• Vemulapati Bhadra Murthy Genomics and Proteomics Group, Department of Biotechnology, K L University, Greenfields, Vaddeswaram, Guntur, Andhra Pradesh 522502
  • Meghana Chowdary Genomics and Proteomics Group, Department of Biotechnology, K L University, Greenfields, Vaddeswaram, Guntur, Andhra Pradesh 522502
  • Sucharitha . Genomics and Proteomics Group, Department of Biotechnology, K L University, Greenfields, Vaddeswaram, Guntur, Andhra Pradesh 522502


Objective: The major objective of the study was to carry out comparative bioinformatics analyses to identify different nsSNPs that were predicted to be deleterious or damaging to the structure and functions of CFTR protein causing cystic fibrosis.

Methods: The CFTR gene variants (nsSNPs) and their related protein sequences from Homo sapiens were subjected to computational analyses using the following bioinformatics tools (a) SIFT: a sequence-homology based prediction tool that can be used to distinguish between the intolerant from tolerant SNP changes. (b) PolyPhen2: a structure and sequence-based physical and comparison tool to study the impact of amino acid substitution on the structure and function of human proteins and (c) I-Mutant2: to predict the protein stability changes arising due to single point mutations.

Results: SIFT, PolyPhen2, and I-Mutant2 analyses indicated that 21 out of 108 nsSNPs were identified to be common that were strongly predicted to be deleterious and damaging for CTFR protein in cystic fibrosis conditions. Most of the substitutions in the CFTR protein contained the amino acids valine followed by cysteine and proline respectively. Homology modeling carried out to determine if any of these nsSNPs had a role in changing the conformation of CFTR protein drastically. Homology modeling of selected nsSNP variants indicated that these substitutions,however did not change the overall CFTR protein structure but predicted to cause severe damaging changes to the phenotypes of CFTR protein. Results indicated that multiple bioinformatics tools are needed to predictthe effect of substitutions and these prediction tools need to be analyzed more into detail and common determination factors are required to predict a nsSNP to be deleterious or damaging to the overall functioning of the CFTR protein.

Conclusion: Multiple bioinformatics tools are in fact the need of the hour to establish if a strong relationship between nsSNPs that could alter the protein stability and cause a deleterious or damaging phenotypic change to the individual with cystic fibrosis involving the CFTR protein.

Keywords: Cystic fibrosis, CFTR protein, SIFT, PolyPhen2, I-Mutant2, Homology model


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How to Cite
Murthy, V. B., M. Chowdary, and S. . “IN SILICO PREDICTION OF DELETERIOUS AND NON-DELETERIOUS NsSNPs IN CFTR GENE VARIANTS”. International Journal of Pharmacy and Pharmaceutical Sciences, Vol. 8, no. 12, Dec. 2016, pp. 303-6, doi:10.22159/ijpps.2016v8i12.14737.
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