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Dissecting the Interaction Fingerprints and Binding Affinity of BYL719 Analogs Targeting PI3Kα.
Dehghani-Ghahnaviyeh, Sepehr; Soylu, Cihan; Furet, Pascal; Velez-Vega, Camilo.
Afiliación
  • Dehghani-Ghahnaviyeh S; Novartis Institutes for BioMedical Research, 181 Massachusetts Avenue, Cambridge, Massachusetts 02139, United States.
  • Soylu C; Novartis Institutes for BioMedical Research, 181 Massachusetts Avenue, Cambridge, Massachusetts 02139, United States.
  • Furet P; Novartis Institutes for BioMedical Research, CH4002 Basel, Switzerland.
  • Velez-Vega C; Novartis Institutes for BioMedical Research, 181 Massachusetts Avenue, Cambridge, Massachusetts 02139, United States.
J Phys Chem B ; 128(8): 1819-1829, 2024 Feb 29.
Article en En | MEDLINE | ID: mdl-38373112
ABSTRACT
Phosphatidylinositol-3-kinase Alpha (PI3Kα) is a lipid kinase which regulates signaling pathways involved in cell proliferation. Dysregulation of these pathways promotes several human cancers, pushing for the development of anticancer drugs to target PI3Kα. One such medicinal chemistry campaign at Novartis led to the discovery of BYL719 (Piqray, Alpelicib), a PI3Kα inhibitor approved by the FDA in 2019 for treatment of HR+/HER2-advanced breast cancer with a PIK3CA mutation. Structure-based drug design played a key role in compound design and optimization throughout the discovery process. However, further characterization of potency drivers via structural dynamics and energetic analyses can be advantageous for ensuing PI3Kα programs. Here, our goal is to employ various in-silico techniques, including molecular simulations and machine learning, to characterize 14 ligands from the BYL719 analogs and predict their binding affinities. The structural insights from molecular simulations suggest that although the ligand-hinge interaction is the primary driver of ligand stability at the pocket, the R group positioning at C2 or C6 of pyridine/pyrimidine also plays a major role. Binding affinities predicted via thermodynamic integration (TI) are in good agreement with previously reported IC50s. Yet, computationally demanding techniques such as TI might not always be the most efficient approach for affinity prediction, as in our case study, fast high-throughput techniques were capable of classifying compounds as active or inactive, and one docking approach showed accuracy comparable to TI.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Tiazoles / Neoplasias de la Mama / Antineoplásicos Límite: Female / Humans Idioma: En Revista: J Phys Chem B Asunto de la revista: QUIMICA Año: 2024 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Tiazoles / Neoplasias de la Mama / Antineoplásicos Límite: Female / Humans Idioma: En Revista: J Phys Chem B Asunto de la revista: QUIMICA Año: 2024 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Estados Unidos