The Neurogranin (Ng) 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 neurogranin, a postsynaptic neuronal protein encoded by the NRGN gene. Neurogranin is a calmodulin-binding protein that plays a key role in synaptic plasticity by regulating calcium–calmodulin signaling pathways within dendritic spines. Through its interaction with calmodulin, neurogranin modulates intracellular calcium dynamics and contributes to mechanisms underlying learning, memory, and long-term potentiation.Beyond its established role in synaptic physiology, neurogranin has attracted increasing attention as a candidate biomarker of neuronal injury and synaptic dysfunction. Elevated concentrations of neurogranin have been reported in several neurological disorders, where the protein has been investigated as a potential indicator of synaptic plasticity, degeneration and neurodegenerative disease processes.Proteins undergoing physiological turnover, proteolytic regulation, and pathological modification generate complex populations of peptide fragments. Experimental studies have demonstrated that neurogranin can be proteolytically processed by endogenous proteases involved in neuronal signaling and protein turnover. However, the potential repertoire of neurogranin-derived peptide fragments has not previously been systematically characterized.The Ng Degradome Foundation Atlas addresses this gap by enumerating the theoretical degradome that may arise from enzymatic or chemical cleavage of the Ng primary sequence. Each predicted fragment is annotated with a comprehensive panel of physicochemical properties relevant to proteomics, biomarker discovery, and computational peptide analysis.Scope and ContentThe dataset comprises every predicted proteolytic fragment derived from the human Ng 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 sequenceCalculated mass-to-charge ratio (m/z)Molecular weight (Da)Boman indexNet chargeIsoelectric point (pI)HydrophobicityInstability indexAliphatic indexThese features provide a unified, feature-rich representation suitable for mass-spectrometry analysis, biomarker discovery, and computational proteomics workflows.Methods SummaryThe Ng Degradome Atlas was generated using a reproducible Python workflow consisting of the following steps:Definition of cleavage sitesExperimentally reported and computationally defined cleavage positions were specified along the neurogranin amino-acid sequence.Fragment enumerationAll pairwise subsequences between cleavage boundaries were generated, producing the complete theoretical degradome.Peptide property calculationPhysicochemical properties were calculated using the peptides Python library.Structured data exportAll peptide information was exported as structured CSV tables.Dataset consolidationOutput 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, enabling transparent re-execution and extension to additional proteins, cleavage definitions, or sequence variants.Data Format and AccessPrimary fileNeurogranin_Degradome_Foundation_Atlas_v1.tar.xzContentsCSV tables containing all predicted peptide fragments and calculated propertiesPython scripts used to generate the degradome datasetDocumentation describing the workflow and dataset structureFile TypeASCII comma-separated values (CSV)Compressionxz -9 -T0 (maximum parallel compression for efficient distribution)CompatibilityThe dataset can be used directly in:Python (pandas, NumPy)RMATLABSASExcel / LibreOfficeIt can also be integrated into proteomics workflows, including:SkylineMaxQuant preprocessingMS/MS spectral library constructioncomputational peptide modelling pipelinesFAIR PrinciplesThis dataset follows FAIR data principles.FindableRich metadata, persistent DOI, and a search-optimized dataset description.AccessiblePublicly available through the open-access Figshare repository.InteroperableStandard CSV format and widely used physicochemical descriptors enable integration with common computational and proteomics tools.ReusableThe dataset includes a fully reproducible Python workflow and transparent data generation pipeline.ApplicationsThe Neurogranin Degradome Foundation Atlas enables research across several biomedical and computational domains:Biomarker discovery in neurodegenerative diseaseMass-spectrometry assay developmentComputational proteomics and peptide modellingNeo-epitope discovery and immunological studiesProteolytic pathway analysisSystems-level degradomicsThe dataset may also serve as a reference framework for interpreting peptide-level signals detected in cerebrospinal fluid or blood proteomic studies of neurological disease.Versioning and Future WorkThis release represents Version 1 of the Neurogranin Degradome Foundation Atlas.Future updates will incorporate:additional experimentally validated cleavage sitesdisease-associated sequence variants of neurograninexperimentally detected peptide fragmentsintegration with other degradome atlases to support systems-level biomarker researchThese developments will progressively refine modelling of neurogranin proteolysis in health and neurodegenerative disease.CitationIf you use this dataset, please cite this Figshare record:DOI: 10.5522/04/32168850