DeCure's autonomous Rare AI scientist is researching a drug-repurposing hypothesis for GABA aminotransaminase deficiency — 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 moduleGABA aminotransaminase deficiency 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
Structures already discussed alongside gaba aminotransaminase deficiency in the retrieved literature, rendered from public PubChem SMILES. Which drugs appear here reflects the evidence found, not a ranked prediction.
What the evidence adds up to
GABA aminotransaminase deficiency is an ultra-rare autosomal recessive disorder of GABA degradation. By 1999 only two patients had been documented. Their phenotype included psychomotor retardation, hypotonia, hyperreflexia, lethargy, refractory seizures and electroencephalographic abnormalities. In the index proband an A-to-G transition at nucleotide 754 of the coding region substituted arginine 220 by lysine. Expression of that mutant in E. coli yielded an enzyme whose Vmax was reduced to 25% of wild-type activity. The second proband most likely harboured a deletion in the 3' region of the GABA-T gene.
A 2023 computational study examined how seven GABA-AT mutations influence structural stability and GABA-binding affinity using molecular dynamics simulation and binding free energy calculation. The study reported that P152S, Q296H, and R92Q play a more critical role in structural instability compared with G465R, L211F, L478P, and R220K.
A 2025 biochemical investigation expressed 10 pathogenic variants in HEK-293 cells and classified them into three groups. Variants with strong structural and catalytic defects were p.P152S, p.L211F, and p.L478P. Variants characterised mainly by a strong catalytic defect were p.R220K, p.Q296H, and p.R377W. Variants exhibiting moderate structural and catalytic defects maintaining substantial transaminase activity were p.R92Q, p.F213C, p.G465D, and p.G465R. No clinical trial, no therapeutic intervention, and no drug repurposing data are reported in any of these abstracts. What is still missing is any funded effort to translate these molecular classifications into a clinical trial, a reliable patient stratification system for a disorder with only a handful of known cases, and the money to develop or test a treatment.
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 Inherited Metabolic Disease · 1999 · 64 citations · open access
Abstract4-Aminobutyrate aminotransferase (GABA-transaminase, GABA-T, EC 2.6.1.19) deficiency (McKusick 137150), an inborn error of GABA degradation, has until now been documented in only a single Flemish child. Compared to the other defects of GABA degradation, succinic semialdehyde dehydrogenase (SSADH, EC 1.2.1.24) deficiency with > 150 patients (McKusick 271980) and pyridoxine-dependent seizures with > 100 patients ('putative' glutamic acid decarboxylase (GAD, EC 4.1.1.15) deficiency; McKusick 266100), GABA-T deficiency is very rare. We present a summary of the clinical, biochemical, enzymatic and molecular findings on the index proband, and a recently identified second patient, with GABA-T deficiency. The phenotype in both included psychomotor retardation, hypotonia, hyperreflexia, lethargy, refractory seizures and electroencephalographic abnormalities. In an effort to elucidate the molecular basis of GABA-T deficiency, we isolated and characterized a 1.5 kb cDNA encoding human GABA-T, in addition to a 41 kb genomic clone which encompassed the GABA-T coding region. Standard methods of cloning and sequencing revealed an A-to-G transition at nucleotide 754 of the coding region in lymphoblast cDNAs derived from the index proband. This mutation resulted in substitution of an invariant arginine at amino acid 220 by lysine. Expression of the mutant in E. coli, followed by isolation and enzymatic characterization of the recombinant protein, revealed an enzyme whose Vmax was reduced to 25% of wild-type activity. The patient and father were heterozygous for this allele; the second allele in the patient remains unidentified. Genomic Southern analysis revealed that the second proband most likely harbours a deletion in the 3' region of the GABA-T gene.
International Journal of Molecular Sciences · 2023 · 13 citations · open access
Computational Exploration of the Effects of Mutations on GABA Aminotransferase in GABA Aminotransferase Deficiency
AbstractGamma-aminobutyric acid (GABA) transaminase—also called GABA aminotransferase (GABA-AT)—deficiency is a rare autosomal recessive disorder characterized by a severe neonatal-infantile epileptic encephalopathy with symptoms such as seizures, hypotonia, hyperreflexia, developmental delay, and growth acceleration. GABA transaminase deficiency is caused by mutations in GABA-AT, the enzyme responsible for the catabolism of GABA. Mutations in multiple locations on GABA-AT have been reported and their locations have been shown to influence the onset of the disease and the severity of symptoms. We examined how GABA-AT mutations influence the structural stability of the enzyme and GABA-binding affinity using computational methodologies such as molecular dynamics simulation and binding free energy calculation to understand the underlying mechanism through which GABA-AT mutations cause GABA-AT deficiency. GABA-AT 3D model depiction was carried out together with seven individual mutated models of GABA-AT. The structural stability of all the predicted models was analyzed using several tools and web servers. All models were evaluated based on their phytochemical values. Additionally, 100 ns MD simulation was carried out and the mutated models were evaluated using RMSD, RMSF, Rg, and SASA. gmxMMPBSA free energy calculation was carried out. Moreover, RMSD and free energy calculations were also compared with those obtained using online web servers. Our study demonstrates that P152S, Q296H, and R92Q play a more critical role in the structural instability of GABA-AT compared with the other mutated models: G465R, L211F, L478P, and R220K.
Molecular Genetics and Metabolism · 2025 · 2 citations · open access
Biochemical investigation of pathogenic missense mutations of human 4-amino butyrate aminotransferase towards the understanding of the molecular pathogenesis of GABA transaminase deficiency.
AbstractGamma-amino butyrate aminotransferase (GABA-AT or ABAT) is a pyridoxal 5'-phosphate (PLP)-dependent enzyme that catalyzes the conversion of GABA and α-ketoglutarate into succinic semialdehyde and L-glutamate. In humans, the primary physiological role of GABA-AT is to control the level of GABA in neuronal tissues. Mutations on ABAT gene are associated to GABA-AT deficiency, an ultra-rare autosomal recessive disorder characterized by accelerated linear growth, severe psychomotor retardation, seizures, hypotonia, and hyperreflexia. So far, several missense pathogenic mutations of GABA-AT have been identified; however, their molecular effects at protein level have been poorly investigated. In this work a biochemical characterization of 10 pathogenic variants of human GABA-AT was carried out by expressing the protein in HEK-293 cells. Moreover, in-silico analyses of the variants were performed to corroborate the experimental findings. Altogether, the data obtained on protein expression level, GABA transaminase activity, and the predicted structural impact allowed us to classify the variants into three distinct groups, such as: (i) variants with strong structural and catalytic defects (p.P152S, p.L211F, and p.L478P); (ii) variants characterized mainly by a strong catalytic defect (p.R220K, p.Q296H, and p.R377W); (iii) variants exhibiting moderate structural and catalytic defects maintaining substantial transaminase activity (p.R92Q, p.F213C, p.G465D, and p.G465R). Based on these results, we provide a picture of the molecular defects of different GABA-AT pathogenic variants with the aim of gaining insights into the enzymatic phenotypes in GABA-AT deficiency.
Data_Sheet_2_2-Pyrrolidinone and Succinimide as Clinical Screening Biomarkers for GABA-Transaminase Deficiency: Anti-seizure Medications Impact Accurate Diagnosis.xlsx
Abstract<p>Broad-scale untargeted biochemical phenotyping is a technology that supplements widely accepted assays, such as organic acid, amino acid, and acylcarnitine analyses typically utilized for the diagnosis of inborn errors of metabolism. In this study, we investigate the analyte changes associated with 4-aminobutyrate aminotransferase (ABAT, GABA transaminase) deficiency and treatments that affect GABA metabolism. GABA-transaminase deficiency is a rare neurodevelopmental and neurometabolic disorder caused by mutations in ABAT and resulting in accumulation of GABA in the cerebrospinal fluid (CSF). For that reason, measurement of GABA in CSF is currently the primary approach to diagnosis. GABA-transaminase deficiency results in severe developmental delay with intellectual disability, seizures, and movement disorder, and is often associated with death in childhood. Using an untargeted metabolomics platform, we analyzed EDTA plasma, urine, and CSF specimens from four individuals with GABA-transaminase deficiency to identify biomarkers by comparing the biochemical profile of individual patient samples to a pediatric-centric population cohort. Metabolomic analyses of over 1,000 clinical plasma samples revealed a rich source of biochemical information. Three out of four patients showed significantly elevated levels of the molecule 2-pyrrolidinone (Z-score ≥2) in plasma, and whole exome sequencing revealed variants of uncertain significance in ABAT. Additionally, these same patients also had elevated levels of succinimide in plasma, urine, and CSF and/or homocarnosine in urine and CSF. In the analysis of clinical EDTA plasma samples, the levels of succinimide and 2-pyrrolidinone showed a high level of correlation (R = 0.73), indicating impairment in GABA metabolism and further supporting the association with GABA-transaminase deficiency and the pathogenicity of the ABAT variants. Further analysis of metabolomic data across our patient population revealed the association of elevated levels of 2-pyrrolidinone with administration of vigabatrin, a commonly used anti-seizure medication and a known inhibitor of GABA-transaminase. These data indicate that anti-seizure medications may alter the biochemical and metabolomic data, potentially impacting the interpretation and diagnosis for the patient. Further, these data demonstrate the power of combining broad scale genotyping and phenotyping technologies to diagnose inherited neurometabolic disorders and support the use of metabolic phenotyping of plasma to screen for GABA-transaminase deficiency.</p>
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.
