期刊
JOURNAL OF MEDICINAL CHEMISTRY
卷 64, 期 6, 页码 3350-3366出版社
AMER CHEMICAL SOC
DOI: 10.1021/acs.jmedchem.0c02199
关键词
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资金
- Deutsche Forschungsgemeinschaft/Germany (DFG, German Research Foundation) [252102222, 263024513]
- Ministerium fur Wirtschaft und Wissenschaft Sachsen-Anhalt/Germany [ZS/2016/05/78617]
- Latvian Council of Science/Latvia [lzp-2018/1-0275]
- Nasjonalforeningen [16154]
- HelseSO/Norway [2016062, 2019054, 2019055]
- Barnekreftforeningen [19008]
- EEA grant/Norway grants Kappa programme [TO100078]
- Norges forskningsradet/Norway [251290, 260786, 295910]
- European Commission [643417]
- JPND (AKA - Finland) [301228]
- BMBF - Germany [01ED1605]
- CSO-MOH - Israel [30000-12631]
- NFR - Norway [260786]
- SRC - Sweden [2015-06795]
- FFR - Austria
- MSMR - Czech Republic
- VIAA - Latvia
- ANF - France
- European Union [643417]
- DFG [STE2931/2 (446812474)]
- Swedish Research Council [2015-06795] Funding Source: Swedish Research Council
- Academy of Finland (AKA) [301228, 301228] Funding Source: Academy of Finland (AKA)
This study utilized a computer-aided pattern analysis (C@PA) approach to discover novel multitarget ABC transporter inhibitors, successfully identifying over 45,000 potential inhibitors from a virtual compound library and revealing five novel lead molecules as triple ABCB1, ABCC1, and ABCG2 inhibitors. C@PA represents the first computational approach for the discovery of promiscuous ABC transporter inhibitors.
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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