2026-06-13T02:37:48Z https://api.figshare.com/v2/oai
oai:figshare.com:article/32054535 2026-04-20T10:39:03Z category_28807 category_25279 category_24136 category_24736 portal_549 item_type_3 month_year_04_2026
10.5522/04/32054535.v1 https://figshare.com/articles/dataset/_b_Visinin-like_protein_1_Degradome_Foundation_Atlas_b_/32054535 https://ndownloader.figshare.com/files/63864558 https://ndownloader.figshare.com/files/63866319 https://ndownloader.figshare.com/files/63866388 https://ndownloader.figshare.com/files/63866478 https://ndownloader.figshare.com/files/63870396 10.5522/04/32054535 Petzold, Axel Axel Petzold 0000-0002-0344-9749 <![CDATA[<b>Visinin-like protein 1 Degradome Foundation Atlas</b>]]> Applications in health Other chemical sciences not elsewhere classified Analytical biochemistry Computational neuroscience (incl. mathematical neuroscience and theoretical neuroscience) VILIP vilip1 vilip-1-expression visinin-like protein-1 VISININ-LIKE PROTEIN-1 2026-04-20 2026-04-21 Dataset 2026 University College London The VILIP-1 Degradome Foundation Atlas (Version 1) is an open-access, fully reproducible reference dataset that provides the first comprehensive in silico reconstruction of the proteolytic degradome of Visinin-like protein-1 (VILIP-1), a neuronal calcium-sensor protein encoded by VSNL1. VILIP-1 participates in intracellular calcium signalling and contributes to neuronal survival, synaptic plasticity, and intracellular signalling pathways. Elevated concentrations of VILIP-1 have been reported in neurodegenerative disorders, where the protein has been investigated as a biomarker of neuronal injury and synaptic dysfunction.

Proteins undergoing physiological turnover and stress-related modification generate complex populations of proteolytic fragments. The potential repertoire of VILIP-1-derived peptides has not previously been systematically characterized. The VILIP-1 Degradome Foundation Atlas addresses this gap by enumerating the theoretical peptide landscape that can arise from proteolytic and chemical cleavage of the VILIP-1 primary sequence.

Each predicted fragment is annotated with a rich panel of physicochemical and biochemical properties relevant to proteomics, biomarker discovery, and computational peptide analysis.



Scope and Content

The dataset comprises every predicted proteolytic fragment derived from the human VILIP-1 primary sequence based on defined cleavage boundaries. The resulting fragment space includes overlapping peptides spanning the entire protein sequence.

For each peptide, the dataset provides:

  • Peptide identifier and coordinates (start and stop positions)
  • Amino acid sequence
  • Calculated mass-to-charge ratio (m/z)
  • Molecular weight (Da)
  • Boman index
  • Net charge
  • Isoelectric point (pI)
  • Hydrophobicity
  • Instability index
  • Aliphatic index

These features provide a unified, feature-rich representation suitable for mass-spectrometry analysis, biomarker discovery, and computational proteomics workflows.



Methods Summary

The Degradome Atlas was generated using a reproducible Python workflow:

  1. Definition of cleavage sites
    Experimentally reported and computationally defined cleavage positions were specified along the full-length VILIP-1 amino-acid sequence.
  2. Fragment enumeration
    All pairwise subsequences between cleavage boundaries were generated, producing the complete theoretical fragment space of the protein.
  3. Peptide property calculation
    Physicochemical properties were calculated using the peptides Python library.
  4. Structured data export
    All peptide information was exported as structured CSV files.
  5. Dataset consolidation
    Output files were merged and compressed into a single FAIR-compliant archive (TAR.XZ format) to facilitate efficient distribution and reproducibility.

The complete Python workflow is included in the repository to enable transparent re-execution and extension to additional proteins or sequence variants.



Data Format and Access

Primary file:
VILIP1_Degradome_Foundation_Atlas_v1.tar.xz

Contents

  • CSV tables containing all predicted peptide fragments and calculated properties
  • Python scripts used to generate the degradome dataset
  • Documentation describing the workflow and dataset structure

File Type:
ASCII comma-separated values (CSV)

Compression:
xz -9 -T0 (maximum parallel compression for efficient distribution)

Compatibility

The dataset can be used directly in:

  • Python (pandas, NumPy)
  • R
  • MATLAB
  • SAS
  • Excel / LibreOffice

It can also be integrated into proteomics workflows, including:

  • Skyline
  • MaxQuant preprocessing
  • MS/MS spectral library construction
  • computational peptide modelling pipelines


FAIR Principles

This dataset follows FAIR data principles:

Findable
Rich metadata, persistent DOI, and search-optimized dataset description.

Accessible
Publicly available through present open-access Figshare repository.

Interoperable
Standard CSV format and widely used physicochemical descriptors.

Reusable
Fully reproducible Python workflow and transparent data generation pipeline.



Applications

The VILIP-1 Degradome Foundation Atlas enables research across several biomedical and computational domains:

  • Biomarker discovery in neurodegenerative disease
  • Mass-spectrometry assay development
  • Computational proteomics and peptide modelling
  • Neo-epitope discovery and immunological studies
  • Proteolytic pathway analysis
  • Systems-level degradomics

The dataset may also serve as a reference framework for interpreting peptide-level signals detected in cerebrospinal fluid or blood proteomic studies.



Versioning and Future Work

This release represents Version 1 of the VILIP-1 Degradome Foundation Atlas.

Future updates will incorporate:

  • additional experimentally validated cleavage sites
  • disease-associated sequence variants of VILIP-1
  • experimentally detected peptide fragments
  • integration with other degradome atlases to support systems-level biomarker research

These developments will progressively refine modelling of VILIP-1 proteolysis in health and neurodegenerative disease.



Citation

If you use this dataset, please cite the associated Figshare DOI:10.5522/04/32054535


and:

Petzold A. Proteolysis-Based Biomarker Repertoires in Protein Degradomics.
Journal of Neurochemistry. 2025;169(3):e70023.
doi:10.1111/jnc.70023

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