Identification of PI3Kα inhibitors through pharmacophore design and drug repositioning†
Objective: PI3K is one of the most frequently mutated proteins in cancer, resulting in changes to its functions in regulating metabolism, immunity, among others. Despite the identification of specific drugs targeting PI3K, significant resistance tothese therapies has been observed. Therefore, the se...
| Autores: | , , , , |
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2024 |
| País: | Perú |
| Institución: | Universidad de San Martín de Porres |
| Repositorio: | Horizonte médico |
| Idioma: | español inglés |
| OAI Identifier: | oai:horizontemedico.usmp.edu.pe:article/2521 |
| Acceso en línea: | https://horizontemedico.usmp.edu.pe/index.php/horizontemed/article/view/2521 |
| Access Level: | acceso abierto |
| Palabra clave: | PI-3K Simulación del Acoplamiento Molecular Bioinformática Cáncer Farmacóforo Molecular Docking Simulation Computational Biology Neoplasms Pharmacophore |
| Sumario: | Objective: PI3K is one of the most frequently mutated proteins in cancer, resulting in changes to its functions in regulating metabolism, immunity, among others. Despite the identification of specific drugs targeting PI3K, significant resistance tothese therapies has been observed. Therefore, the search for new inhibitors is crucial. This project proposes a strategy based on in silico computational tools for screening Food and Drug Administration (FDA)-approved drugs, aiming to evaluate their potential for drug repositioning. Materials and methods: This study obtained the sequence of PI3Kα from UniProt Knowledgebase and its three-dimensional structure from AlphaFold Protein Structure Database, which were then coupled with adenosine triphosphate (ATP) and its selective inhibitors: inavolisib, taselisib, CH5132799, alpelisib and ZSTK474. Drug-protein interaction analysiswas performed using Protein-Ligand Interaction Profiler (PLIP) and its visualization was done in PyMOL. Based on this information, pharmacophores were generated as models for virtual screening using PHARMIT and the FDA-approved druglibrary (https://pharmit.csb.pitt.edu/search.html).Results: Key atomistic positions of drug-protein interactions were identified based on the selective PI3Kα inhibitors interaction, leading to the generation of nine pharmacophores. A virtual screening resulted in 22 drugs that met theproposed criteria, out of which 10 had binding energy values (kcal/mol) equal to or higher than the PI3Kα inhibitors. Subsequently, three drugs with potential use for drug repositioning were selected. Conclusions: This study proposes fostamatinib, pralatrexate and entecavir as possible candidates for drug repositioning. Additionally, the nine pharmacophores can be utilized in other drug databases for identifying new molecules and/or drugs with potential for drug repositioning. Further in silico and in vitro studies of the proposed drugs are recommended. |
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