Biological and Clinical Significance

GABA receptors are the primary inhibitory neurotransmitter receptors in the human central nervous system and are central to neurophysiology, pharmacology, and brain development. While the logical mathematical combination of human GABA receptor subunits exceeds 150,000 permutations, biological constraints restrict this to approximately 50 functional variations in humans. This atlas adopts a rigorous, purely mathematical and logical approach to catalogue every theoretically possible contiguous peptide fragment derived from wild-type human GABA receptor subunit sequences based on predicted enzymatic and chemical cleavage events.

Comprehensive knowledge of the GABA receptor degradome is essential for:

• Biomarker Discovery: Interpreting proteomic measurements across neurological, psychiatric, and systemic human diseases.
• Systems Biology: Contextualising biomarker degradomes reliably alongside other neuro-proteomes.
• Peptidomics Workflow Optimization: Mapping mass spectrometry features to precise subunit origins.

Included Fragment Annotations

Every peptide fragment generated within the atlas is extensively annotated with critical biochemical and biophysical characteristics required for downstream bioinformatics and statistical analysis:

• Sequence Identification: Unique peptide identifier (id) and exact amino acid sequence (peptide).
• Mass Spectrometry Metrics: Molecular weight in Daltons (Da) and mass-to-charge ratio (mz).
• Physicochemical Properties: Net electric charge (charge) and calculated isoelectric point (isoelectric_point / $pI$).
• Stability & Hydrophobicity Descriptors: Boman index (Boman), hydrophobicity index (hydrophobicity), predicted instability index (instability_index), and aliphatic index (aliphatic_index).

Repository Contents

This open-access repository contains the reproducible Python source code, pipeline dependencies, and resulting high-resolution datasets:

• Main Execution Scripts: Individual Python files mapped by UniProt accession numbers (e.g., P18505.py) containing explicitly defined cleavage site positions.
• Structured Datasets: Individual comma-separated (.csv) output files containing all computed peptide fragments and properties for each target subunit sequence.
• Environment Configuration: A requirements.txt file specifying software dependencies.
• Documentation: A technical README.txt detailing usage guidelines and decompression instructions.

Version 1 GABA Subunit Coverage

Version 1 comprehensively catalogues the following 23 human wild-type GABA receptor subunit sequences and associated proteins:

Reproducibility, Customisation, and Usage

The workflow utilises SQLite as an in-memory database to store intermediate peptide structures, guaranteeing deterministic behaviour and flawless reproducibility. Standardised features are computed using the open-source peptides Python library.

Quick Start Pipeline:

1. Dependencies: Create a virtual environment and run pip install pandas peptides.
2. Execution: Execute the subunit-specific scripts (python P18505.py) to generate the corresponding structured datasets (p18505.csv).
3. Customization: Users can modify the internal sites list within the scripts to adapt the workflow for alternative cleavage models, specialized proteases, or genetic variants.

Citations and References

If you use this dataset, source code, or conceptual framework in your research, please cite both of the following references:

1. Dataset DOI: doi:10.5522/04/32820329
2. Methodological Framework: Petzold A. Proteolysis-based biomarker repertoire of the neurofilament proteome. Journal of Neurochemistry. 2025;169:e70023. doi:10.1111/jnc.70023