Laboratory of Bioinformatics , National Institutes of Biomedical Innovation, Health and Nutrition , 7-6-8 Saito-Asagi , Osaka , Ibaraki 567-0085 , Japan.
Discovery Technology Laboratories , Mitsubishi Tanabe Pharma Corporation , 2-2-50 Kawagishi , Toda , Saitama 335-8505 , Japan.
J Chem Inf Model. 2019 Jul 22;59(7):3251-3261. doi: 10.1021/acs.jcim.9b00180. Epub 2019 Jul 11.
Knowing the value of the unbound drug fraction in the brain () is essential in estimating its effects and toxicity on the central nervous system (CNS); however, no model to predict 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 using only freely available software. By selecting appropriate descriptors, training, and evaluation, our model showed an acceptable performance on a test data set ( = 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.
了解脑内游离药物分数的价值()对于评估其对中枢神经系统(CNS)的影响和毒性至关重要;然而,目前还没有公开的模型可以在没有实验程序的情况下预测。在这项研究中,我们从文献和一个开放数据库中收集了 253 个测量值,并使用仅可免费获得的软件构建了用于预测的计算模型。通过选择合适的描述符、训练和评估,我们的模型仅使用化学结构在测试数据集上表现出可接受的性能(= 0.630,预测化合物的百分比在 3 倍误差内:69.4%)。我们的模型可在 https://drumap.nibiohn.go.jp/fubrain/ 上获得,并且可以从支持信息中获得我们所有的数据集。