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QSARs for estimating intrinsic hepatic clearance of organic chemicals in humans.
Environ. Toxicol. Pharmacol. 42, 190-197 (2016)
Quantitative structure-activity relationships (QSARs) were developed to predict the in vitro clearance (CLINT) of xenobiotics metabolised in human hepatocytes (118 compounds) and microsomes (115 compounds). Clearance values were gathered from the scientific literature and multiple linear models were built and validated selecting at most 6 predictors from a pool of over 2000 potential molecular descriptors. For the hepatocytes QSAR, the explained variance (Radj(2)) was 67% and the predictive ability (Rext(2)) was 62%. For the microsomes QSAR, Radj(2) was 50% and Rext(2) 30%. For both liver assays, the most important descriptor relates to electronic properties of the compound. Functional groups of fragments were useful to identify specific compounds that have a deviating reaction rate compared to the others, such as polychlorobiphenyls (PCBs) and organic amides which were poorly metabolised by hepatocytes and microsomes, respectively. For hepatocytes, clearance was predominantly determined by electronic characteristics, while size and shape characteristics were less important and partitioning properties were absent. This may suggest that uptake across the membrane and enzyme binding are not rate-limiting steps. Particularly for hepatocytes the QSAR statistics are encouraging, allowing application of the outcomes in in vitro to in vivo extrapolation.
Impact Factor
Scopus SNIP
Web of Science
Times Cited
Times Cited
Scopus
Cited By
Cited By
Altmetric
2.187
0.949
6
12
Anmerkungen
Besondere Publikation
Auf Hompepage verbergern
Publikationstyp
Artikel: Journalartikel
Dokumenttyp
Wissenschaftlicher Artikel
Schlagwörter
Biotransformation ; Clearance (cl(int)) ; Hepatocytes ; Microsomes ; Quantitative Structure–activity Relationship; Quantitative Structure-activity; Trout Oncorhynchus-mykiss; Bioaccumulation Assessment; Polychlorinated-biphenyls; Isolated Hepatocytes; Liver-microsomes; Drug Clearance; Half-lives; Metabolism; Prediction
Sprache
englisch
Veröffentlichungsjahr
2016
HGF-Berichtsjahr
2016
ISSN (print) / ISBN
1382-6689
e-ISSN
1872-7077
Zeitschrift
Environmental Toxicology and Pharmacology
Quellenangaben
Band: 42,
Seiten: 190-197
Verlag
Elsevier
Verlagsort
Amsterdam
Begutachtungsstatus
Peer reviewed
Institut(e)
Institute of Epidemiology (EPI)
POF Topic(s)
30202 - Environmental Health
Forschungsfeld(er)
Genetics and Epidemiology
PSP-Element(e)
G-504091-003
WOS ID
WOS:000372763600024
Scopus ID
84957940922
PubMed ID
26874337
Erfassungsdatum
2016-02-20