Publication Type:

Journal Article

Source:

J Biomol Struct Dyn, p.1-68 (2018)

Abstract:

<p>BCR-ABL fusion protein drives chronic myeloid leukaemia (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 2D-QSAR and 3D-Pharmacophore models by dividing dataset into 32 training set 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, electro-topological (ES_Count_aasN and ES_Sum_aaaC), electronic (Dipole_X), spatial (PMI_Y) and thermodynamic (Log D), primarily contributing to BCR-ABL kinase inhibitory activity. For best 2D-QSAR model, the statistics were R =0.8707, R =0.8142, 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 0.9629, F 175.3, Q 0.645 and 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 data set. 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.</p>

Cite this Research Publication

A. R. Melge, Kumar, L. G., K, P., Nair, S. V., K, M., and C Mohan, G., “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.”, J Biomol Struct Dyn, pp. 1-68, 2018.