Identification of phytocompounds from Houttuynia cordata Thunb. as potential inhibitors for SARS-CoV-2 replication proteins through GC–MS/LC–MS characterization,molecular docking and molecular dynamics simulation

The COVID-19 pandemic caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is a massive viral disease outbreak of international concerns. The present study is mainly intended to identify the bioactive phytocompounds from traditional antiviral herb Houttuynia cordata Thunb. as potential inhibitors for three main replication proteins of SARS-CoV-2, namely Main protease (Mpro), Papain-Like protease (PLpro) and ADP ribose phosphatase (ADRP) which control the replication process. A total of 177 phytocompounds were characterized from H. cordata using GC–MS/LC–MS and they were docked against three SARS-CoV-2 proteins (receptors), namely Mpro, PLpro and ADRP using Epic, LigPrep and Glide module of Schrödinger suite 2020-3. During docking studies, phytocompounds (ligand) 6-Hydroxyondansetron (A104) have demonstrated strong binding affinity toward receptors Mpro (PDB ID 6LU7) and PLpro (PDB ID 7JRN) with G-score of???7.274 and???5.672, respectively, while Quercitrin (A166) also showed strong binding affinity toward ADRP (PDB ID 6W02) with G-score -6.788. Molecular Dynamics Simulation (MDS) performed using Desmond module of Schrödinger suite 2020–3 has demonstrated better stability in the ligand–receptor complexes A104-6LU7 and A166-6W02 within 100 ns than the A104-7JRN complex. The ADME-Tox study performed using SwissADMEserver for pharmacokinetics of the selected phytocompounds 6-Hydroxyondansetron (A104) and Quercitrin (A166) demonstrated that 6-Hydroxyondansetron passes all the required drug discovery rules which can potentially inhibit Mpro and PLpro of SARS-CoV-2 without causing toxicity while Quercitrin demonstrated less drug-like properties but also demonstrated as potential inhibitor for ADRP. Present findings confer opportunities for 6-Hydroxyondansetron and Quercitrin to be developed as new therapeutic drug against COVID-19.

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A posteriori error analysis of a quadratic finite volume method for nonlinear elliptic problems

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