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PgpRules: a decision tree based prediction server for P-glycoprotein substrates and inhibitors.
Wang, Pei-Hua; Tu, Yi-Shu; Tseng, Yufeng J.
Afiliação
  • Wang PH; Graduate Institute of Biomedical Electronics and Bioinformatics.
  • Tu YS; Graduate Institute of Biomedical Electronics and Bioinformatics.
  • Tseng YJ; Graduate Institute of Biomedical Electronics and Bioinformatics.
Bioinformatics ; 35(20): 4193-4195, 2019 10 15.
Article em En | MEDLINE | ID: mdl-30918935
ABSTRACT

SUMMARY:

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. AVAILABILITY AND IMPLEMENTATION PgpRules is freely accessible at https//pgprules.cmdm.tw/. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Árvores de Decisões Tipo de estudo: Health_economic_evaluation / Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2019 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Árvores de Decisões Tipo de estudo: Health_economic_evaluation / Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2019 Tipo de documento: Article