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Receptor-Based Pharmacophore Modeling in the Search for Natural Products for COVID-19 Mpro.
Saeed, Mohd; Saeed, Amir; Alam, Md Jahoor; Alreshidi, Mousa.
  • Saeed M; Department of Biology, College of Sciences, University of Ha'il, Hail 2440, Saudi Arabia.
  • Saeed A; Department of Clinical Laboratory Sciences, College of Applied Medical Sciences, University of Ha'il, Hail 2440, Saudi Arabia.
  • Alam MJ; Department of Biology, College of Sciences, University of Ha'il, Hail 2440, Saudi Arabia.
  • Alreshidi M; Department of Biology, College of Sciences, University of Ha'il, Hail 2440, Saudi Arabia.
Molecules ; 26(6)2021 Mar 11.
Article in English | MEDLINE | ID: covidwho-1190434
ABSTRACT
Considering the urgency of the COVID-19 pandemic, we developed a receptor-based pharmacophore model for identifying FDA-approved drugs and hits from natural products. The COVID-19 main protease (Mpro) was selected for the development of the pharmacophore model. The model consisted of a hydrogen bond acceptor, donor, and hydrophobic features. These features demonstrated good corroboration with a previously reported model that was used to validate the present model, showing an RMSD value of 0.32. The virtual screening was carried out using the ZINC database. A set of 208,000 hits was extracted and filtered using the ligand pharmacophore mapping, applying the lead-like properties. Lipinski's filter and the fit value filter were used to minimize hits to the top 2000. Simultaneous docking was carried out for 200 hits for natural drugs belonging to the FDA-approved drug database. The top 28 hits from these experiments, with promising predicted pharmacodynamic and pharmacokinetic properties, are reported here. To optimize these hits as Mpro inhibitors and potential treatment options for COVID-19, bench work investigations are needed.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Antiviral Agents / Receptors, Drug / Biological Products / COVID-19 Drug Treatment Type of study: Prognostic study Limits: Humans Language: English Journal subject: Biology Year: 2021 Document Type: Article Affiliation country: Molecules26061549

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Antiviral Agents / Receptors, Drug / Biological Products / COVID-19 Drug Treatment Type of study: Prognostic study Limits: Humans Language: English Journal subject: Biology Year: 2021 Document Type: Article Affiliation country: Molecules26061549