dc.contributor.author
Liu, Sijie
dc.contributor.author
Wu, Jie
dc.contributor.author
Chen, Ya
dc.contributor.author
Wolf, Clemens Alexander
dc.contributor.author
Bureik, Matthias
dc.contributor.author
Kirchmair, Johannes
dc.contributor.author
Marchisio, Mario Andrea
dc.contributor.author
Wolber, Gerhard
dc.date.accessioned
2025-04-30T10:40:39Z
dc.date.available
2025-04-30T10:40:39Z
dc.identifier.uri
https://refubium.fu-berlin.de/handle/fub188/47184
dc.identifier.uri
http://dx.doi.org/10.17169/refubium-46902
dc.description.abstract
The human cytochrome P450 19A1 (CYP19A1, aromatase) is a heme-containing protein catalyzing the final steps of the biosynthesis of the steroid hormone 17β-estradiol. It is a key target for the treatment of sex-hormone-related disorders due to its role in mediating the conversion of androgens to estrogens. Here, we report the development of a virtual screening workflow incorporating machine learning and structure-based modeling that has led to the discovery of new CYP19A1 inhibitors. The machine learning models were built on comprehensive CYP19A1 data sets extracted from the ChEMBL and PubChem Bioassay databases and subjected to thorough validation routines. Ten promising hits that resulted from the virtual screening campaign were selected for experimental testing in an enzymatic assay based on heterologous expression of human CYP19A1 in yeast. Among the seven structurally diverse compounds identified as new CYP19A1 inhibitors, compound 9, a novel, noncovalent inhibitor based on coumarin and imidazole substructures, stood out by its high potency, with an IC50 value of 271 ± 51 nM.
en
dc.format.extent
15 Seiten
dc.rights.uri
https://creativecommons.org/licenses/by/4.0/
dc.subject
Aromatic compounds
en
dc.subject
Molecular modeling
en
dc.subject
Screening assays
en
dc.subject.ddc
600 Technik, Medizin, angewandte Wissenschaften::610 Medizin und Gesundheit::615 Pharmakologie, Therapeutik
dc.title
Integrated Virtual Screening Approach Identifies New CYP19A1 Inhibitors
dc.type
Wissenschaftlicher Artikel
dcterms.bibliographicCitation.doi
10.1021/acs.jcim.5c00204
dcterms.bibliographicCitation.journaltitle
Journal of Chemical Information and Modeling
dcterms.bibliographicCitation.number
7
dcterms.bibliographicCitation.pagestart
65
dcterms.bibliographicCitation.pagestart
3529
dcterms.bibliographicCitation.pageend
3543
dcterms.bibliographicCitation.url
https://doi.org/10.1021/acs.jcim.5c00204
refubium.affiliation
Biologie, Chemie, Pharmazie
refubium.affiliation.other
Institut für Pharmazie

refubium.funding
ACS Publications
refubium.note.author
Gefördert aus Open-Access-Mitteln der Freien Universität Berlin.
refubium.resourceType.isindependentpub
no
dcterms.accessRights.openaire
open access
dcterms.isPartOf.eissn
1549-960X