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

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.

Fig 1. RMSD values of the native wild type protein along with those of the associated mutant proteins.

Fig 2. RMSF values of the native wild type protein along with those of the associated mutant protein.

Fig 3. Total energy of the NKX 2.5 protein compared to that of each mutant protein.

Fig 4. Total number of intra molecular hydrogen bond for the protein NKX 2.5 along with its reported mutations.

Fig 5. Radius of Gyration for the protein NKX 2.5 along with its associated mutations.

Fig 6. a) Secondary structure element percentage of the native wild type and mutant proteins b) SSE percentage of R161P mutant protein along with its occupancy of helices, strands, turns (orange) and loops (white) along the simulated time of 10ns with reference to the residue index.

Fig 7. Visualization of the R161P mutant NKX 2–5 protein superimposed of pre (blue) and post (red) MD structures along with snapshot of the simulation trajectory for every 1 nanosecond timescale.