Correlated Motions and Dynamics in Different Domains of Epidermal Growth Factor Receptor with L858R and T790M Mutations

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

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Detail(s)

Original languageEnglish
Pages (from-to)383-394
Journal / PublicationIEEE/ACM Transactions on Computational Biology and Bioinformatics
Volume19
Issue number1
Online published18 May 2020
Publication statusPublished - Jan 2022

Abstract

Non-small cell lung cancer with an activating epidermal growth factor receptor (EGFR) mutation responds well to targeted drugs. In most cases, drug resistance appears after about a year. Several studies have been conducted on the kinase domain of EGFR to understand the drug resistance mechanism. Since EGFR is a multi-domain protein, mutation in the kinase domain may affect the other domains as well. In this study, we examine the complete structure of the multi-domain EGFR protein and its mutants. We performed molecular dynamics simulations for wildtype EGFR, EGFR with L858R mutation, and EGFR with L858R and T790M mutations. We applied normal mode analysis and complex network analysis to extract the correlated motions in the domains of EGFR. The normal modes are used to construct the dynamic cross-correlation map (DCCM). Simulation results show different patterns of correlated motions in each domain of EGFR mutants compared to the wildtype. In Domains 1 and 3 of the extracellular region, a small number of weak positively correlated motions are extracted. Domains 2 and 4 show large numbers of both positive and negative motions. However, the negatively correlated motions are stronger in mutant structures compared to the wildtype. In Domain 7, some residues showed a positive correlation around the main diagonal. We also identified different communities, nodes and crucial residues in the domains of the structures, which can be important for the function of EGFR. Moreover, hydrogen bond analysis is performed for the stability analysis. The mutant structures have fewer hydrogen bonds compared to the wildtype. Overall, these findings are useful for understanding the dynamics and communications in EGFR domains.

Research Area(s)

  • Epidermal growth factor receptor, mutations, drug resistance, dynamic cross-correlation maps, community network analysis, hydrogen bond analysis

Citation Format(s)

Correlated Motions and Dynamics in Different Domains of Epidermal Growth Factor Receptor with L858R and T790M Mutations. / Qureshi, Rizwan; Ghosh, Avirup; Yan, Hong.
In: IEEE/ACM Transactions on Computational Biology and Bioinformatics, Vol. 19, No. 1, 01.2022, p. 383-394.

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review