A Comprehensive In Silico Analysis on the Structural and Functional Impact of SNPs in the Congenital Heart Defects Associated with NKX2-5 Gene-A Molecular Dynamic Simulation Approach.

Firoz Abdul Samad,Thamilarasan Manivasagam,Bandar A Suliman,Musthafa Mohamed Essa,Syed Hussain Basha,John Lynn Jefferies

doi:10.1371/journal.pone.0153999

Abstract

Congenital heart defects (CHD) presented as structural defects in the heart and blood vessels during birth contribute an important cause of childhood morbidity and mortality worldwide. Many Single nucletotide polymorphisms (SNPs) in different genes have been associated with various types of congenital heart defects. NKX 2–5 gene is one among them, which encodes a homeobox-containing transcription factor that plays a crucial role during the initial phases of heart formation and development. Mutations in this gene could cause different types of congenital heart defects, including Atrial septal defect (ASD), Atrial ventricular block (AVB), Tetralogy of fallot and ventricular septal defect. This highlights the importance of studying the impact of different SNPs found within this gene that might cause structural and functional modification of its encoded protein. In this study, we retrieved SNPs from the database (dbSNP), followed by identification of potentially deleterious Non-synonymous single nucleotide polymorphisms (nsSNPs) and prediction of their effect on proteins by computational screening using SIFT and Polyphen. Furthermore, we have carried out molecular dynamic simulation (MDS) in order to uncover the SNPs that would cause the most structural damage to the protein altering its biological function. The most important SNP that was found using our approach was rs137852685 R161P, which was predicted to cause the most damage to the structural features of the protein. Mapping nsSNPs in genes such as NKX 2–5 would provide valuable information about individuals carrying these polymorphisms, where such variations could be used as diagnostic markers.

Highlights

Single nucleotide polymorphisms (SNPs) are the most common genetic variations in any population; they occur when a single nucleotide in the genome (A, T, C or G) is altered [1]
It was noted that the vast majority of Single nucletotide polymorphisms (SNPs) of this gene fall in the coding region, and the number of Nonsynonymous single nucleotide polymorphisms (nsSNPs) were higher than all the other types of SNPs
Among the 65 nsSNPs selected for further analysis, 24 were predicted to be deleterious by the Sorting intolerant from tolerant (SIFT) server with a tolerant index score less than or equal to 0.03 and the detailed result has been tabulated in S1 Table

Summary

Introduction

Single nucleotide polymorphisms (SNPs) are the most common genetic variations in any population; they occur when a single nucleotide in the genome (A, T, C or G) is altered [1]. Even though many SNP's have no effect on the biological functions of the cell, some can predispose people to certain diseases, influence their immunological response to drugs and can be considered as biomarkers for disease susceptibility [2]. NsSNPs result in changes to the amino acid sequence of proteins and have been reported to be responsible for about 50% of all known genetic variations that are linked to inherited diseases [3]. Even though the influence of genetics on susceptibility to cardiovascular diseases is well documented, delineation of the complete spectrum of the risk alleles was not achieved previously until the development of Generation Sequencing Techniques [6]. Because of the availability of such sequencing data from many databases, researchers have turned to bioinformatics tools to exploit these data and try to annotate and extract useful clinical information hidden within

Methods

Results

Conclusion