Impact of Orthogonal Signal Correction (OSC) on the predictive ability of CoMFA models for the ciliate toxicity of nitrobenzenes

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Authors	BOHÁČ Michal LOEPRECHT Bjorn DAMBORSKÝ Jiří SCHUURMANN Gerrit
Year of publication	2002
Type	Article in Periodical
Magazine / Source	Quantitative Structure-Activity Relationships
MU Faculty or unit	Faculty of Science
Citation
Web	http://ncbr.chemi.muni.cz/~jiri/ABSTRACTS/qsarj02.html
Field	Microbiology, virology
Keywords	QSAR; VALIDATION; COMFA; GOLPE; VARIABLE SELECTION
Description	The impact of orthogonal signal correction (OSC) on the prediction power of CoMFA models was studied using a data set of 47 nitrobenzenes with toxicities (log 1/IC50) towards the aquatic ciliates Tetrahymena pyriformis. Comparative analyses of different data pre-treatments shows that block unscaled weighting (BUW) results in significantly better PLS models than no scaling, centering or autoscaling for OSC. One OSC component is optimal for the signal correction and reduces the X variance by about 40%. While OSC yields improved calibration and cross-validation statistics, standard CoMFA is superior with respect to the external prediction power as evaluated by models built from complementary subsets. Moreover, external prediction reveals some cases of severe OSC overfitting, which needs attention in future investigations.
Related projects:	Rational re-design of microbial enzymes involved in degradation of toxic organic pollutants. Biomolecular Structure-function Relationships and their role in the Metabolism