Sorting Intolerant from Tolerant Algorithm of KCNJ11 Gene Polymorphisms in Diabetes Mellitus

Background: Mutations in the copper transport gene KCNJ11 cause Diabetes Mellitus, a rare inherited autosomal recessive condition of copper metabolism with hepatic and mental symptoms. The Sorting Intolerant from Tolerant (SIFT) method was used in a study to examine the possible effects of protein coding variants on function. SIFT is a computational technique that is frequently used to forecast the outcomes of missense variants, which are single nucleotide changes in the DNA sequence that lead to the replacement of one amino acid with another in the protein.Objective: This study’s objectives include determining the degree to which gene KCNJ11 mutations contribute to the development of Diabetes Mellitus assess whether the observed variations in the KCNJ11 gene would potentially affect protein function and thus contribute to the development of genetic disease. Understanding the impact of protein structure on the SIFT results is emphasized in the paragraph.Methods: We used the SIFT tool to analyze mutations occurring in the KCNJ11 gene because this gene is of particular interest due to its association with certain genetic diseases.Results: According to the study’s findings, the SIFT tool identified the majority of the changes detected in the samples examined (particularly a (G>C) variance) as tolerant, this implies that these specific variants are unlikely to have a major influence on protein function and, as a result, are less likely to contribute to the development of the examined genetic disorder. The results, however, showed two variants (G>T and C>T) that SIFT categorized as intolerant in some of the sample instances. These particular alterations are likely to impact protein function and may be of relevance for future research into their relationship with the investigated hereditary disorder.Conclusions: Overall, the work emphasizes the utility of employing the SIFT method to predict illness outcomes based on coding variants and protein function. Researcher was able to get insight into the possible influence of polymorphisms in the KCNJ11 gene on protein function and their relevance to genetic disease detection by using this computational technique.

Institutions

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-02-20
DOI
https://doi.org/10.5281/zenodo.14900292
Primary Topic
Soil Carbon and Nitrogen Dynamics
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Sorting Intolerant from Tolerant Algorithm of KCNJ11 Gene Polymorphisms in Diabetes Mellitus

Zenodo (CERN European Organization for Nuclear Research)
Soil Carbon and Nitrogen Dynamics
article

Sorting Intolerant from Tolerant Algorithm of KCNJ11 Gene Polymorphisms in Diabetes Mellitus

article en

Abstract

Background: Mutations in the copper transport gene KCNJ11 cause Diabetes Mellitus, a rare inherited autosomal recessive condition of copper metabolism with hepatic and mental symptoms. The Sorting Intolerant from Tolerant (SIFT) method was used in a study to examine the possible effects of protein coding variants on function. SIFT is a computational technique that is frequently used to forecast the outcomes of missense variants, which are single nucleotide changes in the DNA sequence that lead to the replacement of one amino acid with another in the protein.Objective: This study’s objectives include determining the degree to which gene KCNJ11 mutations contribute to the development of Diabetes Mellitus assess whether the observed variations in the KCNJ11 gene would potentially affect protein function and thus contribute to the development of genetic disease. Understanding the impact of protein structure on the SIFT results is emphasized in the paragraph.Methods: We used the SIFT tool to analyze mutations occurring in the KCNJ11 gene because this gene is of particular interest due to its association with certain genetic diseases.Results: According to the study’s findings, the SIFT tool identified the majority of the changes detected in the samples examined (particularly a (G>C) variance) as tolerant, this implies that these specific variants are unlikely to have a major influence on protein function and, as a result, are less likely to contribute to the development of the examined genetic disorder. The results, however, showed two variants (G>T and C>T) that SIFT categorized as intolerant in some of the sample instances. These particular alterations are likely to impact protein function and may be of relevance for future research into their relationship with the investigated hereditary disorder.Conclusions: Overall, the work emphasizes the utility of employing the SIFT method to predict illness outcomes based on coding variants and protein function. Researcher was able to get insight into the possible influence of polymorphisms in the KCNJ11 gene on protein function and their relevance to genetic disease detection by using this computational technique.

Zenodo (CERN European Organization for Nuclear Research)
University of Anbar (IQ)
Good health and well-being
Openalex Percentile: Top 48%
Soil Carbon and Nitrogen Dynamics
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.