Computational Analysis of Deleterious nsSNPs in INS Gene Associated with Permanent Neonatal Diabetes Mellitus DOI Open Access
Elsadig Mohamed Ahmed,

Mohamed E. Elangeeb,

Khalid Mohamed Adam

et al.

Journal of Personalized Medicine, Journal Year: 2024, Volume and Issue: 14(4), P. 425 - 425

Published: April 17, 2024

Insulin gene mutations affect the structure of insulin and are considered a leading cause neonatal diabetes permanent mellitus PNDM. These can production secretion insulin, resulting in inadequate levels subsequent hyperglycemia. Early discovery or prediction PNDM aid better management treatment. The current study identified potential deleterious non-synonymous single nucleotide polymorphisms nsSNPs INS gene. analysis was conducted using bioinformatics tools by implementing computational algorithms including SIFT, PolyPhen2, SNAP2, SNPs & GO, PhD-SNP, MutPred2, I-Mutant, MuPro, HOPE to investigate association between Three mutations, C96Y, P52R, C96R, were shown potentially reduce stability function protein. mutants subjected MDSs for structural analysis. Results suggested that these three pathogenic may functionality protein encoded Therefore, changes influence development Further researches required fully understand various effects on synthesis function. data genetic testing evaluate its risk create treatment prevention strategies personalized medicine.

Language: Английский

Computational Analysis of Deleterious nsSNPs in INS Gene Associated with Permanent Neonatal Diabetes Mellitus DOI Open Access
Elsadig Mohamed Ahmed,

Mohamed E. Elangeeb,

Khalid Mohamed Adam

et al.

Journal of Personalized Medicine, Journal Year: 2024, Volume and Issue: 14(4), P. 425 - 425

Published: April 17, 2024

Insulin gene mutations affect the structure of insulin and are considered a leading cause neonatal diabetes permanent mellitus PNDM. These can production secretion insulin, resulting in inadequate levels subsequent hyperglycemia. Early discovery or prediction PNDM aid better management treatment. The current study identified potential deleterious non-synonymous single nucleotide polymorphisms nsSNPs INS gene. analysis was conducted using bioinformatics tools by implementing computational algorithms including SIFT, PolyPhen2, SNAP2, SNPs & GO, PhD-SNP, MutPred2, I-Mutant, MuPro, HOPE to investigate association between Three mutations, C96Y, P52R, C96R, were shown potentially reduce stability function protein. mutants subjected MDSs for structural analysis. Results suggested that these three pathogenic may functionality protein encoded Therefore, changes influence development Further researches required fully understand various effects on synthesis function. data genetic testing evaluate its risk create treatment prevention strategies personalized medicine.

Language: Английский

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