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A Computational Physics-based Approach to Predict Unbound Brain-to-Plasma Partition Coefficient, K <sub>p,uu</sub>

Morgan Lawrenz, Mats Svensson, Mitsunori Kato, Karen H. Dingley, Jackson Chief Elk, Zhe Nie, Yefen Zou, Zachary Kaplan, H. Rachel Lagiakos, Hideyuki Igawa, Éric Therrien

2023Journal of Chemical Information and Modeling22 citationsDOI

Abstract

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 (K p,uu ). While various medicinal chemistry strategies and in silico models have been reported to improve BBB penetration, they have limited application in predicting K p,uu directly. We describe a physics-based computational approach, a quantum mechanics (QM)-based energy of solvation (E-sol), to predict K p,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 R 2 of 0.61 from a linear regression model.

Topics & Concepts

Categorical variableSolvationIn silicoDrug discoveryPlasmaPenetration (warfare)Statistical physicsPhysicsComputer scienceChemistryMathematicsMoleculeBioinformaticsMachine learningBiologyNuclear physicsOperations researchQuantum mechanicsGeneBiochemistryDrug Transport and Resistance MechanismsComputational Drug Discovery MethodsProtein Interaction Studies and Fluorescence Analysis
A Computational Physics-based Approach to Predict Unbound Brain-to-Plasma Partition Coefficient, K <sub>p,uu</sub> | Litcius