Modelling the cytotoxic activity of pyrazolo-triazole hybrids using descriptors calculated from the open source tool “PaDEL-descriptor”

In this study, we developed QSAR models for the anti-proliferative activity of pyrazolo-triazole hybrids [(1-benzyl-1H-1,2,3-triazol-4-yl)(1,3-diphenyl-1H-pyrazol-4-yl) methanone] on human brain cancer (U87MG), lung cancer (A549), prostate cancer (PC-3), and colon cancer (HT-29) cell lines. We employed K-means cluster analysis to split the data sets. Statistically robust models were generated [pIC50 (U87MG): R = 0.873, Q2 = 0.554, Rpred2=0.866; pIC50 (A549): R = 0.879, Q2 = 0.637, Rpred2=0.858; pIC50 (PC3): R = 0.953; Q2 = 0.850; Rpred2=0.796; pIC50 (HT-29): R = 0.962, Q2 = 0.891; Rpred2=0.707]. The reliability of these models was confirmed by acceptable validation parameters, and these models also satisfied the Golbraikh and Tropsha acceptable model criteria. The QSAR study highlighted the atomic feature and molecular descriptors, information content descriptors, and topological and constitutional descriptors that affect anti-cancer activity.