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Screening of potent phytochemical inhibitors against SARS-CoV-2 protease and its two Asian mutants.
Muhammad, Ijaz; Rahman, Noor; Niaz, Sadaf; Basharat, Zarrin; Rastrelli, Luca; Jayanthi, Sivaraman; Efferth, Thomas; Khan, Haroon.
  • Muhammad I; Department of Zoology, Abdul Wali Khan University Mardan, 23200, Pakistan.
  • Rahman N; Department of Biochemistry, Abdul Wali Khan University Mardan, 23200, Pakistan.
  • Gul-E-Nayab; Department of Zoology, Abdul Wali Khan University Mardan, 23200, Pakistan.
  • Niaz S; Department of Zoology, Abdul Wali Khan University Mardan, 23200, Pakistan.
  • Basharat Z; Jamil-ur-Rahman Center for Genome Research, PCMD, ICCBS, University of Karachi, Karachi, 75270, Pakistan.
  • Rastrelli L; Dipartimento di Farmacia, University of Salerno, Via Giovanni Paolo II, 84084, Fisciano, SA, Italy.
  • Jayanthi S; Computational Drug Design Lab, School of Bio Sciences and Technology, Vellore Institute of Technology, Vellore, 632014, Tamil Nadu, India.
  • Efferth T; Department of Pharmaceutical Biology, Institute of Pharmaceutical and Biomedical Sciences, Johannes Gutenberg University, Staudinger Weg 5, 55128, Mainz, Germany.
  • Khan H; Department of Pharmacy, Abdul Wali Khan University Mardan, 23200, Pakistan. Electronic address: haroonkhan@awkum.edu.pk.
Comput Biol Med ; 133: 104362, 2021 06.
Article in English | MEDLINE | ID: covidwho-1188438
ABSTRACT

BACKGROUND:

COVID-19, declared a pandemic in March 2020 by the World Health Organization is caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). The virus has already killed more than 2.3 million people worldwide. OBJECT The principal intent of this work was to investigate lead compounds by screening natural product library (NPASS) for possible treatment of COVID-19.

METHODS:

Pharmacophore features were used to screen a large database to get a small dataset for structure-based virtual screening of natural product compounds. In the structure-based screening, molecular docking was performed to find a potent inhibitor molecule against the main protease (Mpro) of SARS-CoV-2 (PDB ID 6Y7M). The predicted lead compound was further subjected to Molecular Dynamics (MD) simulation to check the stability of the leads compound with the evolution of time.

RESULTS:

In pharmacophore-based virtual screening, 2,361 compounds were retained out of 30,927. In the structure-based screening, the lead compounds were filtered based on their docking scores. Among the 2,360 compounds, 12 lead compounds were selected based on their docking score. Kazinol T with NPASS ID NPC474104 showed the highest docking score of -14.355 and passed criteria of Lipinski's drug-like parameters. Monitoring ADMET properties, Kazinol T showed its safety for consumption. Docking of Kazinol T with two Asian mutants (R60C and I152V) showed variations in binding and energy parameters. Normal mode analysis for ligand-bound and unbound form of protease along with its mutants, revealed displacement and correlation parameters for C-alpha atoms. MD simulation results showed that all ligand-protein complexes remained intact and stable in a dynamic environment with negative Gibbs free energy.

CONCLUSIONS:

The natural product Kazinol T was a predicted lead compound against the main protease of SARS-CoV-2 and will be the possible treatment for COVID-19.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: SARS-CoV-2 / COVID-19 Type of study: Prognostic study Limits: Humans Language: English Journal: Comput Biol Med Year: 2021 Document Type: Article Affiliation country: J.compbiomed.2021.104362

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Full text: Available Collection: International databases Database: MEDLINE Main subject: SARS-CoV-2 / COVID-19 Type of study: Prognostic study Limits: Humans Language: English Journal: Comput Biol Med Year: 2021 Document Type: Article Affiliation country: J.compbiomed.2021.104362