Quantitative structure-activity relationship (QSAR) modeling of human blood: air partitioning with proper statistical methods and validation.
Blood: air partition coefficient (BApc) is important in assessing toxicokinetics of chemicals. Since very few experimental data are available, quantitative structure-activity relationship (QSAR) models based on calculated molecular descriptors can be useful in estimating BApc. Since all descriptors used in the analysis are computed strictly from structure, they can be applied to any chemical, real or hypothetical. In this article, we report models for BApc estimation using four methods, including stepwise ordinary least-squares regression, which is commonly used in QSAR studies but often results in an inflated 'naïve' q2, over-representing the predictive ability of the model. The models developed using proper statistical techniques had q2 values of 0.825 and 0.841, and may be used to reliably predict BApc values for new compounds that are structurally similar to those upon which the models are based. The models developed using improper techniques had associated q2 values, as computed using naïve methods, of 0.920 and 0.934, severely overstating their actual quality.
University of Minnesota Duluth, Natural Resources Research Institute, Center for Water and Environment, 5013 Miller Trunk Hwy, Duluth, MN 55811, USA. sbasak@nrri.umn.edu
Subhash C
SC
Basak
Denise
D
Mills
Douglas M
DM
Hawkins
Jessica J
JJ
Kraker
D006801:Humans; D008954:Models, Biological; D015233:Models, Statistical; D009930:Organic Chemicals / Q000097:blood* / Q000493:pharmacokinetics; D021281:Quantitative Structure-Activity Relationship; D012044:Regression Analysis
D009930:Organic Chemicals