Metabolomics Navigator Tools, strategies & workflow guidance for metabolomics

Natural-product discovery

MS2DECIDE

Tandem mass spectrum to decision (MS2DECIDE) leverages decision theory and expert knowledge to aggregate the outputs of three widely used annotation tools (GNPS, Sirius, and ISDB-LOTUS) and compute a recommendation for targeting natural products with regard to their potential novelty.

Chemistry–Methods · 2025 · 10.1002/cmtd.202400088

LC-MSUntargeted metabolomicsNatural-product discovery
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What does this strategy enable?

MS2DECIDE combines annotations from GNPS, SIRIUS and ISDB-LOTUS using an expert-informed decision model. It supports prioritization of natural-product features for follow-up rather than establishing chemical novelty or confirming structures.

Transferable workflow

Workflow

  1. 1

    Prepare aligned inputs

    Provide a quantitative CSV table, MGF spectra and compatible SIRIUS annotation results with matching feature identifiers.

  2. 2

    Collect complementary annotations

    Obtain GNPS spectral matches and ISDB-LOTUS results alongside SIRIUS candidates.

    GNPSSIRIUS
  3. 3

    Combine evidence and prioritize

    Use the documented K-estimation method to combine annotation evidence and export ranked results for review.

    MS2DECIDE
  4. 4

    Review candidates

    Inspect spectra, annotation disagreements and experimental context before selecting follow-up experiments.

Connected resources

Tools used in this strategy

MS2DECIDEImplements K-estimation and result export.View tool entry →GNPSMolecular networking and chemical similarityView tool entry →SIRIUSMetabolite annotation and identificationView tool entry →ISDB-LOTUSExternal resource

Strategy profile

Components

Annotation or identification, Spectral search

Scope and considerations

Designed for

  • Prioritizing natural-product features using multiple annotation sources.

Important requirements

  • Compatible feature tables, MS/MS spectra and annotation files; Python and access to the services used by the chosen implementation.

Considerations

  • Scores depend on annotation coverage and the decision model; they are not experimental identification or proof of novelty.
  • Follow the repository documentation for supported SIRIUS and GNPS versions.

Reusable resources

✓ Code available✓ Published method available
Code↗Published method↗

Publication

Mejri, Yassine et al. MS2DECIDE: Aggregating Multiannotated Tandem Mass Spectrometry Data with Decision Theory Enhances Natural Products Prioritization. Chemistry–Methods (2025). DOI: 10.1002/cmtd.202400088.

doi:10.1002/cmtd.202400088