Structural impact analysis of missense SNPs present in the uroguanylin gene by long-term molecular dynamics simulations. (7th December 2016)

• Record Type: Journal Article
• Authors: Marcolino, Antonio C.S.; Porto, William F.; Pires, Állan S.; Franco, Octavio L.; Alencar, Sérgio A.
• Is Part Of: Journal of theoretical biology. Volume 410(2016)
• Page Start: 9
• Page End: 17
• Publication Date: 2016-12-07
• Subjects: Uroguanylin -- Missense SNPs -- Molecular dynamics -- Structural impact; Biology -- Periodicals; Biological Science Disciplines -- Periodicals; Biology -- Periodicals; Biologie -- Périodiques; Theoretische biologie; Biology; Periodicals; 571.05
• DOI: 10.1016/j.jtbi.2016.09.008
• Languages: English
• ISSNs: 0022-5193

Abstract

Abstract: The guanylate cyclase activator 2B, also known as uroguanylin, is part of the guanylin peptide family, which includes peptides such as guanylin and lymphoguanylin. The guanylin peptides could be related to sodium absorption inhibition and water secretion induction and their dysfunction may be related to various pathologies such as chronic renal failure, congestive heart failure and nephrotic syndrome. Besides, uroguanylin point mutations have been associated with essential hypertension. However, currently there are no studies on the impact of missense SNPs on uroguanylin structure. This study applied in silico SNP impact prediction tools to evaluate the impact of uroguanylin missense SNPs and to filter those considered as convergent deleterious, which were then further analyzed through long-term molecular dynamics simulations of 1 μs of duration. The simulations suggested that all missense SNPs considered as convergent deleterious caused some kind of structural change to the uroguanylin peptide. Additionally, four of these SNPs were also shown to cause modifications in peptide flexibility, possibly resulting in functional changes. Highlights: The impact of missense SNPs on the GUCA2B protein was predicted by in silico tools. Seven convergent deleterious SNPs were further analyzed by long-term MD simulations. Four SNPs could cause major damage to the protein on a structural level.