Quantitative structure-activity relationship (QSAR) modeling of human blood: Air partitioning with proper statistical methods and validation

Subhash C Basak, Denise Mills, Douglas M Hawkins, Jessica J. Kraker

Research output: Contribution to journalArticle

8 Scopus citations

Abstract

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.

Original languageEnglish (US)
Pages (from-to)487-502
Number of pages16
JournalChemistry and Biodiversity
Volume6
Issue number4
DOIs
StatePublished - May 26 2009

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