Biochimica et Biophysica Acta (BBA) - General SubjectsBioinformaticsPeer-reviewed journal article
Structural effects driven by rare point mutations in amylin hormone, the type II diabetes-associated peptide
Wendy S. MendesiD, Octávio Luiz FrancoiD, Sérgio Amorim de AlencariD, William Farias PortoiD
Abstract
BackgroundAmylin is a 37-amino-acid peptide hormone co-secreted with insulin, which participates in glucose homeostasis. This hormone is able to aggregate in a {beta}-sheet conformation and deposit in islet amyloids, a hallmark in type II diabetes. Since amylin is a gene-encoded hormone, this peptide has variants caused by point mutations that can impact its functions. MethodsHere, we analyzed the structural effects caused by S20G and G33R point mutations which, according to the 1000 Genomes Project, have frequency in East Asian and European populations, respectively. The analyses were performed by means of aggrescan server, SNP functional effect predictors, and molecular dynamics. ResultsWe found that both mutations have aggregation potential and cause changes in the monomeric forms when compared with wild-type amylin. Furthermore, comparative analyses with pramlintide, an amylin drug analogue, allowed us to infer that second -helix maintenance may be related to the aggregation potential. ConclusionsThe S20G mutation has been described as pathologically related, which is in agreement with our findings. In addition, our data suggest that the G33R mutation might have a deleterious effect. The data presented here also provide new therapy opportunities, whether for creating more effective drugs for diabetes or implementing specific treatment for patients with these mutations. General SignificanceOur data could help to better understand the impact of mutations on the wild-type amylin sequence, as a starting point for the evaluation and characterization of other variations. Moreover, these findings could improve the health of patients with type II diabetes.
- organism: human
- assay: protein structure
- research focus: differential expression
- approach: statistical model
- Citations
- 5
- FWCI
- 0.70
- Field percentile
- top 33%
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