Article ; Online: In Silico Design of New Dual Inhibitors of SARS-CoV-2 M PRO through Ligand- and Structure-Based Methods
International Journal of Molecular Sciences, Vol 24, Iss 8377, p
2023 Volume 8377
Abstract: The viral main protease is one of the most attractive targets among all key enzymes involved in the life cycle of SARS-CoV-2. Considering its mechanism of action, both the catalytic and dimerization regions could represent crucial sites for modulating ... ...
| Abstract | The viral main protease is one of the most attractive targets among all key enzymes involved in the life cycle of SARS-CoV-2. Considering its mechanism of action, both the catalytic and dimerization regions could represent crucial sites for modulating its activity. Dual-binding the SARS-CoV-2 main protease inhibitors could arrest the replication process of the virus by simultaneously preventing dimerization and proteolytic activity. To this aim, in the present work, we identified two series’ of small molecules with a significant affinity for SARS-CoV-2 M PRO , by a hybrid virtual screening protocol, combining ligand- and structure-based approaches with multivariate statistical analysis. The Biotarget Predictor Tool was used to filter a large in-house structural database and select a set of benzo[ b ]thiophene and benzo[ b ]furan derivatives. ADME properties were investigated, and induced fit docking studies were performed to confirm the DRUDIT prediction. Principal component analysis and docking protocol at the SARS-CoV-2 M PRO dimerization site enable the identification of compounds 1b , c , i , l and 2i , l as promising drug molecules, showing favorable dual binding site affinity on SARS-CoV-2 M PRO . |
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| Keywords | catalytic site ; allosteric site ; SARS-CoV-2 M PRO ; inhibitors ; benzo[ b ]thiophene ; benzo[ b ]furan ; Biology (General) ; QH301-705.5 ; Chemistry ; QD1-999 |
| Subject code | 540 |
| Language | English |
| Publishing date | 2023-05-01T00:00:00Z |
| Publisher | MDPI AG |
| Document type | Article ; Online |
| Database | BASE - Bielefeld Academic Search Engine (life sciences selection) |
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