論文

査読有り 国際誌
2019年7月22日

Computational Model To Predict the Fraction of Unbound Drug in the Brain.

Journal of chemical information and modeling
  • Tsuyoshi Esaki
  • ,
  • Rikiya Ohashi
  • ,
  • Reiko Watanabe
  • ,
  • Yayoi Natsume-Kitatani
  • ,
  • Hitoshi Kawashima
  • ,
  • Chioko Nagao
  • ,
  • Kenji Mizuguchi

59
7
開始ページ
3251
終了ページ
3261
記述言語
英語
掲載種別
研究論文(学術雑誌)
DOI
10.1021/acs.jcim.9b00180

Knowing the value of the unbound drug fraction in the brain (fu,brain) is essential in estimating its effects and toxicity on the central nervous system (CNS); however, no model to predict fu,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 fu,brain using only freely available software. By selecting appropriate descriptors, training, and evaluation, our model showed an acceptable performance on a test data set (R2 = 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.

リンク情報
DOI
https://doi.org/10.1021/acs.jcim.9b00180
PubMed
https://www.ncbi.nlm.nih.gov/pubmed/31260629

エクスポート
BibTeX RIS