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
1 Citation (Scopus)


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
JournalJournal of Medicinal Chemistry
Issue number6
Pages (from-to)3350-3366
Number of pages17
Publication statusPublished - 25.03.2021

Research Areas and Centers

  • Academic Focus: Center for Infection and Inflammation Research (ZIEL)


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