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Hands-off linear interaction energy approach to binding mode and affinity estimation of estrogens

  • With this work we target the development of a predictictive model for the identification of small molecules which bind to the estrogen receptor alpha and, thus, may act as endocrine disruptors. We propose a combined thermodynamic approach for the estimation of preferential binding modes along with corresponding free energy differences using a linear interaction energy (LIE) ansatz. The LIE model is extended by a Monte Carlo approach for the computation of conformational entropies as recently developed by our group. Incorporating the entropy contribution substantially increased the correlation with experimental affinity values. Both squared coefficients for the fitted data as well as the more meaningful leave-one-out cross-validation of predicted energies were elevated up to rFit2 = 0.87 and qLOO2 = 0.82, respectively. All calculations have been performed on a set of 31 highly diverse ligands regarding their structural properties and affinities to the estrogen receptor alpha. ComparisonWith this work we target the development of a predictictive model for the identification of small molecules which bind to the estrogen receptor alpha and, thus, may act as endocrine disruptors. We propose a combined thermodynamic approach for the estimation of preferential binding modes along with corresponding free energy differences using a linear interaction energy (LIE) ansatz. The LIE model is extended by a Monte Carlo approach for the computation of conformational entropies as recently developed by our group. Incorporating the entropy contribution substantially increased the correlation with experimental affinity values. Both squared coefficients for the fitted data as well as the more meaningful leave-one-out cross-validation of predicted energies were elevated up to rFit2 = 0.87 and qLOO2 = 0.82, respectively. All calculations have been performed on a set of 31 highly diverse ligands regarding their structural properties and affinities to the estrogen receptor alpha. Comparison of predicted ligand orientations with crystallographic data retrieved from the Protein database pdb.org revealed remarkable binding mode predictions.zeige mehrzeige weniger

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Metadaten
Autoren/innen:V. Durmaz, Sebastian Schmidt, P. Sabri, Christian Piechotta, M. Weber
Dokumenttyp:Zeitschriftenartikel
Veröffentlichungsform:Verlagsliteratur
Sprache:Englisch
Titel des übergeordneten Werkes (Englisch):Journal of chemical information and modeling
Jahr der Erstveröffentlichung:2013
Organisationseinheit der BAM:1 Analytische Chemie; Referenzmaterialien
4 Material und Umwelt
4 Material und Umwelt / 4.1 Biologische Materialschädigung und Referenzorganismen
1 Analytische Chemie; Referenzmaterialien / 1.0 Abteilungsleitung und andere
Verlagsort:Washington, DC
Jahrgang/Band:53
Ausgabe/Heft:10
Erste Seite:2681
Letzte Seite:2688
Freie Schlagwörter:Affinity; Estrogenes; Modeling
DOI:https://doi.org/10.1021/ci400392p
ISSN:1549-9596
ISSN:0095-2338
ISSN:1549-960X
Verfügbarkeit des Volltexts:Volltext-PDF im Netzwerk der BAM verfügbar ("Closed Access")
Datum der Freischaltung:20.02.2016
Referierte Publikation:Ja
Datum der Eintragung als referierte Publikation:21.11.2013