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

Vigneshwaran NamasivayamKatja SilbermannMichael WieseJens PahnkeSven Marcel Stefan
Published in: Journal of medicinal chemistry (2021)
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.
Keyphrases
  • small molecule
  • high throughput
  • systematic review
  • single cell
  • tissue engineering
  • data analysis