Predictive models for designing potent tyrosine kinase inhibitors in chronic myeloid leukemia for understanding its molecular mechanism of resistance by molecular docking and dynamics simulations.

BCR-ABL fusion protein drives chronic myeloid leukemia (CML) which constitutively activates tyrosine kinase involved in the initiation and maintenance of CML phenotype. Ponatinib, an oral drug, was discovered as an efficient BCR-ABL inhibitor by addressing imatinib drug resistance arising due to the point mutations at its active sites. In this study, 44 BCR-ABL kinase inhibitors, which are derivatives of ponatinib, were used to develop a robust two-dimensional quantitative structure-activity relationship (2D-QSAR) and 3D-Pharmacophore models by dividing dataset into 32 training sets and 12 test set molecules. 2D-QSAR model was developed using Genetic Function Approximation (GFA) algorithm consisting of four types of information-rich molecular descriptors, electrotopological (ES_Count_aasN and ES_Sum_aaaC), electronic (Dipole_