z-logo
open-access-imgOpen Access
Computational Prediction of the Effects of Single Nucleotide Polymorphisms of the Gene Encoding Human Endothelial Nitric Oxide Synthase
Author(s) -
Esmaeil Samadian,
Ayyoob Khosravi,
Roghaye Gharae,
Mostafa Mir,
S. Ahmad Sajjadi,
Fahimeh Mohammad Abadi,
Nader Hashemi,
Hamidreza Joshaghani
Publication year - 2016
Publication title -
medical laboratory journal
Language(s) - English
Resource type - Journals
eISSN - 2322-2816
pISSN - 1735-9007
DOI - 10.18869/acadpub.mlj.10.3.1
Subject(s) - endothelial nitric oxide synthase , nitric oxide synthase , single nucleotide polymorphism , gene , nitric oxide , genetics , biology , microbiology and biotechnology , genotype , endocrinology , enos
Genetic variations in the gene encoding endothelial nitric oxide synthase (eNOS) enzyme affect the susceptibility to cardiovascular disease. Identification of the way these changes affect eNOS structure and function in laboratory conditions is difficult and time-consuming. Thus, it seems essential to perform bioinformatics studies prior to laboratory studies to find the variants that are more important. This study aimed to predict the damaging effect of changes in the coding region of eNOS using homologyand structurebased algorithms (SIFT and PolyPhen). Methods: First, the single nucleotide polymorphisms in the coding region (cSNPs) of the human eNOS gene were extracted from dbSNP. Resulting amino acid changes were reported as primary data required for the study. Then, position and type of amino acid changes along with the complete amino acid sequence were separately entered into the SIFT and PolyPhen tools for analysis. Results: Of 144 single nucleotide changes, 38 changes by the SIFT, 47 changes by the PolyPhen and 18 amino acid substitutions by both tools were predicted as damaging. Conclusion: It is predicted that 18 amino acid changes may have damaging phenotypic effects on the structure of the eNOS enzyme that may affect its performance by potentially affecting the enzyme’s various functional regions. Therefore, computational prediction of potentially damaging nsSNPs and prioritizing amino acid changes may be useful for investigating protein performance using targeted re-sequencing and gene mutagenesis experiments.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here
Accelerating Research

Address

John Eccles House
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom