Original Paper

Journal of Molecular Modeling

, Volume 19, Issue 9, pp 3517-3527

First online:

In silico discrimination of nsSNPs in hTERT gene by means of local DNA sequence context and regularity

  • C. George Priya DossAffiliated withMedical Biotechnology Division, School of Biosciences and Technology, VIT University Email author 
  • , Chiranjib ChakrabortyAffiliated withDepartment of Bio-informatics, School of Computer and Information Sciences, Galgotias University
  • , B. RajithAffiliated withMedical Biotechnology Division, School of Biosciences and Technology, VIT University
  • , N. NagasundaramAffiliated withMedical Biotechnology Division, School of Biosciences and Technology, VIT University

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Abstract

Understanding and predicting the significance of novel genetic variants revealed by DNA sequencing is a major challenge to integrate and interpret in medical genetics with medical practice. Recent studies have afforded significant advances in characterization and predicting the association of single nucleotide polymorphisms in human TERT with various disorders, but the results remain inconclusive. In this context, a comparative study between disease causing and novel mutations in hTERT gene was performed computationally. Out of 59 missense mutations, five variants were predicted to be less stable with the most deleterious effect on hTERT gene by in silico tools, in which two mutations (L584W and M970T) were not previously reported to be involved in any of the human disorders. To get insight into the structural and functional impact due to the mutation, docking study and interaction analysis was performed followed by 6 ns molecular dynamics simulation. These results may provide new perspectives for the targeted drug discovery in the coming future.

Keywords

Docking hTERT Molecular dynamics simulation SNPs