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In Silico Investigation of Phytoconstituents of Medicinal Herb 'Piper Longum' Against SARS-CoV-2 by Molecular Docking and Molecular Dynamics Analysis.
Lakhera, Shradha; Devlal, Kamal; Ghosh, Arabinda; Rana, Meenakshi.
  • Lakhera S; Department of Physics, School of Sciences, Uttarakhand Open University, Haldwani, 263139, Uttarakhand, India.
  • Devlal K; Department of Physics, School of Sciences, Uttarakhand Open University, Haldwani, 263139, Uttarakhand, India.
  • Ghosh A; Microbiology Division, Department of Botany, Guwahati University, Guwahati, 781014, Assam, India.
  • Rana M; Department of Physics, School of Sciences, Uttarakhand Open University, Haldwani, 263139, Uttarakhand, India.
Results Chem ; : 100199, 2021 Sep 24.
Article in English | MEDLINE | ID: covidwho-1433775
ABSTRACT
Unavailability of treatment for the SARS-CoV-2 virus has raised concern among the population worldwide. This has led to many attempts to find alternative options to prevent the infection of the disease, including focusing on vaccines and drugs. The use of natural products and herbal extracts can be a better option in beating the virus and boosting up immunity. In the present paper, we have done a systematic in silico study of papain-like protease of COVID-19 virus with the chemical constituents of herbal plant Piper Longum. Screening of the pharmacokinetic properties is done with thirty-two phytoconstituents of Piper Longum which help us in selecting the most active components of the plant. After selection molecular docking is performed with Aristololactam (C17H11NO4), Fargesin (C21H22O6), l-asarinin (C20H18O6), Lignans Machilin F (C20H22O5), Piperundecalidine (C23H29NO3), and Pluviatilol (C20H20O6). Molecular dynamic (MD) is also performed with the inhibitor-receptor complex which suggest significant inhibition and a stable complex of I-Asarinin with PLpro. Docking scores and simulation results suggest that I-Asarinin can act as a potential drug like candidate against COVID-19.
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Full text: Available Collection: International databases Database: MEDLINE Type of study: Prognostic study / Systematic review/Meta Analysis Topics: Traditional medicine / Vaccines Language: English Journal: Results Chem Year: 2021 Document Type: Article Affiliation country: J.rechem.2021.100199

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Full text: Available Collection: International databases Database: MEDLINE Type of study: Prognostic study / Systematic review/Meta Analysis Topics: Traditional medicine / Vaccines Language: English Journal: Results Chem Year: 2021 Document Type: Article Affiliation country: J.rechem.2021.100199