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Molavi Z, Razi S, Mirmotalebisohi SA, Adibi A, Sameni M, Karami F, Niazi V, Niknam Z, Aliashrafi M, Taheri M, Ghafouri-Fard S, Jeibouei S, Mahdian S, Zali H, Ranjbar MM, Yazdani M. Identification of FDA approved drugs against SARS-CoV-2 RNA dependent RNA polymerase (RdRp) and 3-chymotrypsin-like protease (3CLpro), drug repurposing approach. Biomed Pharmacother 2021; 138:111544. [PMID: 34311539 PMCID: PMC8011644 DOI: 10.1016/j.biopha.2021.111544] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2020] [Revised: 03/04/2021] [Accepted: 03/23/2021] [Indexed: 01/08/2023] Open
Abstract
The RNA-dependent RNA polymerase (RdRp) and 3C-like protease (3CLpro) from SARS-CoV-2 play crucial roles in the viral life cycle and are considered the most promising targets for drug discovery against SARS-CoV-2. In this study, FDA-approved drugs were screened to identify the probable anti-RdRp and 3CLpro inhibitors by molecular docking approach. The number of ligands selected from the PubChem database of NCBI for screening was 1760. Ligands were energy minimized using Open Babel. The RdRp and 3CLpro protein sequences were retrieved from the NCBI database. For Homology Modeling predictions, we used the Swiss model server. Their structure was then energetically minimized using SPDB viewer software and visualized in the CHIMERA UCSF software. Molecular dockings were performed using AutoDock Vina, and candidate drugs were selected based on binding affinity (∆G). Hydrogen bonding and hydrophobic interactions between ligands and proteins were visualized using Ligplot and the Discovery Studio Visualizer v3.0 software. Our results showed 58 drugs against RdRp, which had binding energy of − 8.5 or less, and 69 drugs to inhibit the 3CLpro enzyme with a binding energy of − 8.1 or less. Six drugs based on binding energy and number of hydrogen bonds were chosen for the next step of molecular dynamics (MD) simulations to investigate drug-protein interactions (including Nilotinib, Imatinib and dihydroergotamine for 3clpro and Lapatinib, Dexasone and Relategravir for RdRp). Except for Lapatinib, other drugs-complexes were stable during MD simulation. Raltegravir, an anti-HIV drug, was observed to be the best compound against RdRp based on docking binding energy (− 9.5 kcal/mole) and MD results. According to the MD results and binding energy, dihydroergotamine is a suitable candidate for 3clpro inhibition (− 9.6 kcal/mol). These drugs were classified into several categories, including antiviral, antibacterial, anti-inflammatory, anti-allergic, cardiovascular, anticoagulant, BPH and impotence, antipsychotic, antimigraine, anticancer, and so on. The common prescription-indications for some of these medication categories appeared somewhat in line with manifestations of COVID-19. We hope that they can be beneficial for patients with certain specific symptoms of SARS-CoV-2 infection, but they can also probably inhibit viral enzymes. We recommend further experimental evaluations in vitro and in vivo on these FDA-approved drugs to assess their potential antiviral effect on SARS-CoV-2.
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Affiliation(s)
- Zahra Molavi
- Proteomics Research Center, Shahid Beheshti University of Medical Science, Tehran, Iran
| | - Sara Razi
- Proteomics Research Center, Shahid Beheshti University of Medical Science, Tehran, Iran; Department of Biology, Science and Research Branch, Islamic Azad University, Tehran, Iran
| | - Seyed Amir Mirmotalebisohi
- Student Research Committee, Department of Biotechnology, School of Advanced Technologies in Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran; Cellular and Molecular Biology Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Amirjafar Adibi
- Departments of Orthopedics, Faculty of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Marzieh Sameni
- Student Research Committee, Department of Biotechnology, School of Advanced Technologies in Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran; Cellular and Molecular Biology Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Farshid Karami
- Department of Tissue Engineering and Applied Cell Sciences, School of Advanced Technologies in Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Vahid Niazi
- Department of Tissue Engineering and Applied Cell Sciences, School of Advanced Technologies in Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Zahra Niknam
- Proteomics Research Center, Shahid Beheshti University of Medical Science, Tehran, Iran
| | | | - Mohammad Taheri
- Urology and Nephrology Research Cenetr, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Soudeh Ghafouri-Fard
- Department of Medical Genetics, School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Shabnam Jeibouei
- Cellular and Molecular Biology Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran; Department of Tissue Engineering and Applied Cell Sciences, School of Advanced Technologies in Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Soodeh Mahdian
- Department of Cellular and Molecular Biology, Faculty of Biological Sciences, North Tehran Branch, Islamic Azad University, Tehran, Iran
| | - Hakimeh Zali
- Proteomics Research Center, Shahid Beheshti University of Medical Science, Tehran, Iran; Department of Tissue Engineering and Applied Cell Sciences, School of Advanced Technologies in Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
| | - Mohammad Mehdi Ranjbar
- Razi Vaccine and Serum Research Institute, Agricultural Research, Education and Extension Organization (AREEO), Karaj, Iran.
| | - Mohsen Yazdani
- Institute of Biochemistry and Biophysics, Tehran University, Tehran, Iran.
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