In silico prediction, molecular modeling, and dynamics studies on the targeted next-generation sequencing identified genes underlying congenital heart disease in Down syndrome patients - Fiona Hannah Carlus; L Balasubramaniam Sujatha; Anbazhagan Ganesh Kumar; Lakshmanan Loganathan; Karthikeyan Muthusamy; Silas Justin Carlus (Wolters Kluwer Medknow Publications, 2023)
Background : Individuals with Down syndrome (DS) have a 40%-60% chance of being born with congenital heart disease (CHD). This indicates that CHD in individuals with DS is not solely caused by trisomy 21, and there may be other genetic factors contributing to the development of CHD in these children. A study has identified variants in the specific genes that contribute to the pathogenesis of CHD in children with DS, isolated DS, and the CHD group. Computational studies on these identified variants, which, together with trisomy 21, determine the risk for CHD in DS cases, were limited. Here, we aimed to identify the impact of the identified variants that contribute to the pathogenesis of CHD in children with DS through in silico prediction, molecular modeling, and dynamics studies. Methodology and Results : The target single-nucleotide polymorphisms included in the study were examined for pathogenicity, residue conservation, and protein structural changes. The structural predictions were done using I-TASSER, Robetta, SWISS-MODEL, and Phyre2 tools. Further, the predicted models were validated through the PROCHECK server and molecular dynamics simulation using GROMACS software. The conservation analysis conducted on the identified variant highlights its significance in relation to the genetic disorders. Furthermore, a dynamics simulation study revealed the impact of the variant on protein structural stability (≤3 Å), providing valuable insights into its pathogenicity. We have also observed that the structure of the centrosomal protein of 290 kDa gene is relatively unstable, which may be attributed to its exclusive inclusion of helices within its secondary structural components. Conclusions : This computational study explores, for the first time, the association between genes and CHD-DS, evaluating the identified specific frameshift variants. The observed pathogenic mutations in CHD-DS patients require further experimental validation and may contribute to the development of prospective drug design research. The insights gained from the structural and functional implications of these variants could potentially serve as a cornerstone in the development of effective treatments for this debilitating condition.