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المؤلفMathew, Shilu Mathew
المؤلفBenslimane, Fatiha
المؤلفAlthani, Asmaa A.
المؤلفYassine, Hadi M.
تاريخ الإتاحة2024-07-09T10:21:03Z
تاريخ النشر2021-03-12
اسم المنشورQatar Medical Journal
المعرّفhttp://dx.doi.org/10.5339/QMJ.2021.12
الاقتباسMathew, S. M., Benslimane, F., Althani, A. A., & Yassine, H. M. (2021). Identification of potential natural inhibitors of the receptor-binding domain of the SARS-CoV-2 spike protein using a computational docking approach. Qatar medical journal, 2021(1), 12.
الرقم المعياري الدولي للكتاب0253-8253
معرّف المصادر الموحدhttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85104282377&origin=inward
معرّف المصادر الموحدhttp://hdl.handle.net/10576/56526
الملخصBackground: The novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the only zoonotic-origin CoV to reach the pandemic stage, to which neither an effective vaccine nor a specific therapy is available. The spike glycoprotein harbors the receptor-binding domain (RBD) that mediates the virus's entry to host cells. This study aimed to identify novel inhibitors that target the spike protein's RBD domain through computational screening of chemical and natural compounds. Method: The spike protein was modeled from the recently reported electron microscopy protein structure (PDB ID: 6VSB) and the previously described SARS-CoV protein structure (PDB ID: 6ACD and 6ACJ). Virtual lab bench CLC Drug Discovery was used to computationally screen for potential inhibitory effects of currently prescribed drugs (n ¼22), natural antiviral drugs (n ¼100), and natural compounds (n ¼35032). Quantitative Structure-Activity Relationship (QSAR) studies were also performed to determine the leading binders known for their antiviral activity. Results: Among the drugs currently used to treat SARS-CoV2, hydroxychloroquine and favipiravir were identified as the best binders with an average of four H-bonds, with a binding affinity of 236.66 kcal/mol and a minimum interaction energy of 26.63 kcal/mol. In an evaluation of antiviral compounds, fosamprenavir and abacavir showed effective binding of five H-bonds, with an average binding affinity of 218.75 kcal.mol21 and minimum interaction energy of 23.57 kcal/mol. Furthermore, screening of 100 natural antiviral compounds predicted potential binding modes of glycyrrhizin, nepritin, punicalagin, epigallocatechin gallate, and theaflavin (average binding affinity of 249.88 kcal/mol and minimum interaction energy of 24.35 kcal/mol). Additionally, the study reports a list of 25 natural compounds that showed effective binding with an improved average binding affinity of 251.46 kcal/mol. Conclusions: Using computational screening, we identified potential SARS-CoV-2 S glycoprotein inhibitors that bind to the RBD region. Using structure-based design and combination-based drug therapy, the identified molecules could be used to generate anti-SARS-CoV-2 drug candidates.
راعي المشروعThis study was supported by funding from Qatar University, grant # QUCG-BRC-20/21-1.
اللغةen
الناشرHBKU Press
الموضوعAntiviral drugs
Computational docking
Molecular docking
SARS-CoV-2
Spike protein
Virtual screening
العنوانIdentification of potential natural inhibitors of the receptor-binding domain of the SARS-CoV-2 spike protein using a computational docking approach
النوعArticle
رقم العدد1
رقم المجلد2021
ESSN2227-0426
dc.accessType Open Access


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