Computational Model To Predict the Fraction of Unbound Drug in the Brain
Tsuyoshi Esaki, Rikiya Ohashi, Reiko Watanabe, Yayoi Natsume‐Kitatani, Hitoshi Kawashima, Chioko Nagao, Kenji Mizuguchi · Journal of Chemical Information and Modeling · 2019
Knowing the value of the unbound drug fraction in the brain ( f u,brain ) is essential in estimating its effects and toxicity on the central nervous system (CNS); however, no model to predict f u,brain without experimental procedures is publicly available. In this study, we collected 253 measurements from the literature and an open database and built in silico models to predict f u,brain using only freely available software. By selecting appropriate descriptors, training, and evaluation, our model showed an acceptable performance on a test data set ( R 2 = 0.630, percentage of compounds predicted within a 3-fold error: 69.4%) using chemical structure alone. Our model is available at https://drumap.nibiohn.go.jp/fubrain/, and all of our data sets can be obtained from the Supporting Information.