Computational Analysis of KRAS Mutations: Implications for Different Effects on the KRAS p.G12D and p.G13D Mutations

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Abstract

Background: The issue of whether patients diagnosed with metastatic colorectal cancer who harbor KRAS codon 13 mutations could benefit from the addition of anti-epidermal growth factor receptor therapy remains under debate. The aim of the current study was to perform computational analysis to investigate the structural implications of the underlying mutations caused by c.38G>A (p.G13D) on protein conformation. Methods: Molecular dynamics (MD) simulations were performed to understand the plausible structural and dynamical implications caused by c.35G>A (p.G12D) and c.38G>A (p.G13D). The potential of mean force (PMF) simulations were carried out to determine the free energy profiles of the binding processes of GTP interacting with wild-type (WT) KRAS and its mutants (MT). Results: Using MD simulations, we observed that the root mean square deviation (RMSD) increased as a function of time for the MT c.35G>A (p.G12D) and MT c.38G>A (p.G13D) when compared with the WT. We also observed that the GTP-binding pocket in the c.35G>A (p.G12D) mutant is more open than that of the WT and the c.38G>A (p.G13D) proteins. Intriguingly, the analysis of atomic fluctuations and free energy profiles revealed that the mutation of c.35G>A (p.G12D) may induce additional fluctuations in the sensitive sites (P-loop, switch I and II regions). Such fluctuations may promote instability in these protein regions and hamper GTP binding. Conclusions: Taken together with the results obtained from MD and PMF simulations, the present findings implicate fluctuations at the sensitive sites (P-loop, switch I and II regions). Our findings revealed that KRAS mutations in codon 13 have similar behavior as KRAS WT. To gain a better insight into why patients with metastatic colorectal cancer (mCRC) and the KRAS c.38G>A (p.G13D) mutation appear to benefit from anti-EGFR therapy, the role of the KRAS c.38G>A (p.G13D) mutation in mCRC needs to be further investigated. © 2013 Chen et al.

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Chen, C. C., Er, T. K., Liu, Y. Y., Hwang, J. K., Barrio, M. J., Rodrigo, M., … Herreros-Villanueva, M. (2013). Computational Analysis of KRAS Mutations: Implications for Different Effects on the KRAS p.G12D and p.G13D Mutations. PLoS ONE, 8(2). https://doi.org/10.1371/journal.pone.0055793

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