Computational Investigation of Endophytic Fungal (Penicillium citrinum CGJ-C2) Compound and Its In-silico Derivatives for the Inhibition of RNA-Dependent RNA Polymerase of SARS-CoV-2

Abstract

Background: The SARS-CoV2 was responsible for the pandemic situation across the world. SARS-CoV2 is an RNA virus, and its replication depends on RNA Dependent RNA Polymerase (RdRp). Hence, blocking of RdRP would be an alternative strategy to inhibit the virus multiplication without affecting the host physiology. Objective: The current study investigated the inhibitory effect of bioactive compound F3 isolated from P. citrinum CGJ-C2 and its in-silico derivates against RdRp of COVID using computational methods. Methods: Compound F3 and its derivatives were generated computationally, and the crystal structure of RdRp was processed prior to docking. The RdRp and the bioactive compounds were docked using Glide with three levels of precisions. Post-docking MMGBSA analysis and Molecular Dynamic simulations were carried out to study the stability of the docking interactions. Results: Based on the Glide XP score and MMGBSA analysis of fifteen ligands, three leads were selected, compound F3 (-8.655 Kcal/mol), D-1(-8.295 Kcal/mol), and D-14(-8.262 Kcal/mol). These leads (Compound F3, D-1, and D-14) were further evaluated using molecular dynamics (MD) simulation. MD simulations studies showed the stable bonding interaction between LYS500 and ARG569 residues of RdRp with the three lead molecules. Conclusion: Our study highlighted the potential of compounds in terms of binding, interaction stability, and structural integrity. Therefore, these leads can be chosen for further studies in in vitro and in vivo to develop a novel anti-SARS-CoV2 agent with minimal side effects.