SMILES‐Based QSAR Models for the Calcium Channel‐Antagonistic Effect of 1,4‐Dihydropyridines

The activity of 72 1,4‐dihydropyridines as calcium channel antagonists was examined. The simplified molecular input‐line entry system (SMILES) was used as representation of the molecular structure of the calcium channel antagonists. Quantitative structure–activity relationships (QSARs) were developed using CORAL software ( http://www.insilico.eu/CORAL ) for four random splits of the data into the training and test sets. Using the Monte Carlo method, the CORAL software generated the optimal descriptors for one‐variable models. The reproducibility of each model was tested performing three runs of the Monte Carlo optimization. The obtained results reveal good predictive potential of the applied approach: The correlation coefficients (r²) for the test sets of the four random splits are 0.9571, 0.9644, 0.9836, and 0.9444.