Quantitative Structure-Activity Relationship (QSAR) Modeling of Human Blood: Air Partitioning with Proper Statistical Methods and Validation

被引:8
作者
Basak, Subhash C. [1 ]
Mills, Denise [1 ]
Hawkins, Douglas M. [2 ]
Kraker, Jessica J. [3 ]
机构
[1] Univ Minnesota, Nat Resources Res Inst, Ctr Water & Environm, Duluth, MN 55811 USA
[2] Univ Minnesota Twin Cities, Sch Stat, Minneapolis, MN 55455 USA
[3] Univ Wisconsin, Dept Math, Eau Claire, WI 54701 USA
关键词
CHEMOMETRICS REGRESSION TOOLS; TOPOLOGICAL INDEXES; PREDICTING BLOOD; COEFFICIENTS; TISSUE; VIEW; MUTAGENICITY;
D O I
10.1002/cbdv.200800111
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
Blood :air partition coefficient (BA(pc)) 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 BA(pc) Since all descriptors used in the analysis are computed strictly from structure, they can be applied to my chemical, real or hypothetical. In this article, we report models for BA(pc) estimation using four methods, including stepwise ordinary least-squares regression, which is commonly used in QSAR studies but often results in an inflated 'naive' q(2), over-representing the predictive ability of the model. The models developed using proper statistical techniques had q(2) values of 0.825 and 0.841, and may be used to reliably predict BA, values for new compounds that are structurally similar to those upon which the models are based. The models developed using improper techniques had associated q(2) values, as computed using naive methods, of 0.920 and 0.934, severely overstating their actual quality.
引用
收藏
页码:487 / 502
页数:16
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