Publication Type:

Journal Article


Journal of Biomolecular Structure and Dynamics, Taylor and Francis Ltd. (2018)



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_X), spatial (PMI_Y) and thermodynamic (LogD), primarily contributing to BCR-ABL kinase inhibitory activity. For the best 2D-QSAR model, the statistics were R 2 = 0.8707, R 2 pred = 0.8142 and N = 32 for the training set molecules. Phase module of Schrödinger suit was employed for 3D-Pharmacophore model development showing five different pharmacophoric features–ADHHPRR with good R 2 of 0.9629, F of 175.3, Q 2 of 0.645 and root-mean-square error (RMSE) of 0.214 that are essential for an effective BCR-ABL kinase inhibition. These two models were further validated by cross-validation, test set predictions, enrichment factor calculations and predictions based on the external dataset. The molecular mechanism of resistance arising due to gate keeper mutation T315I of ABL kinase in complex with its inhibitors was also studied using molecular docking and molecular dynamics simulations. Our developed models predicted key chemical features for designing potent inhibitors against BCR-ABL kinase activity and its resistance mechanism to CML disease therapy. Communicated by Ramaswamy H. Sarma. © 2019, © 2019 Informa UK Limited, trading as Taylor & Francis Group.


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Cite this Research Publication

A. R. Melge, Kumar, L. G., Pavithran, K., Shantikumar V Nair, Dr. Manzoor K., and Dr. Gopi Mohan C., “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”, Journal of Biomolecular Structure and Dynamics, 2018.