IMPACT OF DELETERIOUS NON-SYNONYMOUS SINGLE NUCLEOTIDE POLYMORPHISMS OF CYTOKINE GENES ON NON-CLASSICAL HYDROGEN BONDS PREDISPOSING TO CARDIOVASCULAR DISEASE: AN IN SILICO APPROACH
DOI:
https://doi.org/10.22159/ajpcr.2017.v10i11.19531Keywords:
Cardiovascular disease, Interleukin 6, Nil, Non-synonymous single nucleotide polymorphisms, Cation-Pi analysisAbstract
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 Objective: Cardiovascular disease (CVD) is a leading cause of death worldwide. Malfunctioning of genes that are responsible for several inflammatory processes is the major cause for its initiation. Cytokine genes are one such group of genes that are involved in the development of CVD. Hence, the prediction of potential point mutations in these genes is important for diagnostic purposes. Such mutations result in altered protein structure and function when compared to neutral ones.
Methods: In this study, interleukin factor 6 (IL6), tumor necrosis factor α (TNF-α), interleukin factor 4 (IL4), and interferon gamma have been analyzed using sorting intolerant from tolerant and PolyPhen 2.0 tools.
Results: Several single nucleotide polymorphisms (SNPs), in IL6, TNF-α, and IL4, are found to be potentially deleterious. In addition, bond analysis has also been performed on these SNPs. It has been predicted that L119P and R196H of IL6 as well as K87T and T181N of TNF-α are potential ns-SNP's that may cause structural and functional variations in the corresponding proteins. The hydrogen and Cation-Pi bond analysis performed in this study provides molecular-based evidence that support the predicted deleterious potential of such SNPs for these CVD candidate genes along with other conventional in silico tools.
Conclusion: The study testifies the importance of adopting a computational approach to narrow down potential point mutants for disease predictions.
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Objective: Cardiovascular disease (CVD) is a leading cause of death worldwide. Malfunctioning of genes that are responsible for several inflammatory processes is the major cause for its initiation. Cytokine genes are one such group of genes that are involved in the development of CVD. Hence, the prediction of potential point mutations in these genes is important for diagnostic purposes. Such mutations result in altered protein structure and function when compared to neutral ones.
Methods: In this study, interleukin factor 6 (IL6), tumor necrosis factor α (TNF-α), interleukin factor 4 (IL4), and interferon gamma have been analyzed using sorting intolerant from tolerant and PolyPhen 2.0 tools.
Results: Several single nucleotide polymorphisms (SNPs), in IL6, TNF-α, and IL4, are found to be potentially deleterious. In addition, bond analysis has also been performed on these SNPs. It has been predicted that L119P and R196H of IL6 as well as K87T and T181N of TNF-α are potential ns-SNP’s that may cause structural and functional variations in the corresponding proteins. The hydrogen and Cation-Pi bond analysis performed in this study provides molecular-based evidence that support the predicted deleterious potential of such SNPs for these CVD candidate genes along with other conventional in silico tools.
Conclusion: The study testifies the importance of adopting a computational approach to narrow down potential point mutants for disease predictions.
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