Computational Analysis of Structural Dynamics of EGFR and its Mutants

Abstract

Non-small cell lung cancer (NSCLC) with activating epidermal growth factor receptor (EGFR) is a major cause of death worldwide. Tyrosine kinase inhibitors (TKIs) have been developed to target the EGFR, stop the downstream signaling and the tumor growth. Despite of initial good results, drug resistance is developed after one year due to a secondary mutation. The L858R, T790M mutation and their combination change the conformational redistribution of EGFR. To combat drug resistance caused by the T790M mutation, AZD9291 third generation drug was approved by the food and drug administration agency, FDA, USA. However, resistance to AZD9291 is developed due to C797S mutation. In this paper, we investigate the drug resistance due to these genomic variations. We perform molecular dynamics (MD) simulation for EGFR, EGFR with L858R single point mutation, EGFR with L858R and T790M double point mutation and EGFR with L858R, T790M and C797S triple point mutation. We apply principal component analysis PCA and clustering to the atomic trajectories of EGFR and its mutants and extract the dominant motions. The first PC captures 29.04%, 51.17% 53.79% and 51.67% variance in WT, L858R, T790M and C797S mutants, respectively. First 20 PCs are used to explain the dynamics of the system, that captures about 90% of the variance in the system. This shows that the mutation increases the variance which leads to structural and dynamical changes and can be one of the reasons for the drug resistance. Our results provide new insights to the conformational dynamics and structural changes in EGFR and its mutants, that can be helpful for understanding the drug resistance mechanism and designing future therapies for NSCLC patients.