In Silico Identification of Possible Inhibitors for Protein Kinase B (PknB) of <i>Mycobacterium tuberculosis</i>
With tuberculosis still being one of leading causes of death in the world and the emergence of drug-resistant strains of <i>Mycobacterium tuberculosis</i> (Mtb), researchers have been seeking to find further therapeutic strategies or more specific molecular targets. PknB is one of the 11...
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MDPI AG
2021-10-01
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| Series: | Molecules |
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| Online Access: | https://www.mdpi.com/1420-3049/26/20/6162 |
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| author | Tatiana F. Vieira Fábio G. Martins Joel P. Moreira Tiago Barbosa Sérgio F. Sousa |
| author_facet | Tatiana F. Vieira Fábio G. Martins Joel P. Moreira Tiago Barbosa Sérgio F. Sousa |
| author_sort | Tatiana F. Vieira |
| collection | DOAJ |
| description | With tuberculosis still being one of leading causes of death in the world and the emergence of drug-resistant strains of <i>Mycobacterium tuberculosis</i> (Mtb), researchers have been seeking to find further therapeutic strategies or more specific molecular targets. PknB is one of the 11 Ser/Thr protein kinases of Mtb and is responsible for phosphorylation-mediated signaling, mainly involved in cell wall synthesis, cell division and metabolism. With the amount of structural information available and the great interest in protein kinases, PknB has become an attractive target for drug development. This work describes the optimization and application of an in silico computational protocol to find new PknB inhibitors. This multi-level computational approach combines protein–ligand docking, structure-based virtual screening, molecular dynamics simulations and free energy calculations. The optimized protocol was applied to screen a large dataset containing 129,650 molecules, obtained from the ZINC/FDA-Approved database, Mu.Ta.Lig Virtual Chemotheca and Chimiothèque Nationale. It was observed that the most promising compounds selected occupy the adenine-binding pocket in PknB, and the main interacting residues are Leu17, Val26, Tyr94 and Met155. Only one of the compounds was able to move the active site residues into an open conformation. It was also observed that the P-loop and magnesium position loops change according to the characteristics of the ligand. This protocol led to the identification of six compounds for further experimental testing while also providing additional structural information for the design of more specific and more effective derivatives. |
| first_indexed | 2024-03-10T06:21:17Z |
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| institution | Directory Open Access Journal |
| issn | 1420-3049 |
| language | English |
| last_indexed | 2024-03-10T06:21:17Z |
| publishDate | 2021-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Molecules |
| spelling | doaj.art-a14470ca0d3c4e82a5740762248710032023-11-22T19:19:01ZengMDPI AGMolecules1420-30492021-10-012620616210.3390/molecules26206162In Silico Identification of Possible Inhibitors for Protein Kinase B (PknB) of <i>Mycobacterium tuberculosis</i>Tatiana F. Vieira0Fábio G. Martins1Joel P. Moreira2Tiago Barbosa3Sérgio F. Sousa4Associate Laboratory i4HB—Institute for Health and Bioeconomy, Faculdade de Medicina, Universidade do Porto, 4200-319 Porto, PortugalAssociate Laboratory i4HB—Institute for Health and Bioeconomy, Faculdade de Medicina, Universidade do Porto, 4200-319 Porto, PortugalAssociate Laboratory i4HB—Institute for Health and Bioeconomy, Faculdade de Medicina, Universidade do Porto, 4200-319 Porto, PortugalAssociate Laboratory i4HB—Institute for Health and Bioeconomy, Faculdade de Medicina, Universidade do Porto, 4200-319 Porto, PortugalAssociate Laboratory i4HB—Institute for Health and Bioeconomy, Faculdade de Medicina, Universidade do Porto, 4200-319 Porto, PortugalWith tuberculosis still being one of leading causes of death in the world and the emergence of drug-resistant strains of <i>Mycobacterium tuberculosis</i> (Mtb), researchers have been seeking to find further therapeutic strategies or more specific molecular targets. PknB is one of the 11 Ser/Thr protein kinases of Mtb and is responsible for phosphorylation-mediated signaling, mainly involved in cell wall synthesis, cell division and metabolism. With the amount of structural information available and the great interest in protein kinases, PknB has become an attractive target for drug development. This work describes the optimization and application of an in silico computational protocol to find new PknB inhibitors. This multi-level computational approach combines protein–ligand docking, structure-based virtual screening, molecular dynamics simulations and free energy calculations. The optimized protocol was applied to screen a large dataset containing 129,650 molecules, obtained from the ZINC/FDA-Approved database, Mu.Ta.Lig Virtual Chemotheca and Chimiothèque Nationale. It was observed that the most promising compounds selected occupy the adenine-binding pocket in PknB, and the main interacting residues are Leu17, Val26, Tyr94 and Met155. Only one of the compounds was able to move the active site residues into an open conformation. It was also observed that the P-loop and magnesium position loops change according to the characteristics of the ligand. This protocol led to the identification of six compounds for further experimental testing while also providing additional structural information for the design of more specific and more effective derivatives.https://www.mdpi.com/1420-3049/26/20/6162<i>Mycobacterium tuberculosis</i>serine/threonine protein kinasesPknBvirtual screeningmolecular dockingmolecular dynamics simulations |
| spellingShingle | Tatiana F. Vieira Fábio G. Martins Joel P. Moreira Tiago Barbosa Sérgio F. Sousa In Silico Identification of Possible Inhibitors for Protein Kinase B (PknB) of <i>Mycobacterium tuberculosis</i> Molecules <i>Mycobacterium tuberculosis</i> serine/threonine protein kinases PknB virtual screening molecular docking molecular dynamics simulations |
| title | In Silico Identification of Possible Inhibitors for Protein Kinase B (PknB) of <i>Mycobacterium tuberculosis</i> |
| title_full | In Silico Identification of Possible Inhibitors for Protein Kinase B (PknB) of <i>Mycobacterium tuberculosis</i> |
| title_fullStr | In Silico Identification of Possible Inhibitors for Protein Kinase B (PknB) of <i>Mycobacterium tuberculosis</i> |
| title_full_unstemmed | In Silico Identification of Possible Inhibitors for Protein Kinase B (PknB) of <i>Mycobacterium tuberculosis</i> |
| title_short | In Silico Identification of Possible Inhibitors for Protein Kinase B (PknB) of <i>Mycobacterium tuberculosis</i> |
| title_sort | in silico identification of possible inhibitors for protein kinase b pknb of i mycobacterium tuberculosis i |
| topic | <i>Mycobacterium tuberculosis</i> serine/threonine protein kinases PknB virtual screening molecular docking molecular dynamics simulations |
| url | https://www.mdpi.com/1420-3049/26/20/6162 |
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