ABSTRACT
Drug development is a tedious, expensive and time consuming process that is accompanied with huge amount of uncertainty due to very low success rate using conventional methods. However, in-silico techniques have helped society in drug designing and repurposing at minimal cost by shortlisting potentially hit compounds from huge libraries in a short span of time. This computational methodology has made a prominent contribution in the virtual screening of therapeutically relevant drugs for various viral diseases. It has helped in providing relevant information regarding drug-target interaction and mechanism through which we can modify our drug compound for better efficiency. In-silico tools additionally helps in predicting toxicity and pharmacokinetics, which can further help in clearing trials and approval. The recent outbreak of novel coronavirus (COVID-19) has resulted in a huge number of deaths and affected the economy of the world adversely. Computational methods have played a major role in shortlisting compounds that can inhibit viral infection by targeting various components of this virus which are essential in spreading the infection and replication mechanism. The repurposing of the drug against coronavirus has become a lot easier and efficient with the advancement in these computational techniques. Hence, this review covers the recent developments in the virtual screening of potentially hit compounds against COVID-19.