Molecular Matchmaking: A Computational Study of the Electrostatic Interaction Between Chronic Myeloid Leukemia Drugs and Bcr-Abl Oncoprotein

In this project, we systematically use several computational techniques such as charge optimization and component analysis to study molecular recognition and binding in the chronic myeloid leukemia (CML) drug systems. Using CML drugs and their biological target, the BcrAbl oncoprotein, we systematically conduct a comparative analysis on five CML drugs bound to both the wild-type (WT) and T315I mutant Abl kinase. While early generation drugs (imatinib, nilotinib, and dasatinib) interact with Thr315 via a hydrogen bond, novel drugs ponatinib and PPY-A bypass interacting with Thr315 altogether. With the mutation to Ile at position 315, early generation drugs may experience a significant loss in favorable binding due to loss of electrostatic interaction and introduction of steric hindrance. To investigate the differential binding of these drugs to the WT and mutant, we optimize each of the drugs to the Abl kinase, allowing us to study how each drug binds to the native form. We also optimize PPY-A and ponatinib to the mutant T315I, comparing this charge distribution with the one generated from optimizing to the native form. Using component analysis, we identify chemical moieties of each drug that contribute favorably or unfavorably to the electrostatic free energy of binding. Taken together, we hope that by studying CML drugs, we will gain some insight into the larger picture of electrostatic binding interaction and potentially provide future direction for rational drug design and battling drug resistance.