Abstract
The main idea of this work was to find predictive quantitative structure–activity relationships (QSAR) for a wide set of c-Src tyrosine kinase inhibitors, by means of resorting to a conformation-independent representation of the chemical structure. In this way, our attempt was to avoid the availability of X-ray crystallographic structural information of the target. Therefore, in a set composed of 80 pyrrolo-pyrimidine derivatives, 1179 theoretical descriptors were simultaneously analyzed through linear regression models obtained with the replacement method variable subset selection technique. Alternatively, the flexible (activity dependent) descriptor approach was also applied in this study. The models were validated and tested through the use of an external test set of compounds, the leave-group-out cross validation method, Y-randomization and applicability domain analysis. Our results were compared with previously published ones based on docking analysis and 3D-QSAR. The obtained conformation-independent approach was in good agreement with experimental observations.
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