As on today 23nd June 2020 there are 8974765 COVID-19 cases worldwide and reported 469159 deaths and 216 countries, areas and territories affected according to the World Health Organization (WHO). In silico approach, docking has become a promising tool for drug discovery and development. We study virtual interaction of ligand (drug) molecules inside the binding pocket of target protein (receptor) . It offers study of all the factors that are being utilized for drug discovery such as identification of hit molecules, optimization of lead compound and virtual screening. . Since it has been reported that the several existing drug showed potential against COVID-19 including oseltamivir, lopinavir, ritonavir, remdesivir, favipiravir, ribavirin, chloroquine and hydroxychloroquine. Since most of the drugs are HIV protease inhibitors we have performed their docking with COVID-19 main protease downloaded from protein data bank (PDB ID 7BRP). Some of the Potential Therapeutic Target Against SARS-CoV and SARS-CoV-2 Several similarities between SARS-CoV-2 and SARS-CoV have been reported. Since the sequencing of SARS-CoV-2 has been done, it has given rise to various molecular modeling experiments to find the potential candidate against novel coronavirus SARS-CoV-2. The SARSCoV-2 originating from bat has been revealed by the phylogenetic analysis. Xu et al. have performed some molecular modeling experiments which revealed similarity in the 3-D structures of SARS-CoV-2 and SARS-CoV in the RBD (receptor binding domain). This leads to designing of various approaches to find out the potential target for development of potential drug candidate against SARS-CoV-2. Molecular Docking Study of Some Drug Candidates with Protease of SARS-CoV-2. Due to unavailability of specific treatment for COVID-19 are several antiretroviral drugs reported to show effectiveness against COVID-19 including ritonavir, lopinavir, alone or in combination with oseltamivir, remdesivir, chloroquine and hydroxychloroquine. . Out of these, ritonavir, remdesivir, chloroquine and hydroxychloroquine has shown efficacy at cellular level which will be evaluated in future by various experimental studies. In drug discovery, molecular docking methodologies is a useful tool as is rapid screening of candidates from drug libraries. . In this research, we have performed docking study of some of the potential therapeutic drug candidates that are being used against COVID-19 worldwide by using computational techniques. Methods of all the docking experiments were performed by using Auto Dock Vina extended on 1 o A Samson 2020 (software for adaptive modeling and simulation of nano systems), because (a) it offers more accuracy in predicting ligand-protein interaction compared to its previous Auto Dock 4.2 (b) it offers shorter running time because of its multiple core processors (c) it offer more accuracy for ligand processing more than 20 rotatable bonds. All dockings were performed as blind dockings (blind docking refers to the use of a grid box which is large enough to encompass any possible ligand-receptor complex). All the protein structures used in docking experiments were retrieved from the protein data bank. All the conformational ligand structures were created by using smiles codes on Samson software to have the most stable structure using energy minimization for the force field and conjugate gradient method. The ligand and protein molecules were converted to their proper readable file format pdb files using Discovery Studio Visualizer 2020. The docking was done using an exhaustiveness value From the binding affinity Table1 & Fig. and bonding interaction Fig. , it is clearly understood that betamethasone phosphate has shown more binding affinity than remedesivir and comparatively more stable in all the ten modes as per the binding affinity values. Even though remedesivir has shown a greater number of pi-alkyl, alkyl binding interactions with protein binding sites, the presence of strong F-hydrogen bonding and F-pi bond interactions are predominant in case of betamethasone phosphate, a corticosteroid. The presence of alpha, beta unsaturated keto group in betamethasone phosphate is also responsible for its more binding affinity when compared to remedesivir. The presence of F-hydrogen bonding and F-pi interactions and also the presence of alpha, beta unsaturated ketone in case of other two corticosteroid ligands like Fluticasone and Dexamethasone are responsible for showing binding affinity closer to remedesvir, lopinavir and also more binding affinity than other drug candidates docked in the study.