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

J Mol Model. 2013 Sep;19(9):3517-27. doi: 10.1007/s00894-013-1888-7. Epub 2013 May 29.

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.

MeSH terms

  • Amino Acids
  • Anemia, Aplastic / genetics
  • Computational Biology / methods
  • Dyskeratosis Congenita / genetics
  • Humans
  • Idiopathic Pulmonary Fibrosis / genetics
  • Ligands
  • Models, Molecular*
  • Molecular Docking Simulation
  • Molecular Dynamics Simulation
  • Mutation
  • Polymorphism, Single Nucleotide*
  • Protein Binding
  • Protein Conformation
  • Protein Interaction Domains and Motifs
  • Telomerase / chemistry*
  • Telomerase / genetics*

Substances

  • Amino Acids
  • Ligands
  • TERT protein, human
  • Telomerase