In silico approaches to predict drug-transporter interaction profiles: Data mining, model generation, and link to cholestasis

Sankalp Jain, Gerhard F. Ecker

    Veröffentlichungen: Beitrag in BuchBeitrag in Buch/SammelbandPeer Reviewed

    Abstract

    Transport proteins play a crucial role in drug distribution, disposition, and clearance by mediating cellular drug influx and efflux. Inhibition of these transporters may lead to drug-drug interactions or even drug-induced liver injury, such as cholestasis, which comprises a major challenge in drug development process. Thus, computer-based (in silico) models that can predict the pharmacological and toxicological profiles of these small molecules with respect to liver transporters may help in the early prioritization of compounds and hence may lower the high attrition rates. In this chapter, we provide a protocol for in silico prediction of cholestasis by generating validated predictive models. In addition to the two-dimensional molecular descriptors, we include transporter inhibition predictions as descriptors and evaluate the influence of the same on the performance of the cholestasis models.

    OriginalspracheEnglisch
    TitelMethods in Molecular Biology
    Herausgeber (Verlag)Humana Press, Inc.
    Seiten383-396
    Seitenumfang14
    DOIs
    PublikationsstatusVeröffentlicht - 1 Jan. 2019

    Publikationsreihe

    ReiheMethods in Molecular Biology
    Band1981
    ISSN1064-3745

    ÖFOS 2012

    • 301207 Pharmazeutische Chemie

    Zitationsweisen