Identification of Anti-SARS-CoV-2 Compounds from Food Using QSAR-Based Virtual Screening, Molecular Docking, and Molecular Dynamics Simulation Analysis
Due to the genetic similarity between SARS-CoV-2 and SARS-CoV, the present work endeavored to derive a balanced Quantitative Structure−Activity Relationship (QSAR) model, molecular docking, and molecular dynamics (MD) simulation studies to identify novel molecules having inhibitory potential against...
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-04-01
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| Series: | Pharmaceuticals |
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| Online Access: | https://www.mdpi.com/1424-8247/14/4/357 |
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| author | Magdi E. A. Zaki Sami A. Al-Hussain Vijay H. Masand Siddhartha Akasapu Sumit O. Bajaj Nahed N. E. El-Sayed Arabinda Ghosh Israa Lewaa |
| author_facet | Magdi E. A. Zaki Sami A. Al-Hussain Vijay H. Masand Siddhartha Akasapu Sumit O. Bajaj Nahed N. E. El-Sayed Arabinda Ghosh Israa Lewaa |
| author_sort | Magdi E. A. Zaki |
| collection | DOAJ |
| description | Due to the genetic similarity between SARS-CoV-2 and SARS-CoV, the present work endeavored to derive a balanced Quantitative Structure−Activity Relationship (QSAR) model, molecular docking, and molecular dynamics (MD) simulation studies to identify novel molecules having inhibitory potential against the main protease (Mpro) of SARS-CoV-2. The QSAR analysis developed on multivariate GA–MLR (Genetic Algorithm–Multilinear Regression) model with acceptable statistical performance (R<sup>2</sup> = 0.898, Q<sup>2</sup>loo = 0.859, etc.). QSAR analysis attributed the good correlation with different types of atoms like non-ring Carbons and Nitrogens, amide Nitrogen, sp<sup>2</sup>-hybridized Carbons, etc. Thus, the QSAR model has a good balance of qualitative and quantitative requirements (balanced QSAR model) and satisfies the Organisation for Economic Co-operation and Development (OECD) guidelines. After that, a QSAR-based virtual screening of 26,467 food compounds and 360 heterocyclic variants of molecule <b>1</b> (benzotriazole–indole hybrid molecule) helped to identify promising hits. Furthermore, the molecular docking and molecular dynamics (MD) simulations of Mpro with molecule <b>1</b> recognized the structural motifs with significant stability. Molecular docking and QSAR provided consensus and complementary results. The validated analyses are capable of optimizing a drug/lead candidate for better inhibitory activity against the main protease of SARS-CoV-2. |
| first_indexed | 2024-03-10T12:23:00Z |
| format | Article |
| id | doaj.art-397d20ef4e644a36999074121dcf9e4e |
| institution | Directory Open Access Journal |
| issn | 1424-8247 |
| language | English |
| last_indexed | 2024-03-10T12:23:00Z |
| publishDate | 2021-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Pharmaceuticals |
| spelling | doaj.art-397d20ef4e644a36999074121dcf9e4e2023-11-21T15:19:49ZengMDPI AGPharmaceuticals1424-82472021-04-0114435710.3390/ph14040357Identification of Anti-SARS-CoV-2 Compounds from Food Using QSAR-Based Virtual Screening, Molecular Docking, and Molecular Dynamics Simulation AnalysisMagdi E. A. Zaki0Sami A. Al-Hussain1Vijay H. Masand2Siddhartha Akasapu3Sumit O. Bajaj4Nahed N. E. El-Sayed5Arabinda Ghosh6Israa Lewaa7Department of Chemistry, Faculty of Science, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh 13318, Saudi ArabiaDepartment of Chemistry, Faculty of Science, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh 13318, Saudi ArabiaDepartment of Chemistry, Vidya Bharati Mahavidyalaya, Amravati, Maharashtra 444 602, IndiaCorden Pharma, Boulder, CO 80301, USACorden Pharma, Boulder, CO 80301, USAEgyptian Drug Authority, Agouza, Giza 35521, EgyptMicrobiology Division, Department of Botany, Gauhati University, Guwahati, Assam 781014, IndiaDepartment of Business Administration, Faculty of Business Administration, Economics and Political Science, British University in Egypt, Cairo 11837, EgyptDue to the genetic similarity between SARS-CoV-2 and SARS-CoV, the present work endeavored to derive a balanced Quantitative Structure−Activity Relationship (QSAR) model, molecular docking, and molecular dynamics (MD) simulation studies to identify novel molecules having inhibitory potential against the main protease (Mpro) of SARS-CoV-2. The QSAR analysis developed on multivariate GA–MLR (Genetic Algorithm–Multilinear Regression) model with acceptable statistical performance (R<sup>2</sup> = 0.898, Q<sup>2</sup>loo = 0.859, etc.). QSAR analysis attributed the good correlation with different types of atoms like non-ring Carbons and Nitrogens, amide Nitrogen, sp<sup>2</sup>-hybridized Carbons, etc. Thus, the QSAR model has a good balance of qualitative and quantitative requirements (balanced QSAR model) and satisfies the Organisation for Economic Co-operation and Development (OECD) guidelines. After that, a QSAR-based virtual screening of 26,467 food compounds and 360 heterocyclic variants of molecule <b>1</b> (benzotriazole–indole hybrid molecule) helped to identify promising hits. Furthermore, the molecular docking and molecular dynamics (MD) simulations of Mpro with molecule <b>1</b> recognized the structural motifs with significant stability. Molecular docking and QSAR provided consensus and complementary results. The validated analyses are capable of optimizing a drug/lead candidate for better inhibitory activity against the main protease of SARS-CoV-2.https://www.mdpi.com/1424-8247/14/4/357SARS-CoVSARS-CoV-2COVID-19QSARmolecular dockingQSAR-based virtual screening |
| spellingShingle | Magdi E. A. Zaki Sami A. Al-Hussain Vijay H. Masand Siddhartha Akasapu Sumit O. Bajaj Nahed N. E. El-Sayed Arabinda Ghosh Israa Lewaa Identification of Anti-SARS-CoV-2 Compounds from Food Using QSAR-Based Virtual Screening, Molecular Docking, and Molecular Dynamics Simulation Analysis Pharmaceuticals SARS-CoV SARS-CoV-2 COVID-19 QSAR molecular docking QSAR-based virtual screening |
| title | Identification of Anti-SARS-CoV-2 Compounds from Food Using QSAR-Based Virtual Screening, Molecular Docking, and Molecular Dynamics Simulation Analysis |
| title_full | Identification of Anti-SARS-CoV-2 Compounds from Food Using QSAR-Based Virtual Screening, Molecular Docking, and Molecular Dynamics Simulation Analysis |
| title_fullStr | Identification of Anti-SARS-CoV-2 Compounds from Food Using QSAR-Based Virtual Screening, Molecular Docking, and Molecular Dynamics Simulation Analysis |
| title_full_unstemmed | Identification of Anti-SARS-CoV-2 Compounds from Food Using QSAR-Based Virtual Screening, Molecular Docking, and Molecular Dynamics Simulation Analysis |
| title_short | Identification of Anti-SARS-CoV-2 Compounds from Food Using QSAR-Based Virtual Screening, Molecular Docking, and Molecular Dynamics Simulation Analysis |
| title_sort | identification of anti sars cov 2 compounds from food using qsar based virtual screening molecular docking and molecular dynamics simulation analysis |
| topic | SARS-CoV SARS-CoV-2 COVID-19 QSAR molecular docking QSAR-based virtual screening |
| url | https://www.mdpi.com/1424-8247/14/4/357 |
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