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Molecular screening of glycyrrhizin-based inhibitors against ACE2 host receptor of SARS-CoV-2.
Ahmad, Sajjad; Waheed, Yasir; Abro, Asma; Abbasi, Sumra Wajid; Ismail, Saba.
  • Ahmad S; Department of Health and Biological Sciences, Abasyn University, Peshawar, 25000, Pakistan.
  • Waheed Y; Foundation University Medical College, Foundation University Islamabad, DHA-I, Islamabad, 44000, Pakistan. yasir.waheed@fui.edu.pk.
  • Abro A; Department of Biotechnology, Faculty of Life Sciences and Informatics, Balochistan University of Information Technology Engineering and Management Sciences, Quetta, Pakistan.
  • Abbasi SW; NUMS Department of Biological Sciences, National University of Medical Sciences, Abid Majeed Rd, The Mall, Rawalpindi, Pakistan.
  • Ismail S; NUMS Department of Biological Sciences, National University of Medical Sciences, Abid Majeed Rd, The Mall, Rawalpindi, Pakistan.
J Mol Model ; 27(7): 206, 2021 Jun 24.
Article in English | MEDLINE | ID: covidwho-1384472
ABSTRACT
The interaction between SARS-CoV-2 Spike protein and angiotensin-converting enzyme 2 (ACE2) is essential to viral attachment and the subsequent fusion process. Interfering with this event represents an attractive avenue for the development of therapeutics and vaccine development. Here, a hybrid approach of ligand- and structure-based virtual screening techniques were employed to disclose similar analogues of a reported antiviral phytochemical, glycyrrhizin, targeting the blockade of ACE2 interaction with the SARS-CoV-2 Spike. A ligand-based similarity search using a stringent cut-off revealed 40 FDA-approved compounds in DrugBank. These filtered hits were screened against ACE2 using a blind docking approach to determine the natural binding tendency of the compounds with ACE2. Three compounds, deslanoside, digitoxin, and digoxin, were reported to show strong binding with ACE2. These compounds bind at the H1-H2 binding pocket, in a manner similar to that of glycyrrhizin which was used as a control. To achieve consistency in the docking results, docking calculations were performed via two sets of docking software that predicted binding energy as ACE2-Deslanoside (AutoDock, -10.3 kcal/mol and DockThor, -9.53 kcal/mol), ACE2-Digitoxin (AutoDock, -10.6 kcal/mol and DockThor, -8.84 kcal/mol), and ACE2-Digoxin (AutoDock, -10.6 kcal/mol and DockThor, -8.81 kcal/mol). The docking results were validated by running molecular simulations in aqueous solution that demonstrated the stability of ACE2 with no major conformational changes in the ligand original binding mode (~ 2 Å average RMSD). Binding interactions remained quite stable with an increased potential for getting stronger as the simulation proceeded. MMGB/PBSA binding free energies were also estimated and these supported the high stability of the complexes compared to the control (~ -50 kcal/mol net MMGB/PBSA binding energy versus ~ -30 kcal/mol). Collectively, the data demonstrated that the compounds shortlisted in this study might be subjected to experimental evaluation to uncover their real blockade capacity of SARS-CoV-2 host ACE2 receptor.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Antiviral Agents / Receptors, Virus / Angiotensin-Converting Enzyme Inhibitors / Glycyrrhizic Acid / Virus Internalization / Spike Glycoprotein, Coronavirus / Angiotensin-Converting Enzyme 2 / SARS-CoV-2 / COVID-19 Drug Treatment Type of study: Experimental Studies / Prognostic study Topics: Vaccines Limits: Animals / Humans Language: English Journal: J Mol Model Journal subject: Molecular Biology Year: 2021 Document Type: Article Affiliation country: S00894-021-04816-Y

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Antiviral Agents / Receptors, Virus / Angiotensin-Converting Enzyme Inhibitors / Glycyrrhizic Acid / Virus Internalization / Spike Glycoprotein, Coronavirus / Angiotensin-Converting Enzyme 2 / SARS-CoV-2 / COVID-19 Drug Treatment Type of study: Experimental Studies / Prognostic study Topics: Vaccines Limits: Animals / Humans Language: English Journal: J Mol Model Journal subject: Molecular Biology Year: 2021 Document Type: Article Affiliation country: S00894-021-04816-Y