In silico identification of novel SARS-COV-2 2'-O-methyltransferase (nsp16) inhibitors: structure-based virtual screening, molecular dynamics simulation and MM-PBSA approaches.

Item request has been placed! ×
Item request cannot be made. ×
loading   Processing Request
Read Online Read More Add to Saved list
  • Additional Information
    • Source:
      Publisher: Taylor & Francis Country of Publication: England NLM ID: 101150203 Publication Model: Print Cited Medium: Internet ISSN: 1475-6374 (Electronic) Linking ISSN: 14756366 NLM ISO Abbreviation: J Enzyme Inhib Med Chem Subsets: MEDLINE
    • Publication Information:
      Original Publication: Basingstoke, UK : Taylor & Francis, c2002-
    • Subject Terms:
      Antiviral Agents/*chemistry ; Enzyme Inhibitors/*chemistry ; SARS-CoV-2/*enzymology ; Viral Nonstructural Proteins/*chemistry; Adenosine/analogs & derivatives ; Adenosine/chemistry ; Adenosine/metabolism ; Antiviral Agents/metabolism ; Binding Sites ; Crystallography, X-Ray ; Databases, Pharmaceutical ; Databases, Protein ; Drug Stability ; Enzyme Inhibitors/metabolism ; High-Throughput Screening Assays ; Humans ; Kinetics ; Methyltransferases ; Molecular Docking Simulation ; Molecular Dynamics Simulation ; Protein Binding ; Protein Conformation, alpha-Helical ; Protein Conformation, beta-Strand ; Protein Interaction Domains and Motifs ; SARS-CoV-2/chemistry ; Thermodynamics ; Viral Nonstructural Proteins/antagonists & inhibitors
    • Abstract:
      The novel coronavirus disease COVID-19, caused by the virus SARS CoV-2, has exerted a significant unprecedented economic and medical crisis, in addition to its impact on the daily life and health care systems all over the world. Regrettably, no vaccines or drugs are currently available for this new critical emerging human disease. Joining the global fight against COVID-19, in this study we aim at identifying a potential novel inhibitor for SARS COV-2 2'-O-methyltransferase (nsp16) which is one of the most attractive targets in the virus life cycle, responsible for the viral RNA protection via a cap formation process. Firstly, nsp16 enzyme bound to Sinefungin was retrieved from the protein data bank (PDB ID: 6WKQ), then, a 3D pharmacophore model was constructed to be applied to screen 48 Million drug-like compounds of the Zinc database. This resulted in only 24 compounds which were subsequently docked into the enzyme. The best four score-ordered hits from the docking outcome exhibited better scores compared to Sinefungin. Finally, three molecular dynamics (MD) simulation experiments for 150 ns were carried out as a refinement step for our proposed approach. The MD and MM-PBSA outputs revealed compound 11 as the best potential nsp16 inhibitor herein identified, as it displayed a better stability and average binding free energy for the ligand-enzyme complex compared to Sinefungin.
    • References:
      J Comput Chem. 2005 Dec;26(16):1668-88. (PMID: 16200636)
      Mutat Res. 2020 Jan - Apr;819-820:111687. (PMID: 31968288)
      Cell Res. 2020 Mar;30(3):269-271. (PMID: 32020029)
      Biochim Biophys Acta Mol Basis Dis. 2020 Oct 1;1866(10):165878. (PMID: 32544429)
      Nat Rev Drug Discov. 2020 Mar;19(3):149-150. (PMID: 32127666)
      J Biomol Struct Dyn. 2020 Jun 24;:1-13. (PMID: 32579061)
      Virol Sin. 2016 Feb;31(1):3-11. (PMID: 26847650)
      J Chem Inf Model. 2014 Jul 28;54(7):1951-62. (PMID: 24850022)
      Arch Med Sci. 2020 Apr 17;16(3):508-518. (PMID: 32399096)
      Lancet. 2020 Feb 15;395(10223):514-523. (PMID: 31986261)
      J Biomol Struct Dyn. 2018 May;36(7):1713-1727. (PMID: 28531373)
      Nat Commun. 2020 Jul 24;11(1):3717. (PMID: 32709887)
      J Comput Chem. 2009 Dec;30(16):2785-91. (PMID: 19399780)
      Nature. 2010 Nov 18;468(7322):452-6. (PMID: 21085181)
      J Comput Chem. 2005 Dec;26(16):1781-802. (PMID: 16222654)
      PLoS One. 2016 Feb 04;11(2):e0148181. (PMID: 26845440)
      Genes Dev. 2005 Jun 15;19(12):1444-54. (PMID: 15933069)
      J Chem Inf Model. 2014 Mar 24;54(3):902-12. (PMID: 24555519)
      Curr Top Med Chem. 2008;8(18):1555-72. (PMID: 19075767)
      J Biomol Struct Dyn. 2020 May 20;:1-10. (PMID: 32397940)
      J Comput Chem. 2010 Jan 30;31(2):455-61. (PMID: 19499576)
      Pharmgenomics Pers Med. 2014 Aug 14;7:241-9. (PMID: 25206310)
      Nucleic Acids Res. 2016 Sep 19;44(16):7511-26. (PMID: 27317694)
      J Biomol Struct Dyn. 2020 Apr 30;:1-10. (PMID: 32306836)
      J Phys Chem B. 2009 Mar 5;113(9):2748-63. (PMID: 19708111)
      Elife. 2019 May 13;8:. (PMID: 31081496)
      Front Chem. 2020 Oct 30;8:584894. (PMID: 33195080)
      Front Microbiol. 2020 Jul 14;11:1723. (PMID: 32765482)
      J Biomol Struct Dyn. 2020 Sep;38(15):4521-4535. (PMID: 31647392)
      Clin Pharmacokinet. 2011 Apr;50(4):229-44. (PMID: 21348537)
    • Contributed Indexing:
      Keywords: 3D pharmacophore; COVID-19 therapies; MM-PBSA calculations; SARS COV-2 2′-O-methyltransferase (nsp16) Inhibitor; molecular dynamics
    • Accession Number:
      0 (Antiviral Agents)
      0 (Enzyme Inhibitors)
      0 (NSP16 protein, SARS-CoV-2)
      0 (Viral Nonstructural Proteins)
      EC 2.1.1.- (Methyltransferases)
      K72T3FS567 (Adenosine)
      W2U467CIIL (sinefungin)
    • Publication Date:
      Date Created: 20210309 Date Completed: 20210319 Latest Revision: 20211204
    • Publication Date:
      20240105
    • Accession Number:
      PMC7946047
    • Accession Number:
      10.1080/14756366.2021.1885396
    • Accession Number:
      33685335