| Title: | Natural flavonoid pectolinarin computationally targeted as a promising drug candidate against SARS-CoV-2 |
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| Authors: | ID Rani, Mukta (Author)
ID Chouhan, Raghuraj S., Institut "Jožef Stefan" (Author)
ID Singh, Rajesh K. (Author), et al. |
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| Files: |  URL - Source URL, visit https://www.sciencedirect.com/science/article/pii/S2665928X23000260?via%3Dihub
 PDF - Presentation file, download (5,57 MB)
MD5: 8DFF7BB52BEA7B728D6D2BA95ABF3DCE
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| Language: | English |
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| Typology: | 1.01 - Original Scientific Article |
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| Organization: |  IJS - Jožef Stefan Institute
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| Abstract: | Coronavirus disease-2019 (COVID-19) has become a global pandemic, necessitating the development of new medicines. In this investigation, we identified potential natural flavonoids and compared their inhibitory activity against spike glycoprotein, which is a target of SARS-CoV-2 and SARS-CoV. The target site for the interaction of new inhibitors for the treatment of SARS-CoV-2 has 82% sequence identity and the remaining 18% dissimilarities in RBD S1-subunit, S2-subunit, and 2.5% others. Molecular docking was employed to analyse the various binding processes used by each ligand in a library of 85 natural flavonoids that act as anti-viral medications and FDA authorised treatments for COVID-19. In the binding pocket of the target active site, remdesivir has less binding interaction than pectolinarin, according to the docking analysis. Pectolinarin is a natural flavonoid isolated from Cirsiumsetidensas that has anti-cancer, vasorelaxant, anti-inflammatory, hepatoprotective, anti-diabetic, anti-microbial, and anti-oxidant properties. The S-glycoprotein RBD region (330–583) is inhibited by kaempferol, rhoifolin, and herbacetin, but the S2 subunit (686–1270) is inhibited by pectolinarin, morin, and remdesivir. MD simulation analysis of S-glycoprotein of SARS-CoV-2 with pectolinarin complex at 100ns based on high dock-score. Finally, ADMET analysis was used to validate the proposed compounds with the highest binding energy. |
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| Keywords: | coronaviruses, SARS-CoV-2, S-glycoproteins, computational analysis |
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| Publication status: | Published |
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| Publication version: | Version of Record |
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| Submitted for review: | 19.09.2023 |
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| Article acceptance date: | 11.12.2023 |
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| Publication date: | 15.12.2023 |
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| Publisher: | Elsevier |
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| Year of publishing: | 2024 |
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| Number of pages: | str. 1-12 |
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| Numbering: | Vol. ,7 [article no.] 100120 |
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| Source: | Nizozemska |
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| PID: | 20.500.12556/DiRROS-24734  |
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| UDC: | 577 |
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| ISSN on article: | 2665-928X |
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| DOI: | 10.1016/j.crstbi.2023.100120 |
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| COBISS.SI-ID: | 178467075 |
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| Copyright: | © 2023 The Authors. |
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| Note: | Nasl. z nasl. zaslona;
Opis vira z dne 20. 12. 2023;
Soavtor iz Slovenije: R. S. Chouhan;
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| Publication date in DiRROS: | 16.12.2025 |
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| Views: | 8 |
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| Downloads: | 9 |
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