Metabolic biotransformation half-lives in fish: QSAR modeling and consensus analysis.
Bioaccumulation in fish is a function of competing rates of chemical uptake and elimination. For hydrophobic organic chemicals bioconcentration, bioaccumulation and biomagnification potential are high and the biotransformation rate constant is a key parameter. Few measured biotransformation rate constant data are available compared to the number of chemicals that are being evaluated for bioaccumulation hazard and for exposure and risk assessment. Three new Quantitative Structure-Activity Relationships (QSARs) for predicting whole body biotransformation half-lives (HLN) in fish were developed and validated using theoretical molecular descriptors that seek to capture structural characteristics of the whole molecule and three data set splitting schemes. The new QSARs were developed using a minimal number of theoretical descriptors (n=9) and compared to existing QSARs developed using fragment contribution methods that include up to 59 descriptors. The predictive statistics of the models are similar thus further corroborating the predictive performance of the different QSARs; Q(2)ext ranges from 0.75 to 0.77, CCCext ranges from 0.86 to 0.87, RMSE in prediction ranges from 0.56 to 0.58. The new QSARs provide additional mechanistic insights into the biotransformation capacity of organic chemicals in fish by including whole molecule descriptors and they also include information on the domain of applicability for the chemical of interest. Advantages of consensus modeling for improving overall prediction and minimizing false negative errors in chemical screening assessments, for identifying potential sources of residual error in the empirical HLN database, and for identifying structural features that are not well represented in the HLN dataset to prioritize future testing needs are illustrated.
QSAR Research Unit in Environmental Chemistry and Ecotoxicology, Department of Theoretical and Applied Sciences, University of Insubria, Varese, Italy. Electronic address: ester.papa@uninsubria.it.
Ester
E
Papa
REACH Mastery, Via Giovio 16, 22100 Como, Italy.
Leon
L
van der Wal
ARC Arnot Research & Consulting, 36 Sproat Avenue, Toronto, ON, Canada; Department of Physical and Environmental Science, University of Toronto Scarborough, Toronto, ON, Canada.
Jon A
JA
Arnot
QSAR Research Unit in Environmental Chemistry and Ecotoxicology, Department of Theoretical and Applied Sciences, University of Insubria, Varese, Italy.
Paola
P
Gramatica
D000818:Animals; D001711:Biotransformation; D005399:Fishes / Q000378:metabolism*; D006207:Half-Life; D008954:Models, Biological; D008956:Models, Chemical; D009930:Organic Chemicals / Q000737:chemistry / Q000378:metabolism*; D021281:Quantitative Structure-Activity Relationship; D018570:Risk Assessment; D014874:Water Pollutants, Chemical / Q000737:chemistry / Q000378:metabolism*
D009930:Organic Chemicals; D014874:Water Pollutants, Chemical
Biotransformation rate; Chemical prioritization; Consensus modeling; Metabolic half-life; QSAR; Risk assessment