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Identifying non-nucleoside inhibitors of RNA-dependent RNA-polymerase of SARS-CoV-2 through per-residue energy decomposition-based pharmacophore modeling, molecular docking, and molecular dynamics simulation by Shahkaar Aziz; Muhammad Waqas; Tapan Kumar Mohanta; Sobia Ahsan Halim; Aqib Iqbal; Amjad Ali; Asaad Khalid; Ashraf N. Abdalla; Ajmal Khan; Ahmed Al-Harrasi is a Medicine article available to read on EtoBox.
What is Identifying non-nucleoside inhibitors of RNA-dependent RNA-polymerase of SARS-CoV-2 through per-residue energy decomposition-based pharmacophore modeling, molecular docking, and molecular dynamics simulation about?
Background and Objective The current coronavirus disease-2019 (COVID-19) pandemic has triggered a worldwide health and economic crisis. The severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) causes the disease and completes its life cycle using the RNA-dependent RNA-polymerase (RdRp) enzyme, a prominent target for antivirals. In this study, we have computationally screened ∼690 million compounds from the ZINC20 database and 11,698 small molecule inhibitors from DrugBank to find existing and novel non-nucleoside inhibitors for SARS-CoV-2 RdRp. Methods Herein, a combination of the structure-based pharmacophore modeling and hybrid virtual screening methods, including per-residue energy decomposition-based pharmacophore screening, molecular docking, pharmacokinetics, and toxicity evaluation were employed to retrieve novel as well as existing RdRp non-nucleoside inhibitors from large chemical databases. Besides, molecular dynamics simulation and Molecular Mechanics/Generalized Born Surface Area (MM/GBSA) method were used to investigate the binding stability and calculate the binding free energy of RdRp–inhibitor complexes. Results Based on docking scores and significant bindin
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- Author
- Shahkaar Aziz; Muhammad Waqas; Tapan Kumar Mohanta; Sobia Ahsan Halim; Aqib Iqbal; Amjad Ali; Asaad Khalid; Ashraf N. Abdalla; Ajmal Khan; Ahmed Al-Harrasi
- Publisher
- Elsevier BV
- Published
- 2023
- Language
- EN
- Field
- Medicine (Health Sciences)