GENERAL INFORMATION

1. Title of Dataset: Neuromelanin Plasma Interactome


2. Authors: Alexandra Moreno-García, Olga Calero, Miguel Calero, and Antonio J. Martín-Galiano

3. Date of data collection: January 2022


4. Date of data publication on repository: June 2026


5. Geographic location of data collection <latitude, longitude, or city/region, Country, continent as appropriate>: Majadahonda 28210, Madrid (SPAIN)


6. Information about funding sources that supported the collection of the data (including research project reference/acronym):
- Spanish Ministry of Science, Innovation and Universities (grant PID2023-152789OB-I00), 
- Intramural Strategic Action in Health (AESI) of the Instituto de Salud Carlos III (ISCIII, Spain) (grant PI25CIII00030), 
- National Programme for the Promotion of Talent and its Employability from the Spanish Ministry of Science (Grant PEJ-2014-A95295),
- Spanish research network CIBER de Enfermedades Neurodegenerativas (CIBERNED), ISCIII.

7. Recommended citation for this dataset: 
To be completed.



SHARING/ACCESS/CONTEXT INFORMATION

1. Usage Licenses/restrictions placed on the data (please indicate if different data files have different usage license): CC BY

2. Links to publications/other research outputs that cite the data: 

To be completed.

3. Links to publications/other research outputs that use the data:

To be completed.
4. Links to other publicly accessible locations of the data: 

To be completed.
5. Links/relationships to ancillary data sets: 
To be completed.

6. Was data derived from another source? If so, please add link where such work is located:

No


DATA & FILE OVERVIEW

1. File List: 

NBPP_ProteinAbundance_rawdata.tsv
NBPP_suppl_table_1.tsv
NBPP_suppl_table_2_enrichment.Process.tsv
NBPP_suppl_table_3_enrichment.DISEASES_.tsv

2. Relationship between files, if important: 


3. Additional related data collected that was not included in the current data package: 


4. Are there multiple versions of the dataset? If so, please indicate where they are located:
No


METHODOLOGICAL INFORMATION

1. Description of methods used for collection/generation of data: 
Proteomics analysis was performed at the CNB-CSIC proteomics facility (Madrid, Spain). Before analysis, to remove potential contamination and precipitated material, the eluates from each column were loaded onto S-Trap™ columns after reduction and alkylation with tris(2-carboxyethyl)phosphine (TCEP) and chloroacetamide, and then digested with trypsin. Each digest was cleaned with a StageTip C18 column (#NC002838, Thermofisher) before liquid chromatography electrospray ionization tandem mass spectrometry (LC-ESI-MS/MS) analysis. For label-free protein identification and quantification, data corresponding to 500 ng of protein digestion mixture (quantified by fluorimetry) were acquired through a combination of 60-minute liquid chromatography using a C-18 reverse phase column that separated peptides by hydrophobicity, followed by fragmentation of eluted peptides in the Orbitrap Exploris 240 (Thermo Fisher Scientific) mass spectrometer for liquid chromatography–tandem mass spectrometry (LC-MS/MS). Raw data files were explored using the Mascot search engine against the reviewed SwissProt Homo sapiens database. Proteins were deemed identified when they had a Q-value < 0.01, with at least 2 peptide-spectrum matches and at least 2 unique peptides. The abundance of each protein was normalized to the sum of the intensities of all its peptides. Proteins that were ≥ 2-fold concentrated compared to control resin or that were found only in pLD and/or pNA resin were considered as NBPPs 

2. Methods for processing the data: 
The proteins detected in ≥ 15 % of the experiments in the common Repository of Adventitious Proteins, cRAP, and fetal bovine serum proteins, cRFP databases were filtered out. The human plasma proteome, including protein concentration data, was downloaded from the Human Plasma PeptideAtlas (release 2025), a curated database providing high-confidence identifications and relative abundance estimates for plasma proteins. Only gene products unequivocally linked to abundance values were retained for downstream analyses. These data were used to evaluate the abundance distribution of NBPPs relative to the overall plasma proteome. 
The molecular weight, pI, and grand average of hydropathy (GRAVY) index were calculated using the PROTPARAM program of EXPASY. Proteins with structurally disordered regions were identified with IUPred3. Pre-calculated Gene Ontology terms and glycosylation annotations for the human proteome were downloaded from Uniprot. 
For protein conformational analyses, AlphaFold2 models for the entire human proteome (Proteome ID: UP000005640) were downloaded from the original repository (https://alphafold.ebi.ac.uk/download). To assess the solvent accessibility of Asp and Glu residues, surfaces for all NBPPs were calculated with the get_surface module of the PDB package of Biopython. The atomic depths were calculated using the min_dist module. Acidic residues were considered solvent-exposed when at least one of their carboxyl-group oxygens was located at 1.4 Å or less from the surface. DSSP assignments for secondary structure were parsed from pdb-format AlphaFold2 files using an in-house Python script.


3. Instrument- or software-specific information needed to interpret/reproduce the data, please indicate their location: 


4. Standards and calibration information, if appropriate: 


5. Environmental/experimental conditions: 


6. Describe any quality-assurance procedures performed on the data: 
 Proteins were deemed identified when they had a Q-value < 0.01, with at least 2 peptide-spectrum matches and at least 2 unique peptides. The abundance of each protein was normalized to the sum of the intensities of all its peptides. Proteins that were ≥ 2-fold concentrated compared to control resin or that were found only in pLD and/or pNA resin were considered as NBPPs 


7. People involved with sample collection, processing, analysis and/or submission, please specify using CREDIT roles https://credit.niso.org/: 


8. Author contact information: Miguel Calero (mcalero@isciii.es), Antonio J. Martín-Galiano (mgaliano@isciii.es)

DATA-SPECIFIC INFORMATION:


1. Number of variables: Variables specified in header of each tsv file.


2. Number of cases/rows: NA


3. Variable List: Variables specified in header of each tsv file.


4. Missing data codes: empty or ¨Not Found¨


5. Specialized formats or other abbreviations used: Variables specified in header of each tsv file.

6. Dictionaries/codebooks used: 


7. Controlled vocabularies/ontologies used: Disease Ontology & Biological Process