DeCure's autonomous Neuro AI scientist is researching a drug-repurposing hypothesis for Charcot-Marie-Tooth disease type 4F — screening already-approved drugs against its 1-gene Open Targets disease module to publish open-access research. Research is fast; the path to publication is funded in milestone stages.
Disease moduleCharcot-Marie-Tooth disease type 4F maps to a 1-gene Open Targets module — the target space DeCure's AI scientist screens approved drugs against.
DeCure.ai methodSignature reversal (LINCS) plus network proximity (STRING) rank already-approved drugs likely to perturb this module — the same engine that produces DeCure.ai's repurposing hypotheses.
Repurposing thesisScreening approved medicines against this disease module, then publishing the evidence for the strongest candidate. Known pharmacology and human exposure data make the first question sharper — they do not establish safety or efficacy in a new indication.
Research record
01
ResearchComing soon
Candidate research + dossier — target rationale, drug-repurposing thesis and evidence pack.proof: Published dossier + on-chain hash
02
ValidationComing soon
In-vitro biological validation at a contract research org (CRO).proof: CRO contract + in-vitro report
03
Peer review & paperComing soon
Peer-reviewed paper published open-access (preprint + journal).proof: DOI + open-access link + on-chain hash
Current lead
No approved-drug candidate for charcot-marie-tooth disease type 4f is corroborated in the literature DeepSearch retrieved. Some conditions are managed with non-pharmacological care — a device, surgery or physical therapy — rather than a medicine; that may be the case here, or the literature we found may simply be too sparse yet to support a drug-repurposing angle.
Molecular view
periaxin (PRX) — PRX is one of the genes genetically linked to this disease in Open Targets — shown as context, not as a drug target we're pursuing: no approved-drug candidate for this disease is yet corroborated in the literature we found.
Loading structure…
helix sheet apo structuredrag to rotate · scroll to zoom
RCSB Protein Data Bank · entry 4CMZ · 2.7 Å · ligand none (apo structure). Experimental structure, not a prediction.
Evidence
Retrieved by DeepSearch across 234,678,978 indexed works and resolved on OpenAlex — ranked by citations, including the results that did not work.
Journal of Neuromuscular Diseases · 2019 · 2 citations
Late onset CMT2A in a Family with an MFN2 Variant: c.2222T>G (p.Leu741Trp)
AbstractMutations in MFN2 cause a range of Charcot-Marie-Tooth disease (CMT) phenotypes with different inheritance patterns and underlying pathogenic mechanisms. Recently, a family with a dominantly inherited CMT harboring c.2222T>G (p.Leu741Trp) mutation in MFN2 has been reported for the first time. Here, we report a second family also with a dominantly inherited CMT harboring the same mutation, thereby confirming the pathogenicity of this mutation. Interestingly, the disease onset of this second family is much later than the previously reported cases.
Journal of Foot and Ankle Research · 2011 · 1 citations · open access
Development, reliability and validity of the Charcot‐Marie‐Tooth disease Pediatric Scale (CMTPedS)
AbstractCharcot-Marie-Tooth disease (CMT) causes peripheral nerve demyelination, progressive foot weakness, cavus deformity, difficulty walking and sensory loss. There is a need for accurate, sensitive and disease-relevant measures of young children through to adolescents with CMT to enable accurate assessment of baseline performance, monitor disease severity longitudinally, and determine responses to existing and novel foot and ankle interventions. Our objective was to develop a multidimensional scale to measure disease severity of children with CMT, known as the CMT Pediatric Scale (CMTPedS). The CMTPedS has undergone a thorough development process: (1) definition of the construct; (2) generation of the item pool; (3) choice of scoring format; (4) peer-review (face validity); (5) pilot testing; (6) standardised training; (7) inter-rater reliability of four international centres assessing eight children with CMT; (8) multicenter implementation. Findings of the development process: (1) the CMTPedS is a composite scale with broad application to measure disease severity of childhood CMT with eight domains capturing symptoms, foot/ankle involvement, lower limb sensation, hand dexterity/strength, balance, motor function; (2) a large pool of items generated from the literature were reduced based on disease-specificity, functional/patient-relevance, reliability/validity, published norms, test duration and ease of interpretation; (3) items collapsed to 5-point Likert scales using z-scores based on age/gender norms; (4) quality, appropriateness and suitability of items peer-reviewed by 23 expert clinicians/researchers/patient representatives at the 168th European Neuromuscular Centre International Workshop; (5) pilot-tested on four children with CMT to check for administration problems, item instructions, order and duration; (6) clinicians from USA, UK, Italy and Australia trained through workshops, online manual and video resources; (7) all items exhibited good to excellent inter-rater reliability (ICC2,40.78-0.99) (8) a multicenter natural history study of children with all types of CMT aged 3-17 years is underway, with 90 children recruited to date. Application and psychometric validation of the CMTPedS continues. We plan to apply the final CMTPedS as the primary outcome in clinical trials of podiatric, pharmacological and surgical interventions.
Disease module: DeepOracle (Open Targets). Structures: RDKit from PubChem SMILES. Literature: retrieved by DeepSearch across 234,678,978 indexed works (targeted per-candidate search), resolved on OpenAlex.
DeCure is a research and publication project, not medical advice and not a treatment. "DeCure for X" describes a research goal, not a claim that a cure exists. Backing a cure is a contribution to fund the research — it is not an investment, and confers no yield, royalty, equity or IP ownership. Papers are published open-access by the DeCure.ai DAO.
