In silico Tools and Techniques for Screening and Development of Peptide-Based Spike Protein Inhibitors against Novel Coronavirus (Sars-CoV-2)

The recent pandemic situation created by the novel coronavirus (SARS-CoV-2) across the globe is a great concern.So, the discovery of novel antiviral agents is desirable to address this challenge.In this context, the antiviral peptides (AVPs) possess an enormous potential and can be considered to develop novel therapeutic strategies to combat SARS-CoV-2 infection.The anti-viral peptides are mostly preferable over small inhibitor molecules for having high target specificity and lower side effects.The spike protein is an important structural protein of SARS-CoV-2 that binds with the human angiotensin-converting enzyme-2 leading to host entry of the virus.Hence, the activity of the anti-viral peptides will be based on the interference of the peptide inhibitor between the binding site of spike protein, and the ACE2 protein ultimately will prevent the virus invasion process.Several database resources are available that contain many anti-viral peptides from natural sources.However, the experimental basis of establishing the therapeutic importance of every protein from the database is a difficult and time-consuming task.Hence the available bioinformatics tools and techniques can be suitably used to screen, structure prediction, evaluation of ant-viral peptide-SARS-CoV-2 spike protein interaction, toxicity prediction, molecular dynamics simulation, and so on.In this review, the implementation of some of the major computational tools, their availability, and effectiveness in predicting the peptides against the Spike protein have been discussed.