The novel coronavirus disease 2019 (COVID-19) was firstly reported from Wuhan city of China found as highly contagious, transmittable and pathogenic viral infection. The World Health Organization declared COVID-19 as a pandemic since its emergence from China. The RNA dependent RNA polymerase (nsp-12) is a complex with nsp-7 and nsp-8 cofactors major constituent of viral replication and RNA synthesis machinery. In current study, the RdRp of virus was selected as a receptor protein for computational drug discovery. Computational homology modelling was done in order to find the hidden secondary structures and structural assessment of viral protein to target them via antiviral drugs. The study based on docking of different phytochemicals to check potential of different plant metabolites against viral replicative proteins. Out of 200 ligands used in this study from different plants the best ten were selected based on drug discovery parameters such as S-score, ligand interactions, hydrophobic interactions and drug likeness. The ten best selected ligands were Verbenalin, Epigallocatechin, Swertisin, Nobiletin, Pinoresinol, Caftaric acid, Hesperetin, Islandicin, Neochlorogenic acid and Sesamin that exploit the potency as antagonist of viral protein. Among binding interactions of all ligands Arg339 centred as the main interacting residue among almost all the ligands. Till now many antiviral agents have shown potency in only mild cases of SARS-CoV-2 but no effective drug has been found for critical pulmonary cases. In clinical trials many broad-spectrum antiviral agents have been still in trail periods of testing against SARS-CoV-2. Till date no effective drug or vaccine has been validated with significant efficacy and potency against the SARS-CoV-2 therefore there is an urgent need to design effective vaccine against nCoV-19 infections.