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A Computational Physics-based Approach to Predict Unbound Brain-to-Plasma Partition Coefficient, Kp,uu.
Lawrenz, Morgan; Svensson, Mats; Kato, Mitsunori; Dingley, Karen H; Chief Elk, Jackson; Nie, Zhe; Zou, Yefen; Kaplan, Zachary; Lagiakos, H Rachel; Igawa, Hideyuki; Therrien, Eric.
Afiliación
  • Lawrenz M; Schrödinger Inc., San Diego, California 92122, United States.
  • Svensson M; Schrödinger Inc., New York, New York 10036, United States.
  • Kato M; Schrödinger Inc., New York, New York 10036, United States.
  • Dingley KH; Schrödinger Inc., New York, New York 10036, United States.
  • Chief Elk J; Schrödinger Inc., Portland, Oregon 97204, United States.
  • Nie Z; Schrödinger Inc., San Diego, California 92122, United States.
  • Zou Y; Schrödinger Inc., San Diego, California 92122, United States.
  • Kaplan Z; Schrödinger Inc., New York, New York 10036, United States.
  • Lagiakos HR; Schrödinger Inc., New York, New York 10036, United States.
  • Igawa H; Schrödinger Inc., New York, New York 10036, United States.
  • Therrien E; Schrödinger Inc., New York, New York 10036, United States.
J Chem Inf Model ; 63(12): 3786-3798, 2023 06 26.
Article en En | MEDLINE | ID: mdl-37267072
The blood-brain barrier (BBB) plays a critical role in preventing harmful endogenous and exogenous substances from penetrating the brain. Optimal brain penetration of small-molecule central nervous system (CNS) drugs is characterized by a high unbound brain/plasma ratio (Kp,uu). While various medicinal chemistry strategies and in silico models have been reported to improve BBB penetration, they have limited application in predicting Kp,uu directly. We describe a physics-based computational approach, a quantum mechanics (QM)-based energy of solvation (E-sol), to predict Kp,uu. Prospective application of this method in internal CNS drug discovery programs highlights the utility and accuracy of this new method, which showed a categorical accuracy of 79% and an R2 of 0.61 from a linear regression model.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Encéfalo / Barrera Hematoencefálica Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: J Chem Inf Model Asunto de la revista: INFORMATICA MEDICA / QUIMICA Año: 2023 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: Encéfalo / Barrera Hematoencefálica Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: J Chem Inf Model Asunto de la revista: INFORMATICA MEDICA / QUIMICA Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Estados Unidos