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Albumin Degradome Foundation Atlas

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DataCite Commons2025-12-08 更新2026-05-07 收录
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https://rdr.ucl.ac.uk/articles/dataset/Albumin_Degradome_Foundation_Atlas/30818825
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<b>Albumin Degradome Foundation Atlas — Version 1</b><b>Dataset Description </b><b>The Albumin Degradome Foundation Atlas</b> (Version 1) is an open-access, fully reproducible reference dataset that provides the first comprehensive in~silico reconstruction of the proteolytic degradome of human serum albumin (ALB). Serum albumin is the most abundant plasma protein and plays central roles in osmotic regulation, molecular transport, antioxidant defence, and systemic homeostasis. Its continuous turnover generates a diverse pool of proteolytic fragments that has not previously been systematically mapped.This dataset enumerates all theoretically possible albumin-derived peptides generated from defined enzymatic and chemical cleavage sites along the full-length human serum albumin sequence. Each fragment is annotated with a rich panel of physicochemical and biochemical properties relevant to proteomics, immunology, and biomarker discovery.<b>Scope and Content</b>The dataset comprises every predicted proteolytic fragment of human albumin, including overlapping peptides spanning the entire primary sequence. For each peptide, the following features are provided:Peptide identifier and coordinates (start and stop positions)Amino acid sequenceCalculated mass-to-charge ratio (m/z)Molecular weight (Da)Boman indexNet chargeIsoelectric point (pI)HydrophobicityInstability indexAliphatic indexAll fragments were computationally generated using Python, with reproducible logic that mirrors the approaches used in the Neurofilament Degradome Foundation Atlas.<b>Methods Summary</b>The degradome was constructed by:Defining experimentally reported and computationally predicted cleavage sites within the ALB primary sequence.Generating all pairwise subsequences between cleavage positions.Computing peptide physicochemical indices using the <i>peptides</i> Python library.Exporting all results as structured CSV files.Merging and compressing outputs into a single FAIR-compliant archive (TAR.XZ format) to enable efficient download and reproducibility.The full Python workflow is included in the repository for transparency and easy re-execution.<b>Data Format and Access</b><b>Primary file:</b> <code>Albumin_Degradome_Foundation_Atlas_v1.tar.xz</code><br>(contains all peptide tables in standard CSV format)<b>File Type:</b> ASCII comma-separated values (CSV)<b>Compression:</b> <code>xz -9 -T0</code> for maximal CPU-parallelised compression<b>Compatibility:</b>R, Python, MATLAB, SASExcel, LibreOfficeAny proteomics workflow (e.g., Skyline, MaxQuant preprocessing, MS/MS spectral libraries)<b>FAIR Principles</b>This dataset is fully aligned with FAIR data standards:<b>Findable:</b> Rich metadata, stable DOI, search-optimised description<b>Accessible:</b> Open-access Figshare repository<b>Interoperable:</b> Standard numeric and CSV formats<b>Reusable:</b> Transparent, reproducible Python source code included<b>Applications</b>The Albumin Degradome Foundation Atlas supports research across multiple biomedical domains:Biomarker development in liver disease, kidney dysfunction, inflammation, and systemic disordersMass-spectrometry method developmentComputational proteomics and peptide modellingAutoimmunity and neo-epitope analysisProtein–peptide interaction studiesProteolytic pathway mapping and degradomics<b>Versioning and Future Work</b>This is <b>Version 1</b> of the Albumin Degradome Foundation Atlas. Future releases will incorporate:Additional cleavage sites from newly published experimental studiesDisease-associated albumin variants and post-translational modificationsIntegration with other degradome atlases to support systems-level biomarker research<b>Citation</b>If you use this dataset, please cite the associated Figshare DOI and:Petzold A. <i>Proteolysis-Based Biomarker Repertoires in Protein Degradomics.</i><br><i>J. Neurochem.</i> 2025;169(3):e70023. doi:10.1111/jnc.70023
提供机构:
University College London
创建时间:
2025-12-08
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