapeutic and Prophylactic Agents for Viral Diseases

Abstract

Abstract: Over the last two decades computational technologies have always played a crucial role in anti-viral drug development. Whenever a virus spreads and becomes a threat to global health it brings along the challenge to develop new therapeutics and prophylactics. Computational drug and vaccine discovery have evolved at a breakneck pace over the years. Some interesting examples of computational drug discovery are anti-AIDS drugs, where HIV protease and reverse transcriptase have been targeted by agents developed using computational methods. Various computational methods that have been applied to anti-viral research include, ligand-based methods that rely on known active compounds i.e., pharmacophore modeling, machine learning or classical QSAR; structure-based methods that rely on an experimentally determined 3D structure of the targets i.e., molecular docking and molecular dynamics and methods for development of vaccines such as reverse vaccinology; structural vaccinology and vaccine epitope prediction. In this review we summarize these approaches as they were applied to battle viral diseases and underscore their importance for anti-viral research. We discuss the role of computational methods in the development of small molecules and vaccines against, human immunodeficiency virus, yellow fever, human papilloma virus, SARS-CoV-2, and other viruses. Various computational tools available for abovementioned purposes have been listed and described. A discussion on application of artificial intelligence-based methods for antiviral drug discovery has also been included.