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C@PA: Computer-Aided Pattern Analysis to Predict Multitarget ABC Transporter Inhibitors

  • Vigneshwaran Namasivayam
  • , Katja Silbermann
  • , Michael Wiese
  • , Jens Pahnke
  • , Sven Marcel Stefan*
  • *Corresponding author for this work
  • University of Bonn
  • Leibniz Institute of Plant Biochemistry
  • University of Lübeck
  • University of Oslo
  • University of Sydney

Research output: Contribution to journal › Article › peer-review

39 Citations (Scopus)

Abstract

Based on literature reports of the last two decades, a computer-aided pattern analysis (C@PA) was implemented for the discovery of novel multitarget ABCB1 (P-gp), ABCC1 (MRP1), and ABCG2 (BCRP) inhibitors. C@PA included basic scaffold identification, substructure search and statistical distribution, as well as novel scaffold extraction to screen a large virtual compound library. Over 45,000 putative and novel broad-spectrum ABC transporter inhibitors were identified, from which 23 were purchased for biological evaluation. Our investigations revealed five novel lead molecules as triple ABCB1, ABCC1, and ABCG2 inhibitors. C@PA is the very first successful computational approach for the discovery of promiscuous ABC transporter inhibitors.

Original languageEnglish
Pages (from-to)3350-3366
JournalJournal of Medicinal Chemistry
Volume64
Issue number6
DOIs
Publication statusPublished - 25 Mar 2021

OECD Field of Science

  • 3.1 Basic Medicine

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