<br/>Chronic myeloid leukemia (CML) is a type of blood cell cancer caused by a genetic abnormality leading to the unregulated growth of myeloid cells in the bone marrow. CML is usually treated with kinase inhibitor drugs that block the ATP binding pocket of Bcr-Abl kinase and stop aberrant cell production. We are focusing on improving the binding affinity and specificity of imatinib to Bcr-Abl kinase by analyzing avenues to decrease the electrostatic component of binding free energy through computational methods. First, we investigate the interactions between imatinib and the Abl kinase domain by employing molecular dynamics (MD) simulations to obtain a conformational ensemble of the system. Electrostatic charge optimization is then performed on a subset of ensemble snapshots to determine the hypothetical charge distribution on the drug that would maximize binding affinity using a continuum electrostatics framework. Additionally, drug moieties contributing most favorably to the electrostatic component of binding free energy are identified through component analysis. Currently, we are analyzing the robustness of this theoretical, optimal charge distribution by carrying out MD simulations with the original drug charges replaced by the optimized drug charge distribution. This allows us to explore how conformational dynamics are impacted by the optimal drug charge distribution. We plan to repeat charge optimization and component analysis using this new conformational ensemble to analyze robustness and determine whether the optimized drug indeed has a more favorable electrostatic binding affinity with the kinase after accounting for observed differences in conformational sampling. The insights into determinants of electrostatic affinity gained by these computational frameworks could aid in the development of novel, more efficacious CML therapeutics.

Computational analysis of optimal electrostatic interactions between imatinib and Abl Kinase

ACS Spring 2022

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