Analysis of the co-evolutions of correlations as a tool for QSAR-modeling of carcinogenicity: an unexpected good prediction based on a model that seems untrustworthy

Abstract

To validate QSAR models an external test set is increasingly used. However the definition of the compounds for the test set is still debated. We studied, co-evolutions of correlations between optimal descriptors and carcinogenicity (pTD50) for the subtraining, calibration, and test set. Weak correlations for the sub-training set are sometimes accompanied by quite good correlations for the external test set. This can be explained in terms of the probability theory and can help define a suitable test set. The simplified molecular input line entry system (SMILES) was used to represent the molecular structure. Correlation weights for calculating the optimal descriptors are related to fragments of the SMILES. The statistical quality of the model is: n=170, r²=0.6638, q²=0.6554, s=0.828, F=331 (sub-training set); n=170, r²=0.6609, r² _pred=0.6520, s=0.825, F=331 (calibration set); and n=61, r²=0.7796, r² _pred=0.7658, R_m ²=0.7448, s=0.563, F=221 (test set). The calculations were done with CORAL software (http://www.insilico.eu/coral/).