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

Vigneshwaran Namasivayam, Katja Silbermann, Michael Wiese, Jens Pahnke, Sven Marcel Stefan*

*Korrespondierende/r Autor/-in für diese Arbeit
1 Zitat (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.

OriginalspracheEnglisch
ZeitschriftJournal of Medicinal Chemistry
Jahrgang64
Ausgabenummer6
Seiten (von - bis)3350-3366
Seitenumfang17
ISSN0022-2623
DOIs
PublikationsstatusVeröffentlicht - 25.03.2021

Strategische Forschungsbereiche und Zentren

  • Forschungsschwerpunkt: Infektion und Entzündung - Zentrum für Infektions- und Entzündungsforschung Lübeck (ZIEL)

Fingerprint

Untersuchen Sie die Forschungsthemen von „C@PA: Computer-Aided Pattern Analysis to Predict Multitarget ABC Transporter Inhibitors“. Zusammen bilden sie einen einzigartigen Fingerprint.

Zitieren