4.7 Article

PgpRules: a decision tree based prediction server for P-glycoprotein substrates and inhibitors

Journal

BIOINFORMATICS
Volume 35, Issue 20, Pages 4193-4195

Publisher

OXFORD UNIV PRESS
DOI: 10.1093/bioinformatics/btz213

Keywords

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Funding

  1. NTU SPARK program, Ministry of Science and Technology, Taiwan [most 107-2823-8-002-003-]
  2. Computational Molecular Design and Metabolomics Laboratory, Department of Computer Science and Information Engineering at National Taiwan University

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P-glycoprotein (P-gp) is a member of ABC transporter family that actively pumps xenobiotics out of cells to protect organisms from toxic compounds. P-gp substrates can be easily pumped out of the cells to reduce their absorption; conversely P-gp inhibitors can reduce such pumping activity. Hence, it is crucial to know if a drug is a P-gp substrate or inhibitor in view of pharmacokinetics. Here we present PgpRules, an online P-gp substrate and P-gp inhibitor prediction server with ruled-sets. The two models were built using classification and regression tree algorithm. For each compound uploaded, PgpRules not only predicts whether the compound is a P-gp substrate or a P-gp inhibitor, but also provides the rules containing chemical structural features for further structural optimization.

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