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

Vigneshwaran Namasivayam; Katja Silbermann; Michael Wiese; Jens Pahnke; Sven Marcel Stefan

doi:10.1021/acs.jmedchem.0c02199

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

Institute of Experimental Dermatology

University of Bonn

1 Citation (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 language	English
Journal	Journal of Medicinal Chemistry
Volume	64
Issue number	6
Pages (from-to)	3350-3366
Number of pages	17
ISSN	0022-2623
DOIs	https://doi.org/10.1021/acs.jmedchem.0c02199
Publication status	Published - 25.03.2021

Research Areas and Centers

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

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This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1021/acs.jmedchem.0c02199

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title = "C@PA: Computer-Aided Pattern Analysis to Predict Multitarget ABC Transporter Inhibitors",

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. ",

author = "Vigneshwaran Namasivayam and Katja Silbermann and Michael Wiese and Jens Pahnke and Stefan, {Sven Marcel}",

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AU - Namasivayam, Vigneshwaran

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AU - Wiese, Michael

AU - Pahnke, Jens

AU - Stefan, Sven Marcel

PY - 2021/3/25

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N2 - 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.

AB - 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.

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

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