# TDP43 M337V Research Report **Protein:** TDP43 M337V **Variant:** M337V **UniProt ID:** Q13148 **Disease Association:** ALS / FTD **Report Generated:** 2026-07-14 01:59 UTC **AlphaFold Confidence (pLDDT):** 65.7% **Structure Folded:** 2026-07-06 --- ## Structure Summary TDP-43 is a protein that normally helps regulate RNA in cells, but when it forms toxic clumps in the brain and spinal cord, it causes ALS (a disease affecting movement) and FTD (a disease affecting behavior and language). This analysis examined the M337V mutation, where methionine at position 337 is replaced by valine, using computer-based structure prediction with moderate confidence (average score 65.7 out of 100). The low confidence scores indicate substantial uncertainty in the predicted structure, limiting definitive conclusions about how this specific mutation alters protein shape and behavior. --- TDP-43 (TAR DNA-binding protein 43) is an RNA-binding protein essential for RNA metabolism, splicing, and transport within cells. Under normal conditions, TDP-43 resides primarily in the cell nucleus, but in ALS and FTD, it mislocalizes to the cytoplasm where it forms toxic aggregates that are found in approximately 97% of ALS cases and 45% of FTD cases [4]. The M337V mutation, where methionine at position 337 is replaced by the smaller amino acid valine, is located in the C-terminal domain (CTD), a region critical for protein phase transitions and aggregation behavior [5]. Recent research demonstrates that M337V significantly exacerbates TDP-43 proteotoxicity compared to wild-type protein, increasing oxidative stress and neuronal injury in motor neuron-like cells [1]. This mutation appears to enhance the protein's tendency to undergo aberrant phase transitions, shifting from normal liquid-like assemblies to pathological solid aggregates [3]. The C-terminal alpha-helix region where M337V resides plays a crucial role in coupling condensate formation (normal cellular assemblies) with amyloid assembly (disease-related fibrils), and mutations in this region can uncouple these processes [5]. The AlphaFold2 structure prediction for M337V yielded an average confidence score (pLDDT) of 65.7, which falls into the low-confidence range (below 70). This moderate-to-low confidence reflects the inherent disorder of TDP-43's C-terminal domain, which lacks a stable fixed structure under physiological conditions. The CTD is intrinsically disordered, meaning it exists as an ensemble of flexible conformations rather than a single rigid shape [5]. Therefore, the low confidence scores should be interpreted not as prediction failure, but as accurately capturing the dynamic, disordered nature of this protein region. Definitive structural conclusions about mutation-specific conformational changes cannot be made with confidence at this resolution. The molecular consequences of M337V extend beyond simple structural changes. The mutation occurs in a region where TDP-43 interacts with multiple cellular quality control systems. Studies show that TRIM16, a protein involved in cellular stress responses, is downregulated in cells expressing M337V, leading to impaired activation of antioxidant defenses and increased oxidative injury [1]. Additionally, TDP-43 mutations can influence interactions with other ALS-associated proteins like SOD1, potentially amplifying disease mechanisms through multiple pathways [2]. The mutation's location in the CTD may also affect nuclear-cytoplasmic transport dynamics, which modulate TDP-43's phase behavior and aggregation propensity [3]. Clinically, M337V represents one of several pathogenic variants in TDP-43's C-terminal region associated with familial ALS and FTD. The mutation contributes to the broader landscape of TDP-43 proteinopathies, which also include cases caused by mutations in other genes and sporadic disease. Recent advances in biomarker development, such as CSF acetylated tau measurements, are improving the ability to distinguish between TDP-43 and tau pathology in living patients [4], though direct detection of specific TDP-43 mutations in biofluids remains challenging. Understanding mutation-specific effects like those of M337V may inform future precision medicine approaches, particularly as therapeutic strategies targeting TDP-43 aggregation and phase behavior advance toward clinical testing. ## Works Cited [1] Chen et al. (2026). TRIM16 attenuates TDP43-mediated oxidative injury by coordinating Nrf2 activation and TFR1 autophagic degradation. Free radical biology & medicine. [PubMed](https://pubmed.ncbi.nlm.nih.gov/42092406/) [2] Ribeiro et al. (2026). Molecular Modulation of the Crosstalk Between TDP-43 and SOD1. International journal of molecular sciences. [PubMed](https://pubmed.ncbi.nlm.nih.gov/42074053/) [3] Chin et al. (2026). Nuclear export modulates TDP-43 phase transition and cytoplasmic aggregation. bioRxiv : the preprint server for biology. [PubMed](https://pubmed.ncbi.nlm.nih.gov/41993496/) [4] Honey et al. (2026). An acetylated Tau-174 CSF biomarker discriminates between TDP-43 and tau pathology in patients with frontotemporal lobar degeneration. Nature medicine. [PubMed](https://pubmed.ncbi.nlm.nih.gov/41986736/) [5] Byrd et al. (2026). An ALS-associated mutation in the C-terminal alpha-helix of TDP-43 uncouples condensate formation and amyloid assembly. Protein science : a publication of the Protein Society. [PubMed](https://pubmed.ncbi.nlm.nih.gov/41969219/) ## Similar Research **Integrative genetic analysis illuminates ALS heritability and identifies risk genes.** Megat et al. (2023) *Related research* [Read on PubMed](https://pubmed.ncbi.nlm.nih.gov/36670122/) **Biomarker discovery in Alzheimer's and neurodegenerative diseases using Nucleic Acid Linked Immuno-Sandwich Assay.** Ashton et al. (2025) *Related research* [Read on PubMed](https://pubmed.ncbi.nlm.nih.gov/40401628/) **Frontotemporal dementia. How to deal with its diagnostic complexity?** Antonioni et al. (2025) *Related research* [Read on PubMed](https://pubmed.ncbi.nlm.nih.gov/39911129/) **Proteomic analysis reveals distinct cerebrospinal fluid signatures across genetic frontotemporal dementia subtypes.** Sogorb-Esteve et al. 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(2024) *Related research* [Read on PubMed](https://pubmed.ncbi.nlm.nih.gov/38320753/) --- ## Open Targets Disease Associations | Disease | Score | Data Sources | |---------|-------|--------------| | amyotrophic lateral sclerosis | 0.820 | literature, animal_model, genetic_association, genetic_literature | | frontotemporal dementia with motor neuron disease | 0.707 | literature, animal_model, genetic_association, genetic_literature | | familial amyotrophic lateral sclerosis | 0.480 | literature, animal_model, genetic_literature | | frontotemporal dementia | 0.453 | literature, animal_model, genetic_association, genetic_literature | | neurodegenerative disease | 0.453 | literature, affected_pathway | | motor neuron disorder | 0.446 | literature, genetic_association | | amyotrophic lateral sclerosis, dominant | 0.370 | genetic_literature | | hereditary disease | 0.191 | literature, genetic_association | | immunodeficiency due to MASP-2 deficiency | 0.188 | genetic_association | | Parkinson disease | 0.147 | literature, animal_model, genetic_association | *...and 2568 more associations* --- ## Agent Findings ### Literature (1) - **2026-07-06:** None of the papers directly address the TDP43 M337V variant. The papers focus on other genetic causes of ALS/FTD (C9orf72, CHCHD10, SOD1) and general TDP-43 pathology, but do not mention the M337V mutation in TARDBP. While they provide valuable context about TDP-43 proteinopathy mechanisms and biomarkers relevant to ALS/FTD broadly, they lack specific relevance to understanding the M337V variant's pathogenic effects or clinical characteristics. ### Clinical (1) - **2026-07-06:** ### Structural (1) - **2026-07-07:** AlphaFold structure update: Baseline check: 2 structure(s) found ### Synthesis (1) - **2026-07-07:** Synthesis of 5 findings (clinical, literature, peptides, structural, supplements): The TDP43 M337V variant associated with ALS/FTD presents a mixed therapeutic landscape with emerging... --- *Generated by [Clarity Protocol](https://clarityprotocol.io)* **Data Sources:** - Structure predictions: AlphaFold via ColabFold - Clinical variant data: ClinVar, gnomAD - Disease associations: Open Targets Platform - Research findings: AI agents (PubMed, clinical databases)