ArticleScientific reports2018
Molecular modelling of mitofusin 2 for a prediction for Charcot-Marie-Tooth 2A clinical severity.
Article in Scientific reports, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Charcot-Marie-Tooth type 2A variants of mitofusin 2 sensitize cells to apoptotic cell death.Journal of cell science · 2025Article
- Digenesis in Charcot-Marie-Tooth Disease: Impact of Combined Mutations in the MFN2 and GDAP1 Genes.Journal of the peripheral nervous system : JPNS · 2025Article
- Modeling of Charcot-Marie-Tooth disease in zebrafish.Frontiers in molecular neuroscience · 2025Review
- Structural insights into Charcot-Marie-Tooth disease-linked mutations in human GDAP1.FEBS open bio · 2022Article
- The Role of Impaired Mitochondrial Dynamics in MFN2-Mediated Pathology.Frontiers in cell and developmental biology · 2022Review
- Animal Models of CMT2A: State-of-art and Therapeutic Implications.Molecular neurobiology · 2020Review
- Article
- A Molecular Perspective on Mitochondrial Membrane Fusion: From the Key Players to Oligomerization and Tethering of Mitofusin.The Journal of membrane biology · 2019Review
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Charcot-Marie-Tooth disease type 2A (CMT2A) is an autosomal dominant neuropathy caused by mutations in the mitofusin 2 gene (MFN2). More than 100 MFN2 gene mutations have been reported so far, with majority located within the GTPase domain encoding region. These domain-specific mutations present wide range of symptoms with differences associated with distinct amino acid substitutions in the same position. Due to the lack of conclusive phenotype-genotype correlation the predictive value of genetic results remains still limited. We have explored whether changes in the protein structure caused by MFN2 mutations can help to explain diseases phenotypes. Using a stable protein model, we evaluated the effect of 26 substitutions on the MFN2 structure and predicted the molecular consequences of such alterations. The observed changes were correlated with clinical features associated with a given mutation. Of all tested mutations positive correlation of molecular modelling with the clinical features reached 73%. Our analysis revealed that molecular modelling of mitofusin 2 mutations is a powerful tool, which predicts associated pathogenic impacts and that these correlate with clinical outcomes. This approach may aid an early diagnosis and prediction of symptoms severity in CMT2A patients.
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