Gnps Spectral Library Compound Retrieval

GNPS Spectral Library Compound Retrieval

Summary

Fetches MS/MS spectra and structural metadata (SMILES, precursor m/z, charge, adduct) for known and modified compounds from the GNPS spectral library by accession identifier. This retrieval is the essential first step for comparative tandem mass spectral alignment workflows where ground-truth structures must be loaded before modification site analysis can begin.

When to use

You have GNPS library accession IDs (e.g. CCMSLIB00011906190) for a reference compound and a chemically or biologically modified analog, and need to load their full MS/MS spectra and structural annotations to set up a modification-finding analysis. Use this skill when you must establish baseline spectra with known, curated metadata rather than importing raw experimental data.

When NOT to use

• Input is already a local, parsed spectrum object (e.g., .mzML or .mgf file loaded in memory) — use spectrum import instead.
• You need to search GNPS by molecular formula, mass, or structure similarity rather than by known accession ID — use GNPS network search or molecular networking tools instead.
• The compound is proprietary, unpublished, or not yet deposited in GNPS — use manual spectral entry or in-house database instead.

Inputs

• GNPS accession ID(s) (string, format: CCMSLIB* or mzspec:GNPS:GNPS-LIBRARY:accession:*)
• Spectral filtering parameters (mz_tolerance, ppm_tolerance, ratio_to_base_peak thresholds)

Outputs

• Compound object(s) with fields: spectrum (list of [m/z, intensity] pairs), precursor_mz (float), precursor_charge (int), adduct (string), smiles (string)
• Normalized peak list (intensity-scaled, filtered by abundance threshold)
• Structured metadata record (accession, source, collection date if available)

How to apply

Query the GNPS library API or web interface using a compound accession ID to retrieve the spectrum (formatted as m/z–intensity peak pairs), precursor m/z, precursor charge, ionization adduct, and SMILES string. Apply spectral filtering parameters (mz_tolerance=0.01, ppm_tolerance=40, ratio_to_base_peak=0.01) and peak normalization (normalize_peaks=True) to standardize the retrieved spectrum for downstream alignment. Instantiate a Compound object with these fields to create a queryable, structured representation suitable for ModiFinder analysis. Repeat for both the known and modified compound to establish a paired comparison set.

Related tools

• ModiFinder (Consumes retrieved Compound objects as known and modified reference structures for site localization via tandem mass spectral alignment) — https://github.com/Wang-Bioinformatics-Lab/ModiFinder_base
• GNPS Library (Authoritative source database for MS/MS spectral and structural metadata retrieval by accession) — https://gnps.ucsd.edu/
• RDKit (Parses SMILES strings and enables molecular structure visualization and comparison after retrieval) — http://www.rdkit.org/
• Python (Programming environment for scripting accession lookups, spectrum normalization, and Compound object instantiation)

Examples

# Load known and modified compounds from GNPS library
known = Compound(spectrum=s1_peaks, precursor_mz=506.2651, precursor_charge=1, adduct='[M+H]+', smiles=known_smiles)  # CCMSLIB00011906190
modified = Compound(spectrum=s2_peaks, precursor_mz=507.2730, precursor_charge=1, adduct='[M+H]+', smiles=None)  # CCMSLIB00011906105

Evaluation signals

• Retrieved spectrum contains ≥1 peak and precursor_mz is non-null and positive (validates non-empty, valid spectrum record).
• Precursor charge is a positive integer (int ≥ 1) and adduct string matches common ion formats (e.g. '[M+H]+', '[M-H]-').
• SMILES string parses without error in RDKit and produces a valid molecular graph (validates structural integrity).
• Retrieved spectrum, when normalized with normalize_peaks=True and filtered by ratio_to_base_peak=0.01, contains peak intensities in [0, 1] range (validates normalization was applied).
• For paired comparisons (known + modified), both Compound objects have matching precursor_charge and compatible adduct classes (e.g. both positive or both negative), indicating compatible ionization contexts.

Limitations

• GNPS accession IDs may become obsolete or records may be merged; no versioning guarantee is provided by the library.
• Retrieved SMILES may be missing or incorrect if the record was deposited without structural validation; external chemical database cross-referencing may be needed.
• Spectral filtering parameters (mz_tolerance, ppm_tolerance, ratio_to_base_peak) must be chosen a priori; no automated recommendation is provided for dataset-specific optimization.
• GNPS library records reflect the ionization and instrumental conditions of the original deposition; retrieved spectra may not match user's instrument settings or desired energy regime.

Evidence

• [other] Workflow step of loading compounds from GNPS library before analysis: "Get compound from GNPS; Draw the molecule"
• [other] Specific accession IDs used in the paper's evaluation task: "Load known compound (CCMSLIB00011906190) and modified compound (CCMSLIB00011906105) from GNPS"
• [other] Spectral filtering parameters applied during retrieval: "with mz_tolerance=0.01, ppm_tolerance=40, ratio_to_base_peak=0.01, normalize_peaks=True"
• [readme] Core API for constructing Compound objects from retrieved data: "main_compound = Compound( spectrum=s1_peaks, # Formatted as [[mz, int], ...] precursor_mz=s1_prec_mz, # Float precursor_charge=s1_charge,"
• [intro] Purpose of spectral retrieval in modification site analysis: "ModiFinder is a tool for site localization of structural modifications using MS/MS data"