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Efficient Interrogation of the Kinetic Barriers Demarcating Catalytic States of a Tyrosine Kinase with Optimal Physical Descriptors and Mixture Models.
Dutta, Pallab; Sengupta, Neelanjana.
Afiliación
  • Dutta P; Department of Biological Sciences, Indian Institute of Science Education and Research (IISER) Kolkata, Mohanpur, 741246, India.
  • Sengupta N; Department of Biological Sciences, Indian Institute of Science Education and Research (IISER) Kolkata, Mohanpur, 741246, India.
Chemphyschem ; 24(6): e202200595, 2023 03 14.
Article en En | MEDLINE | ID: mdl-36394126
ABSTRACT
Computer simulations are increasingly used to access thermo-kinetic information underlying structural transformation of protein kinases. Such information are necessary to probe their roles in disease progression and interactions with drug targets. However, the investigations are frequently challenged by forbiddingly high computational expense, and by the lack of standard protocols for the design of low dimensional physical descriptors that encode system features important for transitions. Here, we consider the demarcating characteristics of the different states of Abelson tyrosine kinase associated with distinct catalytic activity to construct a set of physically meaningful, orthogonal collective variables that preserve the slow modes of the system. Independent sampling of each metastable state is followed by the estimation of global partition function along the appropriate physical descriptors using the modified Expectation Maximized Molecular Dynamics method. The resultant free energy barriers are in excellent agreement with experimentally known rate-limiting dynamics and activation energy computed with conventional enhanced sampling methods. We discuss possible directions for further development and applications.
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Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Proteínas Tirosina Quinasas / Simulación de Dinámica Molecular Tipo de estudio: Prognostic_studies Idioma: En Revista: Chemphyschem Asunto de la revista: BIOFISICA / QUIMICA Año: 2023 Tipo del documento: Article País de afiliación: India

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Proteínas Tirosina Quinasas / Simulación de Dinámica Molecular Tipo de estudio: Prognostic_studies Idioma: En Revista: Chemphyschem Asunto de la revista: BIOFISICA / QUIMICA Año: 2023 Tipo del documento: Article País de afiliación: India