Structure and Energy-based Analyses of FGFR2 Kinase Mutations Revealing Differences in Cancer and Syndrome Mutations and Inconclusive Nature of Energy Analysis for the Mutants
Date
Authors
Sambare, Snehal Vilas
Journal Title
Journal ISSN
Volume Title
Publisher
Abstract
Fibroblast growth factor receptor 2 (FGFR2) is a protein in humans encoded by gene FGFR2. It plays an important role in the regulation of cell proliferation, differentiation, migration and apoptosis, and in the regulation of embryonic development. Mutations in FGFR2 gene are associated with numerous medical conditions that include craniosynostosis syndromes (abnormal bone development) and various cancers. In fact, FGFR2 is shown to be activated in many cancers through the mechanisms of gene amplification, translocations, and point mutations. There remains many FGFR2 mutations whose effects are unknown. In this work we have investigated point mutations in FGFR2 kinase. We have performed region-based analysis wherein we mapped mutations to various domains of protein and performed Shannon entropy analysis on the mutant positions. BLOSUM matrix values were also obtained for the mutations to get insights about differences in amino acids substitution for cancer and syndromes. Structure energy-based analysis was performed using FoldX, a protein design algorithm. Statistical analysis like Normality tests, T-tests, Mann-Whitney-Wilcoxon Tests were performed on the energy values obtained from FoldX, and histograms were generated. This analysis makes the following contributions. The region-based analysis shows that cancer causing mutations are distributed across all regions, whereas syndrome causing mutations are not uniformly distributed across all domains. The BLOSUM analysis reveals that in cancer causing mutations substitution takes place between amino acids with similar physicochemical properties, whereas in syndrome causing mutations all types of amino acids can be substituted. The structure-energy based, and statistical analysis shows that cancer causing and syndrome causing mutations have identical energy distributions, indicating that energy cannot be used as predictor for differentiating cancer causing and syndromes causing mutants in FGFR2. The results of histogram analysis are inconclusive. In summary, this study has provided interesting insights that can be helpful for further research of FGFR2 kinase mutations.
Description
Keywords
FGFR2 kinase, Cancer, Syndrome, FoldX analysis