QSAR Classification of Anticancer Heterocyclichydrazones with Reactivity Descriptors

Abstract

In this study, validated PLS-DA models that discriminate heterocyclichydrazones with potentanticancer activity (GI50/IC50<50x10-6M) from those with low activity (GI50/IC50>=50x10-6M) against the cancer cell lines HCT-116 (colon), OVCAR-8 (human ovary), HL-60 (leukemia),and SF-295 (glioblastoma) were developed. A dataset of 24-a-(N)-heterocyclichydrazones and 14N-acylhydrazonyl-thienyl and various global and local reactivity descriptors were used for modeling.The best models classified for training and test sets with an accuracy range between 67-100%, aclass specificity and sensitivity range between 71-100%, error rate range between 0-0.27, and nonerrorrate range between 0.73-1.0. An external set of 20 compounds was predicted and the modelsshowed which new compounds are not suggested for further biological investigation. The molecularproperties with impact on the modeled endpoints show that the antitumor activity can be improvedwith electron-acceptor N-acylhydrazonyl-thienyl derivatives and a-(N)-heterocyclichydrazones withmoderate electron-donating character.