Coupled Solvent and Protein Dynamics Confer Differences in Exon-19 Deletion Mutants of the Epidermal Growth Factor Receptor Kinase

Abstract

Deletions in Exon-19 of the epidermal growth factor receptor (EGFR) play a pivotal role in the pathogenesis of non-small cell lung cancer (NSCLC), influencing patient response to tyrosine kinase inhibitors (TKIs). Although these mutations are known to affect treatment efficacy, the precise molecular mechanisms have been unclear. Building upon recent insights from the study [DOI: 10.1038/s41467-022-34398-z], which identified two distinct mutation profiles associated with differential drug sensitivity and clinical outcomes, our research delves into the molecular dynamics that drive these variances. We employed molecular dynamics simulations, enhanced sampling methods, and machine learning to classify Exon-19 deletion mutations into two profiles based on their conformational dynamics. Profile 1 mutations display only localized motions in key subdomains in their fluctuations about the equilibrium state, and a high affinity for ATP and consequent resistance to TKIs, while profile 2 mutations show reduced ATP binding affinity due to delocalized motion characterized by an increased flexibility between the N- and C-lobes of the EGFR kinase domain. This structural flexibility perturbs the ATP binding site, leading to decreased affinity and, heightened sensitivity to TKIs. Our use of the INDirect Umbrella Sampling (INDUS) technique has shed light on the collective solvent dynamics, further elucidating the coupling between long timescale solvent fluctuations and protein conformational dynamics, that likely contributes to the observations in HDX-MS studies. Our free energy analysis, covering timescales relevant to both HDX-MS and ligand interaction, provides a deeper understanding of the relationship between protein and solvent dynamics and their collective impact on drug efficacy in NSCLC with EGFR Exon-19 deletions. Significance StatementEGFR Exon 19 deletion mutations are key drivers in non-small cell lung cancer (NSCLC), yet their drug sensitivity to tyrosine kinase inhibitors (TKIs) varies significantly. This study identifies two mutation profiles: mutations that exhibit high ATP binding affinity and localized conformational motion, driving TKI resistance, and mutations that show reduced ATP affinity due to delocalized structural flexibility, enhancing TKI sensitivity. Using molecular dynamics simulations and free energy sampling techniques, we reveal how solvent fluctuations and protein dynamics collectively affect drug binding and efficacy. These findings provide a mechanistic basis for differential drug sensitivity, informing precision medicine strategies for NSCLC patients with EGFR Exon-19 mutations.