A comprehensive in Silico analysis of the functional and structural impact of single nucleotide polymorphisms (SNPs) in the human IL-33 gene.
Computational tools
In silico
Interleukin 33 (IL-33)
Single-nucleotide polymorphisms (SNPs)
Journal
Computational biology and chemistry
ISSN: 1476-928X
Titre abrégé: Comput Biol Chem
Pays: England
ID NLM: 101157394
Informations de publication
Date de publication:
Oct 2021
Oct 2021
Historique:
received:
19
06
2020
revised:
17
06
2021
accepted:
09
08
2021
pubmed:
30
8
2021
medline:
4
11
2021
entrez:
29
8
2021
Statut:
ppublish
Résumé
Interleukin 33 (IL-33) is the latest member of the IL-1 cytokine family, which plays both pro - and anti-inflammatory functions. Numerous Single-nucleotide polymorphisms (SNPs) in the IL-33 gene have been recognized to be associated with a vast variety of inflammatory disorders. SNPs associated studies have become a crucial approach in uncovering the genetic background of human diseases. However, distinguishing the functional SNPs in a disease-related gene from a pool of both functional and neutral SNPs is a major challenge and needs multiple experiments of hundreds or thousands of SNPs in candidate genes. This study aimed to identify the possible deleterious SNPs in the IL-33 gene using bioinformatics predictive tools. The nonsynonymous SNPs (nsSNPs) were analyzed by SIFT, PolyPhen, PROVEAN, SNP&GO, MutPred, SNAP, PhD SNP, and I-Mutant tools. The Non-coding SNPs (ncSNPs) were also analyzed by SNPinfo and RegulomeDB tools. In conclusion, our in-silico analysis predicted 5 nsSNPs and 22 ncSNPs as potential candidates in the IL-33 gene for future genetic association studies.
Identifiants
pubmed: 34455166
pii: S1476-9271(21)00127-4
doi: 10.1016/j.compbiolchem.2021.107560
pii:
doi:
Substances chimiques
IL33 protein, human
0
Interleukin-33
0
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
107560Informations de copyright
Copyright © 2021 Elsevier Ltd. All rights reserved.