Developing Dynamic Structure-Based Pharmacophore and ML-Trained QSAR Models for the Discovery of Novel Resistance-Free RET Tyrosine Kinase Inhibitors Through Extensive MD Trajectories and NRI Analysis.
ChemMedChem
; 19(12): e202300644, 2024 Jun 17.
Article
en En
| MEDLINE
| ID: mdl-38523069
ABSTRACT
Activation of RET tyrosine kinase plays a critical role in the pathogenesis of various cancers, including non-small cell lung cancer, papillary thyroid cancers, multiple endocrine neoplasia type 2A and 2B (MEN2A, MEN2B), and familial medullary thyroid cancer. Gene fusions and point mutations in the RET proto-oncogene result in constitutive activation of RET signaling pathways. Consequently, developing effective inhibitors to target RET is of utmost importance. Small molecules have shown promise as inhibitors by binding to the kinase domain of RET and blocking its enzymatic activity. However, the emergence of resistance due to single amino acid changes poses a significant challenge. In this study, a structure-based dynamic pharmacophore-driven approach using E-pharmacophore modeling from molecular dynamics trajectories is proposed to select low-energy favorable hypotheses, and ML-trained QSAR models to predict pIC50 values of compounds. For this aim, extensive small molecule libraries were screened using developed ligand-based models, and potent compounds that are capable of inhibiting RET activation were proposed.
Palabras clave
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Relación Estructura-Actividad Cuantitativa
/
Inhibidores de Proteínas Quinasas
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Proteínas Proto-Oncogénicas c-ret
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Simulación de Dinámica Molecular
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Proto-Oncogenes Mas
Límite:
Humans
Idioma:
En
Revista:
ChemMedChem
Asunto de la revista:
FARMACOLOGIA
/
QUIMICA
Año:
2024
Tipo del documento:
Article
País de afiliación:
Turquía