In Silico Screening of the DrugBank Database to Search for Possible Drugs against SARS-CoV-2
Coronavirus desease 2019 (COVID-19) is responsible for more than 1.80 M deaths worldwide. A Quantitative Structure-Activity Relationships (QSAR) model is developed based on experimental pIC<sub>50</sub> values reported for a structurally diverse dataset. A robust model with only five des...
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-02-01
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| Series: | Molecules |
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| Online Access: | https://www.mdpi.com/1420-3049/26/4/1100 |
| _version_ | 1797395984599220224 |
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| author | Sebastián A. Cuesta José R. Mora Edgar A. Márquez |
| author_facet | Sebastián A. Cuesta José R. Mora Edgar A. Márquez |
| author_sort | Sebastián A. Cuesta |
| collection | DOAJ |
| description | Coronavirus desease 2019 (COVID-19) is responsible for more than 1.80 M deaths worldwide. A Quantitative Structure-Activity Relationships (QSAR) model is developed based on experimental pIC<sub>50</sub> values reported for a structurally diverse dataset. A robust model with only five descriptors is found, with values of R<sup>2</sup> = 0.897, Q<sup>2</sup><sub>LOO</sub> = 0.854, and Q<sup>2</sup><sub>ext</sub> = 0.876 and complying with all the parameters established in the validation Tropsha’s test. The analysis of the applicability domain (AD) reveals coverage of about 90% for the external test set. Docking and molecular dynamic analysis are performed on the three most relevant biological targets for SARS-CoV-2: main protease, papain-like protease, and RNA-dependent RNA polymerase. A screening of the DrugBank database is executed, predicting the pIC<sub>50</sub> value of 6664 drugs, which are IN the AD of the model (coverage = 79%). Fifty-seven possible potent anti-COVID-19 candidates with pIC<sub>50</sub> values > 6.6 are identified, and based on a pharmacophore modelling analysis, four compounds of this set can be suggested as potent candidates to be potential inhibitors of SARS-CoV-2. Finally, the biological activity of the compounds was related to the frontier molecular orbitals shapes. |
| first_indexed | 2024-03-09T00:43:45Z |
| format | Article |
| id | doaj.art-75738541e73e4517b80fffa37afd2d1d |
| institution | Directory Open Access Journal |
| issn | 1420-3049 |
| language | English |
| last_indexed | 2024-03-09T00:43:45Z |
| publishDate | 2021-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Molecules |
| spelling | doaj.art-75738541e73e4517b80fffa37afd2d1d2023-12-11T17:39:32ZengMDPI AGMolecules1420-30492021-02-01264110010.3390/molecules26041100In Silico Screening of the DrugBank Database to Search for Possible Drugs against SARS-CoV-2Sebastián A. Cuesta0José R. Mora1Edgar A. Márquez2Grupo de Química Computacional y Teórica (QCT-USFQ), Departamento de Ingeniería Química, Colegio Politécnico, Universidad San Francisco de Quito, Diego de Robles y Vía Interoceánica, Quito 170901, EcuadorGrupo de Química Computacional y Teórica (QCT-USFQ), Departamento de Ingeniería Química, Colegio Politécnico, Universidad San Francisco de Quito, Diego de Robles y Vía Interoceánica, Quito 170901, EcuadorGrupo de Investigaciones en Química y Biología, Departamento de Química y Biología, Facultad de Ciencias Exactas, Universidad del Norte, Carrera 51B, Km 5, vía Puerto Colombia, Barranquilla 081007, ColombiaCoronavirus desease 2019 (COVID-19) is responsible for more than 1.80 M deaths worldwide. A Quantitative Structure-Activity Relationships (QSAR) model is developed based on experimental pIC<sub>50</sub> values reported for a structurally diverse dataset. A robust model with only five descriptors is found, with values of R<sup>2</sup> = 0.897, Q<sup>2</sup><sub>LOO</sub> = 0.854, and Q<sup>2</sup><sub>ext</sub> = 0.876 and complying with all the parameters established in the validation Tropsha’s test. The analysis of the applicability domain (AD) reveals coverage of about 90% for the external test set. Docking and molecular dynamic analysis are performed on the three most relevant biological targets for SARS-CoV-2: main protease, papain-like protease, and RNA-dependent RNA polymerase. A screening of the DrugBank database is executed, predicting the pIC<sub>50</sub> value of 6664 drugs, which are IN the AD of the model (coverage = 79%). Fifty-seven possible potent anti-COVID-19 candidates with pIC<sub>50</sub> values > 6.6 are identified, and based on a pharmacophore modelling analysis, four compounds of this set can be suggested as potent candidates to be potential inhibitors of SARS-CoV-2. Finally, the biological activity of the compounds was related to the frontier molecular orbitals shapes.https://www.mdpi.com/1420-3049/26/4/1100SARS-CoV-2QSARdocking analysisDrugBankmolecular dynamics |
| spellingShingle | Sebastián A. Cuesta José R. Mora Edgar A. Márquez In Silico Screening of the DrugBank Database to Search for Possible Drugs against SARS-CoV-2 Molecules SARS-CoV-2 QSAR docking analysis DrugBank molecular dynamics |
| title | In Silico Screening of the DrugBank Database to Search for Possible Drugs against SARS-CoV-2 |
| title_full | In Silico Screening of the DrugBank Database to Search for Possible Drugs against SARS-CoV-2 |
| title_fullStr | In Silico Screening of the DrugBank Database to Search for Possible Drugs against SARS-CoV-2 |
| title_full_unstemmed | In Silico Screening of the DrugBank Database to Search for Possible Drugs against SARS-CoV-2 |
| title_short | In Silico Screening of the DrugBank Database to Search for Possible Drugs against SARS-CoV-2 |
| title_sort | in silico screening of the drugbank database to search for possible drugs against sars cov 2 |
| topic | SARS-CoV-2 QSAR docking analysis DrugBank molecular dynamics |
| url | https://www.mdpi.com/1420-3049/26/4/1100 |
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