GAE2 Antibody
Description
GAD2 Antibody Overview
GAD2 (Glutamate Decarboxylase 2) is an enzyme responsible for synthesizing gamma-aminobutyric acid (GABA), the primary inhibitory neurotransmitter in the central nervous system. Antibodies targeting GAD2 are critical tools for studying autoimmune neurological disorders, including type 1 diabetes and stiff-person syndrome .
Research Applications
GAD2 antibodies are utilized to:
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Investigate GABAergic signaling disruptions in epilepsy and Parkinson’s disease.
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Diagnose autoimmune disorders via detection of anti-GAD65 autoantibodies .
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Study synaptic vesicle dynamics in neuronal models.
Experimental Validation:
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Western Blot: Detects ~65 kDa band corresponding to GAD2 in human brain lysates .
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Immunofluorescence: Localizes GAD2 to cytoplasmic vesicles and presynaptic clusters in neurons .
Therapeutic Antibody Context
While GAD2 antibodies are primarily research tools, broader antibody engineering advancements provide insights into their potential therapeutic applications:
Comparative Antibody Technologies:
Critical Analysis of Nomenclature
The term "GAE2" may stem from typographical errors or ambiguous abbreviations. Cross-referencing antibody databases ( ) and genomic repositories confirms:
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No match for "GAE2" in UniProt, ClinicalTrials.gov, or Therapeutic Antibody Society listings.
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GAD2 (HGNC:4093) remains the closest validated target with commercial/reagent antibodies .
Future Directions
Emerging antibody engineering strategies (e.g., bispecific formats , Fc optimization ) could enhance GAD2 antibody utility for:
Product Specs
Constituents: 50% Glycerol, 0.01M Phosphate Buffered Saline (PBS), pH 7.4
Target Background
Q&A
Here’s a structured collection of FAQs tailored to academic research scenarios involving antibody-related investigations, synthesized from interdisciplinary insights in the provided sources:
Advanced Research Questions
How can conflicting results in antibody efficacy across models be resolved?
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Analysis: Compare model-specific variables (e.g., epitope accessibility, blood-brain barrier penetration). Anti-GA antibodies improved behavior in C9orf72 450 mice but failed in AAV-G4C2 149 mice due to poly-GA accumulation differences .
Key Data:Model Poly-GA Clearance Behavioral Outcome C9orf72 450 mice Partial Improved movement AAV-G4C2 149 mice None No change
What computational tools enhance antibody design for targeting dynamic epitopes?
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Toolkit: Use deep learning models (e.g., AF2Complex) trained on evolutionary patterns of antigen-binding sequences. This approach achieved 90% accuracy in identifying SARS-CoV-2 spike-targeting antibodies .
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Workflow:
How do post-translational modifications (PTMs) impact antibody validation?
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Considerations: Screen for PTMs (e.g., phosphorylation at S623/S625 in Gab2) that alter epitope conformation. Use denaturing conditions in Western blots to avoid masking effects .
PTM Example:Site Modification Functional Impact Y452 Phosphorylation Modulates Gab2 signaling S623 Phosphorylation Affects MAPK binding
Methodological Guidance
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For conflicting data: Replicate findings across independent models (e.g., cellular vs. animal systems) and quantify all centrifugation fractions to capture aggregate-prone antigens .
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For structural studies: Combine AI-predicted interfaces with mutagenesis to isolate critical binding residues, as done for CT-P59 .
