DockCADD: A streamlined in silico pipeline for the identification of potent ribosomal S6 Kinase 2 (RSK2) inhibitors
The search for innovative therapeutic strategies remains critical in addressing cancer, one of the leading global health challenges. Ribosomal S6 Kinase 2 (RSK2), a serine/threonine kinase, has emerged as a promising target for cancer therapy because it is implicated in oncogenic signaling. Herein,...
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Elsevier
2025-03-01
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| Series: | Scientific African |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2468227625000523 |
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| author | El Mehdi Karim Meriem Khedraoui Abdelkbir Errougui Yasir S. Raouf Abdelouahid Samadi Samir Chtita |
| author_facet | El Mehdi Karim Meriem Khedraoui Abdelkbir Errougui Yasir S. Raouf Abdelouahid Samadi Samir Chtita |
| author_sort | El Mehdi Karim |
| collection | DOAJ |
| description | The search for innovative therapeutic strategies remains critical in addressing cancer, one of the leading global health challenges. Ribosomal S6 Kinase 2 (RSK2), a serine/threonine kinase, has emerged as a promising target for cancer therapy because it is implicated in oncogenic signaling. Herein, we developed an open-source computational pipeline, identified as DockCADD (available at https://github.com/mehdikariim/DockCADD), which enables the identification of potent RSK2 inhibitors by automated virtual screening, ADME-Tox profiling, and molecular dynamics (MD) simulations. Employing pyran derivatives as the scaffold, top-scoring inhibitors as identified by the pipeline showed scores ranging from -9.46 to -9.89 kcal/mol and binding free energies ranging from -53.731 to -55.193 kcal/mol. Ligands L1, L2 and L3 showed stable binding within the ATP-binding pocket, wherein the compounds undergo slight structural distortions with a favorable van der Waal's interaction. The ligand L3 has exhibited the highest MM-GBSA binding free energy (-55.193 kcal/mol), which so far presents the most promising candidate. These results have pointed out the use of DockCADD as an efficient tool for the fast and low-cost process of drug discovery; L1–L3 should be further validated experimentally for cancer therapy. |
| format | Article |
| id | doaj-art-e5279ec2a9bb4972a5f5b76db38519aa |
| institution | Kabale University |
| issn | 2468-2276 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Scientific African |
| spelling | doaj-art-e5279ec2a9bb4972a5f5b76db38519aa2025-02-11T04:35:18ZengElsevierScientific African2468-22762025-03-0127e02581DockCADD: A streamlined in silico pipeline for the identification of potent ribosomal S6 Kinase 2 (RSK2) inhibitorsEl Mehdi Karim0Meriem Khedraoui1Abdelkbir Errougui2Yasir S. Raouf3Abdelouahid Samadi4Samir Chtita5Laboratory of Analytical and Molecular Chemistry, Faculty of Sciences Ben M'Sik, Hassan II University of Casablanca, Casablanca, 7995, MoroccoLaboratory of Analytical and Molecular Chemistry, Faculty of Sciences Ben M'Sik, Hassan II University of Casablanca, Casablanca, 7995, MoroccoLaboratory of Analytical and Molecular Chemistry, Faculty of Sciences Ben M'Sik, Hassan II University of Casablanca, Casablanca, 7995, MoroccoDepartment of Chemistry, College of Science, United Arab Emirates University, Al Ain P.O. Box 15551, United Arab EmiratesDepartment of Chemistry, College of Science, United Arab Emirates University, Al Ain P.O. Box 15551, United Arab Emirates; Corresponding authors.Laboratory of Analytical and Molecular Chemistry, Faculty of Sciences Ben M'Sik, Hassan II University of Casablanca, Casablanca, 7995, Morocco; Corresponding authors.The search for innovative therapeutic strategies remains critical in addressing cancer, one of the leading global health challenges. Ribosomal S6 Kinase 2 (RSK2), a serine/threonine kinase, has emerged as a promising target for cancer therapy because it is implicated in oncogenic signaling. Herein, we developed an open-source computational pipeline, identified as DockCADD (available at https://github.com/mehdikariim/DockCADD), which enables the identification of potent RSK2 inhibitors by automated virtual screening, ADME-Tox profiling, and molecular dynamics (MD) simulations. Employing pyran derivatives as the scaffold, top-scoring inhibitors as identified by the pipeline showed scores ranging from -9.46 to -9.89 kcal/mol and binding free energies ranging from -53.731 to -55.193 kcal/mol. Ligands L1, L2 and L3 showed stable binding within the ATP-binding pocket, wherein the compounds undergo slight structural distortions with a favorable van der Waal's interaction. The ligand L3 has exhibited the highest MM-GBSA binding free energy (-55.193 kcal/mol), which so far presents the most promising candidate. These results have pointed out the use of DockCADD as an efficient tool for the fast and low-cost process of drug discovery; L1–L3 should be further validated experimentally for cancer therapy.http://www.sciencedirect.com/science/article/pii/S2468227625000523RSK2 inhibitorsMolecular dockingADME-Tox profilingMolecular dynamicsMM-GBSAPyran derivatives |
| spellingShingle | El Mehdi Karim Meriem Khedraoui Abdelkbir Errougui Yasir S. Raouf Abdelouahid Samadi Samir Chtita DockCADD: A streamlined in silico pipeline for the identification of potent ribosomal S6 Kinase 2 (RSK2) inhibitors Scientific African RSK2 inhibitors Molecular docking ADME-Tox profiling Molecular dynamics MM-GBSA Pyran derivatives |
| title | DockCADD: A streamlined in silico pipeline for the identification of potent ribosomal S6 Kinase 2 (RSK2) inhibitors |
| title_full | DockCADD: A streamlined in silico pipeline for the identification of potent ribosomal S6 Kinase 2 (RSK2) inhibitors |
| title_fullStr | DockCADD: A streamlined in silico pipeline for the identification of potent ribosomal S6 Kinase 2 (RSK2) inhibitors |
| title_full_unstemmed | DockCADD: A streamlined in silico pipeline for the identification of potent ribosomal S6 Kinase 2 (RSK2) inhibitors |
| title_short | DockCADD: A streamlined in silico pipeline for the identification of potent ribosomal S6 Kinase 2 (RSK2) inhibitors |
| title_sort | dockcadd a streamlined in silico pipeline for the identification of potent ribosomal s6 kinase 2 rsk2 inhibitors |
| topic | RSK2 inhibitors Molecular docking ADME-Tox profiling Molecular dynamics MM-GBSA Pyran derivatives |
| url | http://www.sciencedirect.com/science/article/pii/S2468227625000523 |
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