Dhwani Raghav1, Vinay Sharma2, Subhash Mohan Agarwal3
1Bioinformatics Division, Institute of Cytology and Preventive Oncology (icmr), I-7, Sector-39, Noida-201301; Department of Bioscience and Biotechnology, Banasthali University, Rajasthan 304022, India.
2Department of Bioscience and Biotechnology, Banasthali University, Rajasthan 304022, India.
3Bioinformatics Division, Institute of Cytology and Preventive Oncology (icmr), I-7, Sector-39, Noida-201301, India.
Epidermal Growth Factor Receptor (EGFR) is a member of the receptor tyrosine kinase family, which plays a vital role in the development and progression of various cancers due to mutations in the tyrosine kinase domain (TKD). It is thus important to understand the functional significance of amino acid variation occurring within TKD due to non-synonymous Single Nucleotide Polymorphism (nsSNPs). Therefore, we have evaluated the influence of nsSNPs on the structure of EGFR-TKD using computational approaches. The present work proposes the five crucial mutational hotspots that disrupt the active conformation of EGFR-TKD and hence be responsible for causing malignancy. The study was undertaken to predict the deleterious nsSNPs in EGFR kinase domain by employing evolutionary sequence information, protein stability evaluation and molecular dynamics simulations. A total of 2493 SNPs of EGFR gene and their corresponding sequences were retrieved from the dbSNP database, out of which 41 (1.6%) were nsSNPs. The functional impact of coding nsSNPs was then evaluated by using sequence homology based method (SIFT) and structure homology based method (PolyPhen) tool. Thereafter, the stability in terms of free energy of identified mutations was calculated by three web servers CUPSAT, I-mutant2.0 and iPTree-STAB. Further, to evaluate the structural and functional impact of these mutations we performed the molecular dynamics (MD) simulation using GROMACS. To facilitate the selection of SNPs and better define the role of kinase mutations in EGFR, we undertook the analysis of 41 nsSNPs. Screening of 41 mutations led to the prediction of 13 mutants by SIFT and PolyPhen as having a potentially damaging effect on protein function. We then examined the stability of proposed mutants by computing their free energy and predicted 10 variants that are less stable than wild structure. Subsequently, we performed the 2ns molecular dynamics simulations of 5 highly unstable EGFR mutants (G719A, P733L, V742A, S768I and H773R) and identified the changes in protein conformation. The MD trajectories showed that the native EGFR is stabilized after 0.9ns while the stability of mutants is achieved after longer simulation. The RMSF profile of P-loop and A-loop shows an increased flexibility for all the mutants. We also observe that the 3 mutants (V742A, P733L and H773R) show large root mean square deviation (2.075, 2.59 and 2.752 Å respectively) compared to the native EGFR. Based on these observations we propose that these nsSNPs disrupt the conformation of EGFR-TKD. The present work suggests five novel mutations that should be selected for screening studies as they might have a significant effect on the structure of EGFR gene and thus may be responsible for causing carcinoma. Read More …