Decoding the genetic basis of demyelination: Prediction of potential pathogenic coding and regulatory noncoding MBP SNPs in multiple sclerosis

BACKGROUND: The Myelin Basic Protein (MBP) gene is essential for myelin sheath formation in the central nervous system. Coding and noncoding single-nucleotide polymorphisms (SNPs) can impair the protein structure and function, contributing to demyelinating diseases exemplified by multiple sclerosis. This study aimed to assess the impact of SNPs in the MBP gene on protein structure and function. METHODS: We employed a comprehensive approach to investigate the impact of both noncoding and coding SNPs of the MBP gene. Initially, we utilized RegulomeDB to assess the regulatory roles of SNPs located in the 3' untranslated regions (3' UTRs). Subsequently, we examined the influence of the 3' UTR SNPs on microRNA (miRNA) binding sites using PolymiRTS. Furthermore, we analyzed the functional 3' UTR SNPs using RNAfold to evaluate their impact on RNA structure. To predict deleterious nonsynonymous SNPs (nsSNPs), various bioinformatics tools, including SIFT, PolyPhen-2, PROVEAN, META-SNP, ESNPs&GO, PANTHER, and AlphaMissense, were employed. Protein stability was assessed using I-Mutant2.0, MUpro, and DDMut. Structural modeling was performed with AlphaFold, and both wild-type and mutant proteins were visualized in UCSF ChimeraX. Conservation analysis was conducted using the ConSurf tool, and protein interaction networks were explored using the STRING database. RESULTS: Eight noncoding SNPs were identified as potential regulatory SNPs, affecting the miRNA binding sites. Moreover, three nsSNPs, rs1971676214 (D173E), rs1242552448 (D173H), and rs772570115 (G176W), were consistently predicted to be pathogenic and to destabilize the protein structure. These variants were located in highly conserved sites and disrupted hydrogen bonds. STRING analysis revealed interactions between MBP and other myelin-related, immune, and signaling proteins, linking it to CNS and autoimmune pathways. CONCLUSIONS: This study identified eight noncoding 3' UTR SNPs and three potentially pathogenic nsSNPs that may compromise gene expression and protein structure and function, respectively, offering insight into genetic mechanisms of demyelination.

Authors

Institutions

Publication Details

Journal
PLoS ONE
Published
2026-05-21
DOI
https://doi.org/10.1371/journal.pone.0347598
Primary Topic
Hereditary Neurological Disorders
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Decoding the genetic basis of demyelination: Prediction of potential pathogenic coding and regulatory noncoding MBP SNPs in multiple sclerosis

Samah O. Mohager, Ebtihal Kamal, Ghalia Mahfod Aldoseri, Arwa Ibrahim Alwabran et al.
PLoS ONE
Hereditary Neurological Disorders
article

Decoding the genetic basis of demyelination: Prediction of potential pathogenic coding and regulatory noncoding MBP SNPs in multiple sclerosis

Samah O. Mohager, Ebtihal Kamal, Ghalia Mahfod Aldoseri, Arwa Ibrahim Alwabran, Ghanem Mahfod Aldoseri, Mobarak Mahfod Aldoseri
article en

Abstract

BACKGROUND: The Myelin Basic Protein (MBP) gene is essential for myelin sheath formation in the central nervous system. Coding and noncoding single-nucleotide polymorphisms (SNPs) can impair the protein structure and function, contributing to demyelinating diseases exemplified by multiple sclerosis. This study aimed to assess the impact of SNPs in the MBP gene on protein structure and function. METHODS: We employed a comprehensive approach to investigate the impact of both noncoding and coding SNPs of the MBP gene. Initially, we utilized RegulomeDB to assess the regulatory roles of SNPs located in the 3' untranslated regions (3' UTRs). Subsequently, we examined the influence of the 3' UTR SNPs on microRNA (miRNA) binding sites using PolymiRTS. Furthermore, we analyzed the functional 3' UTR SNPs using RNAfold to evaluate their impact on RNA structure. To predict deleterious nonsynonymous SNPs (nsSNPs), various bioinformatics tools, including SIFT, PolyPhen-2, PROVEAN, META-SNP, ESNPs&GO, PANTHER, and AlphaMissense, were employed. Protein stability was assessed using I-Mutant2.0, MUpro, and DDMut. Structural modeling was performed with AlphaFold, and both wild-type and mutant proteins were visualized in UCSF ChimeraX. Conservation analysis was conducted using the ConSurf tool, and protein interaction networks were explored using the STRING database. RESULTS: Eight noncoding SNPs were identified as potential regulatory SNPs, affecting the miRNA binding sites. Moreover, three nsSNPs, rs1971676214 (D173E), rs1242552448 (D173H), and rs772570115 (G176W), were consistently predicted to be pathogenic and to destabilize the protein structure. These variants were located in highly conserved sites and disrupted hydrogen bonds. STRING analysis revealed interactions between MBP and other myelin-related, immune, and signaling proteins, linking it to CNS and autoimmune pathways. CONCLUSIONS: This study identified eight noncoding 3' UTR SNPs and three potentially pathogenic nsSNPs that may compromise gene expression and protein structure and function, respectively, offering insight into genetic mechanisms of demyelination.

PLoS ONEVol. 21(5)
Prince Sattam Bin Abdulaziz University (SA)
Prince Sattam bin Abdulaziz University
Life in Land
Openalex Percentile: Top 8%
Hereditary Neurological Disorders
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.