Screening of phytochemicals as potent inhibitor of 3-chymotrypsin and papain-like proteases of SARS-CoV2: an in silico approach to combat COVID-19

Abstract

COVID-19 and its causative organism SARS-CoV2 that emerged from Wuhan city, China have paralyzed the world. With no clinically approved drugs, the global health system is struggling to find an effective treatment measure. At this crucial juncture, screening of plant-derived compounds may be an effective strategy to combat COVID-19. The present study investigated the binding affinity of phytocompounds with 3-Chymotrypsin-like (3CLpro) and Papain-like proteases (PLpro) of SARS-CoV2 using in-silico techniques. A total of 32 anti-protease phytocompounds were investigated for the binding affinity to the proteins. Docking was performed in Autodock Vina. Pharmacophore descriptors of best ligands were studied using LigandScout. Molecular dynamics (MD) simulation of apo-protein and ligand-bound complexes was carried out in YASARA software. The druglikeness properties of phytocompounds were studied using ADMETlab. Out of 32 phytochemicals, amentoflavone and gallocatechin gallate showed the best binding affinity to 3CLpro (–9.4 kcal/mol) and PLpro (–8.8 kcal/mol). Phytochemicals such as savinin, theaflavin-3,3-digallate, and kazinol-A also showed strong affinity. MD simulation revealed ligand-induced conformational changes in the protein with decreased surface area and higher stability. The RMSD/F of proteins and ligands showed stability of the protein suggesting the effective binding of the ligand in both the proteins. Both amentoflavone and gallocatechin gallate possess promising druglikeness property. The present study thus suggests that Amentoflavone and Gallocatechin gallate may be potential inhibitors of 3CLpro and PLpro proteins and effective drug candidates for SARS-CoV2. However, the findings of in silico study need to be supported by in vivo studies to establish the exact mode of action. Communicated by Ramaswamy H. Sarma

Efficacy of Phytochemicals Derived from Avicennia officinalis for the Management of COVID-19: A Combined In Silico and Biochemical Study

“…The time step was set to 1.25 fs, and after every 100 ps, the simulation trajectories were saved. The simulation trajectories were analyzed to calculate the root-mean-square deviation (RMSD), root-mean-square fluctuation (RMSF), the radius of gyration (Rg), solvent-accessible surface area (SASA), and hydrogen bonds [ 67 ].…”

Combined use of the hepatitis C drugs and amentoflavone could interfere with binding of the spike glycoprotein of SARS-CoV-2 to ACE2: the results of a molecular simulation study

“…To the best of our knowledge, there are no other MD simulations of paritaprevir–RBD and amentoflavone–RBD complexes. But, there are many stable MD simulations of the amentoflavone complex with the main protease (Ghosh et al, 2020 ; Lokhande et al, 2020 ; Mishra et al, 2020 ; Patil et al, 2021 ; Saravanan et al, 2020 ; Swargiary et al, 2020 ). For paritaprevir and simeprevir, stable MD simulations with the main protease and the uridylate-specific endoribonuclease (NSP15) have been obtained (Alamri et al, 2020 ; Khan, Jha, Amera, et al, 2020 ; Khan, Jha, Singh, et al, 2020 ).…”

“…There are also studies searching for inhibitors for RNA-dependent RNA polymerase (Elfiky, 2020 ), papain-like protease (Ibrahim et al, 2020 ), and RNA endoribonuclease (Khan, Jha, Singh, et al, 2020 ; Sharma et al, 2021 ). In many works, a multitarget approach was used (Albohy et al, 2020 ; Chikhale et al, 2020 ; Khan, Jha, Amera, et al, 2020 ; Maffucci & Contini, 2020 ; Mishra et al, 2021 ; Patil et al, 2021 ; Puttaswamy et al, 2020 ; Rameshkumar et al, 2021 ; Swargiary et al, 2020 ). Despite the large number of drug-repurposing studies against SARS-CoV-2, there is little agreement about the identified hit candidates and almost no experimental validation of the results (Dotolo et al, 2021 ).…”

Chemical Profiles and Pharmacological Properties with in Silico Studies on Elatostema papillosum Wedd

“…The normal simulation time step of 1.25 fs was maintained. The simulation trajectories were saved after every 100-ps interval, and the simulation was run for 50-ns to analyze RMSD and root mean square fluctuation (RMSF) [ 58 , 59 ]. Imipramine HCl, diazepam, diclofenac-Na, and ascorbic acid were denoted as control 1, control 2, control 3, and control 4, respectively.…”