Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/144576
Title: Effects of single nucleotide polymorphisms on the binding of afatinib to EGFR : a potential patient stratification factor revealed by modeling studies
Authors: Kannan, Srinivasaraghavan
Tan, Daniel Shao-Weng
Verma, Chandra Shekhar
Keywords: Science::Biological sciences
Issue Date: 2018
Source: Kannan, S., Tan, D. S.-W., & Verma, C. S. (2019). Effects of Single Nucleotide Polymorphisms on the Binding of Afatinib to EGFR: A Potential Patient Stratification Factor Revealed by Modeling Studies. Journal of Chemical Information and Modeling, 59(1), 309–315. doi:10.1021/acs.jcim.8b00491
Journal: Journal of chemical information and modeling
Abstract: The anticancer drug afatinib has been found to be more effective at inhibiting the oncogenic EGFR mutant exon 19 deletion (19del) over the oncogenic EGFR mutant L858R. The underlying mechanism has been hypothesized to result from differences in structural constraints introduced by the mutations and stabilizing interactions afforded by a buried water molecule in 19del (Kannan, S.; et al. Sci. Rep. 2017, 7, 1540). The COSMIC cancer database is mined for EGFR sequences to discover that several mutations in the form of Single nucleotide polymorphisms (SNPs) line this hydration cavity. In this work, the effects of these SNPs on the affinity of afatinib for EGFRWT and oncogenic mutants EGFRL858R and EGFR19del were studied using free energy perturbation and thermodynamic Integration calculations. The simulations reveal that several SNPs have significant effects on the affinity of afatinib for the mutant EGFRs carrying the SNPs and may thus have clinical implications relating to emergence of resistance to afatinib, thus potentially impacting the choice of EGFR inhibitors in the clinic.
URI: https://hdl.handle.net/10356/144576
ISSN: 1549-9596
DOI: 10.1021/acs.jcim.8b00491
Rights: This document is the Accepted Manuscript version of a Published Work that appeared in final form in Journal of chemical information and modeling, copyright © American Chemical Society after peer review and technical editing by the publisher. To access the final edited and published work see https://doi.org/10.1021/acs.jcim.8b00491
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:SBS Journal Articles

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