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In silico prediction of potential inhibitors for the main protease of SARS-CoV-2 using molecular docking and dynamics simulation based drug-repurposing.
Kumar, Yogesh; Singh, Harvijay; Patel, Chirag N.
  • Kumar Y; Department of Metabolic & Structural Biology, CSIR-Central Institute of Medicinal & Aromatic Plants, Lucknow 226015, India; Department of Medicine, University Medical Center Hamburg-Eppendorf, 20246 Hamburg, Germany. Electronic address: kumar.yogesh601@gmail.com.
  • Singh H; Department of Biochemistry, Molecular Biology & Biophysics, University of Minnesota, Minneapolis, MN 55455, USA. Electronic address: hsingh@umn.edu.
  • Patel CN; Department of Botany, Bioinformatics & Climate Impacts Management, University School of Sciences, Gujarat University, Navrangpur, Ahmedabad 280009, Gujarat, India.
J Infect Public Health ; 13(9): 1210-1223, 2020 Sep.
Article in English | MEDLINE | ID: covidwho-599724
ABSTRACT

BACKGROUND:

The rapidly enlarging COVID-19 pandemic caused by the novel SARS-corona virus-2 is a global public health emergency of an unprecedented level. Unfortunately no treatment therapy or vaccine is yet available to counter the SARS-CoV-2 infection, which substantiates the need to expand research efforts in this direction. The indispensable function of the main protease in virus replication makes this enzyme a promising target for inhibitors screening and drug discovery to treat novel coronavirus infection. The recently concluded α-ketoamide ligand-bound X-ray crystal structure of SARS-CoV-2 Mpro (PDB ID 6Y2F) from Zhang et al. has revealed the potential inhibitor binding mechanism and the molecular determinants responsible for substrate binding.

METHODS:

For the study, we have targeted the SARS-CoV-2 Mpro for the screening of FDA approved antiviral drugs and carried out molecular docking based virtual screening. Further molecular dynamic simulation studies of the top three selected drugs carried out to investigated for their binding affinity and stability in the SARS-CoV-2 Mpro active site. The phylogenetic analysis was also performed to know the relatedness between the SARS-CoV-2 genomes isolated from different countries.

RESULTS:

The phylogenetic analysis of the SARS-CoV-2 genome reveals that the virus is closely related to the Bat-SL-CoV and does not exhibit any divergence at the genomic level. Molecular docking studies revealed that among the 77 drugs, screened top ten drugs shows good binding affinities, whereas the top three drugs Lopinavir-Ritonavir, Tipranavir, and Raltegravir were undergone for molecular dynamics simulation studies for their conformational stability in the active site of the SARS-CoV-2 Mpro protein.

CONCLUSIONS:

In the present study among the library of FDA approved antiviral drugs, the top three inhibitors Lopinavir-Ritonavir, Tipranavir, and Raltegravir show the best molecular interaction with the main protease of SARS-CoV-2. However, the in-vitro efficacy of the drug molecules screened in this study further needs to be corroborated by carrying out a biochemical and structural investigation.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Antiviral Agents / Pneumonia, Viral / Protease Inhibitors / Cysteine Endopeptidases / Viral Nonstructural Proteins / Coronavirus Infections / Drug Repositioning / Betacoronavirus Type of study: Prognostic study / Randomized controlled trials Topics: Vaccines Limits: Humans Language: English Journal: J Infect Public Health Journal subject: Communicable Diseases / Public Health Year: 2020 Document Type: Article

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Antiviral Agents / Pneumonia, Viral / Protease Inhibitors / Cysteine Endopeptidases / Viral Nonstructural Proteins / Coronavirus Infections / Drug Repositioning / Betacoronavirus Type of study: Prognostic study / Randomized controlled trials Topics: Vaccines Limits: Humans Language: English Journal: J Infect Public Health Journal subject: Communicable Diseases / Public Health Year: 2020 Document Type: Article