Computational Screening of Plant-Derived Natural Products against SARS-CoV-2 Variants
The present study explores the efficacy of plant-derived natural products (PDNPs) against spike glycoproteins (S-glycoprotein) of SARS-CoV-2 variants using molecular docking, ADMET, molecular dynamics (MD) simulation and density-functional theory (DFT) analysis. In all, 100 PDNPs were screened again...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-11-01
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| Series: | Future Pharmacology |
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| Online Access: | https://www.mdpi.com/2673-9879/2/4/34 |
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| author | Waseem Ahmad Ansari Mohd Aamish Khan Fahmina Rizvi Kajim Ali Mohd Kamil Hussain Mohammad Saquib Mohammad Faheem Khan |
| author_facet | Waseem Ahmad Ansari Mohd Aamish Khan Fahmina Rizvi Kajim Ali Mohd Kamil Hussain Mohammad Saquib Mohammad Faheem Khan |
| author_sort | Waseem Ahmad Ansari |
| collection | DOAJ |
| description | The present study explores the efficacy of plant-derived natural products (PDNPs) against spike glycoproteins (S-glycoprotein) of SARS-CoV-2 variants using molecular docking, ADMET, molecular dynamics (MD) simulation and density-functional theory (DFT) analysis. In all, 100 PDNPs were screened against spike glycoprotein of SARS-CoV-2 variants, namely alpha (B.1.1.17), beta (B.1.351), delta (B.1.617), gamma (P.1) and omicron (B.1.1.529). Results showed that rutin, EGCG, hesperidin, withanolide G, rosmarinic acid, diosmetin, myricetin, epicatechin and quercetin were the top hit compounds against each of the SARS-CoV-2 variants. The most active compounds, rutin, hesperidin, EGCG and rosmarinic acid gave binding scores of −10.2, −8.1, −8.9, −8.3 and −9.2 kcal/mol, against omicron, delta, alpha, beta and gamma variants, respectively. Further, the stability of docked complexes was confirmed by the analysis of molecular descriptors (RMSD, RMSF, SASA, Rg and H-bonds) in molecular dynamic simulation analysis. Moreover, the physiochemical properties and drug-likeness of the tested compounds showed that they have no toxicity or carcinogenicity and may be used as druggable targets. In addition, the DFT study revealed the higher activity of the tested compounds against the target proteins. This led us to conclude that rutin, hesperidin, EGCG and rosmarinic acid are good candidates to target the S-glycoproteins of SARS-CoV-2 variants. Further, in vivo and clinical studies needed to develop them as drug leads against existing or new SARS-CoV-2 variants are currently underway in our laboratory. |
| first_indexed | 2024-03-09T16:33:13Z |
| format | Article |
| id | doaj.art-51799a5a00cf4b9aa856bf936953d6ce |
| institution | Directory Open Access Journal |
| issn | 2673-9879 |
| language | English |
| last_indexed | 2024-03-09T16:33:13Z |
| publishDate | 2022-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Future Pharmacology |
| spelling | doaj.art-51799a5a00cf4b9aa856bf936953d6ce2023-11-24T14:59:05ZengMDPI AGFuture Pharmacology2673-98792022-11-012455857810.3390/futurepharmacol2040034Computational Screening of Plant-Derived Natural Products against SARS-CoV-2 VariantsWaseem Ahmad Ansari0Mohd Aamish Khan1Fahmina Rizvi2Kajim Ali3Mohd Kamil Hussain4Mohammad Saquib5Mohammad Faheem Khan6Department of Biotechnology, Era University, Sarfarazganj, Hardoi Road, Lucknow 226003, IndiaDepartment of Biotechnology, Era University, Sarfarazganj, Hardoi Road, Lucknow 226003, IndiaDepartment of Biotechnology, Era University, Sarfarazganj, Hardoi Road, Lucknow 226003, IndiaDepartment of Biotechnology, Era University, Sarfarazganj, Hardoi Road, Lucknow 226003, IndiaDepartment of Chemistry, Govt. Raza P.G. College, Rampur, M. J. P. Rohilkhand University, Bareilly 244901, IndiaDepartment of Chemistry, University of Allahabad, Prayagraj 211002, IndiaDepartment of Biotechnology, Era University, Sarfarazganj, Hardoi Road, Lucknow 226003, IndiaThe present study explores the efficacy of plant-derived natural products (PDNPs) against spike glycoproteins (S-glycoprotein) of SARS-CoV-2 variants using molecular docking, ADMET, molecular dynamics (MD) simulation and density-functional theory (DFT) analysis. In all, 100 PDNPs were screened against spike glycoprotein of SARS-CoV-2 variants, namely alpha (B.1.1.17), beta (B.1.351), delta (B.1.617), gamma (P.1) and omicron (B.1.1.529). Results showed that rutin, EGCG, hesperidin, withanolide G, rosmarinic acid, diosmetin, myricetin, epicatechin and quercetin were the top hit compounds against each of the SARS-CoV-2 variants. The most active compounds, rutin, hesperidin, EGCG and rosmarinic acid gave binding scores of −10.2, −8.1, −8.9, −8.3 and −9.2 kcal/mol, against omicron, delta, alpha, beta and gamma variants, respectively. Further, the stability of docked complexes was confirmed by the analysis of molecular descriptors (RMSD, RMSF, SASA, Rg and H-bonds) in molecular dynamic simulation analysis. Moreover, the physiochemical properties and drug-likeness of the tested compounds showed that they have no toxicity or carcinogenicity and may be used as druggable targets. In addition, the DFT study revealed the higher activity of the tested compounds against the target proteins. This led us to conclude that rutin, hesperidin, EGCG and rosmarinic acid are good candidates to target the S-glycoproteins of SARS-CoV-2 variants. Further, in vivo and clinical studies needed to develop them as drug leads against existing or new SARS-CoV-2 variants are currently underway in our laboratory.https://www.mdpi.com/2673-9879/2/4/34SARS-CoV-2 variantsplant-derived natural productsmolecular dockingmolecular dynamic simulationDensity-Functional Theory |
| spellingShingle | Waseem Ahmad Ansari Mohd Aamish Khan Fahmina Rizvi Kajim Ali Mohd Kamil Hussain Mohammad Saquib Mohammad Faheem Khan Computational Screening of Plant-Derived Natural Products against SARS-CoV-2 Variants Future Pharmacology SARS-CoV-2 variants plant-derived natural products molecular docking molecular dynamic simulation Density-Functional Theory |
| title | Computational Screening of Plant-Derived Natural Products against SARS-CoV-2 Variants |
| title_full | Computational Screening of Plant-Derived Natural Products against SARS-CoV-2 Variants |
| title_fullStr | Computational Screening of Plant-Derived Natural Products against SARS-CoV-2 Variants |
| title_full_unstemmed | Computational Screening of Plant-Derived Natural Products against SARS-CoV-2 Variants |
| title_short | Computational Screening of Plant-Derived Natural Products against SARS-CoV-2 Variants |
| title_sort | computational screening of plant derived natural products against sars cov 2 variants |
| topic | SARS-CoV-2 variants plant-derived natural products molecular docking molecular dynamic simulation Density-Functional Theory |
| url | https://www.mdpi.com/2673-9879/2/4/34 |
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