Skip to main content Home Skills LLMs & Models hmdb-database Access Human Metabolome Database (220K+ metabolites). Search by name/ID/structure, retrieve chemical properties, biomarker data, NMR/MS spectra, pathways, for metabolomics and identification.
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HMDB Database
Overview
The Human Metabolome Database (HMDB) is a comprehensive, freely available resource containing detailed information about small molecule metabolites found in the human body.
When to Use This Skill
This skill should be used when performing metabolomics research, clinical chemistry, biomarker discovery, or metabolite identification tasks.
Database Contents
HMDB version 5.0 (current as of 2025) contains:
220,945 metabolite entries covering both water-soluble and lipid-soluble compounds8,610 protein sequences for enzymes and transporters involved in metabolism130+ data fields per metabolite including:
Chemical properties (structure, formula, molecular weight, InChI, SMILES)
Clinical data (biomarker associations, diseases, normal/abnormal concentrations)
Biological information (pathways, reactions, locations)
Spectroscopic data (NMR, MS, MS-MS spectra)
External database links (KEGG, PubChem, MetaCyc, ChEBI, PDB, UniProt, GenBank)
Core Capabilities
1. Web-Based Metabolite Searches
Access HMDB through the web interface at https://www.hmdb.ca/ for:
Text Searches:
Search by metabolite name, synonym, or identifier (HMDB ID)
Example HMDB IDs: HMDB0000001, HMDB0001234
Search by disease associations or pathway involvement
Query by biological specimen type (urine, serum, CSF, saliva, feces, sweat)
Structure-Based Searches:
Use ChemQuery for structure and substructure searches
Search by molecular weight or molecular weight range
Use SMILES or InChI strings to find compounds
LC-MS spectral matching
GC-MS spectral matching
NMR spectral searches for metabolite identification
Combine multiple criteria (name, properties, concentration ranges)
Filter by biological locations or specimen types
Search by protein/enzyme associations
2. Accessing Metabolite Information When retrieving metabolite data, HMDB provides:
Systematic name, traditional names, and synonyms
Chemical formula and molecular weight
Structure representations (2D/3D, SMILES, InChI, MOL file)
Chemical taxonomy and classification
Metabolic pathways and reactions
Associated enzymes and transporters
Subcellular locations
Biological roles and functions
Normal concentration ranges in biological fluids
Biomarker associations with diseases
Clinical significance
Toxicity information when applicable
Experimental and predicted NMR spectra
MS and MS-MS spectra
Retention times and chromatographic data
Reference peaks for identification
3. Downloadable Datasets
XML : Complete metabolite, protein, and spectra dataSDF : Metabolite structure files for cheminformaticsFASTA : Protein and gene sequencesTXT : Raw spectra peak listsCSV/TSV : Tabular data exports
All metabolites or filtered by specimen type
Protein/enzyme sequences
Experimental and predicted spectra (NMR, GC-MS, MS-MS)
Pathway information
Download XML format for comprehensive data including all fields
Use SDF format for structure-based analysis and cheminformatics workflows
Parse CSV/TSV formats for integration with data analysis pipelines
Check version dates to ensure up-to-date data (current: v5.0, 2023-07-01)
Free for academic and non-commercial research
Commercial use requires explicit permission (contact samackay@ualberta.ca )
Cite HMDB publication when using data
4. Programmatic API Access API Availability:
HMDB does not provide a public REST API. Programmatic access requires contacting the development team:
Alternative Programmatic Access:
R/Bioconductor : Use the hmdbQuery package for R-based queries
Install: BiocManager::install("hmdbQuery")
Provides HTTP-based querying functions
Downloaded datasets : Parse XML or CSV files locally for programmatic analysisWeb scraping : Not recommended; contact team for proper API access instead
5. Common Research Workflows Metabolite Identification in Untargeted Metabolomics:
Obtain experimental MS or NMR spectra from samples
Use HMDB spectral search tools to match against reference spectra
Verify candidates by checking molecular weight, retention time, and MS-MS fragmentation
Review biological plausibility (expected in specimen type, known pathways)
Search HMDB for metabolites associated with disease of interest
Review concentration ranges in normal vs. disease states
Identify metabolites with strong differential abundance
Examine pathway context and biological mechanisms
Cross-reference with literature via PubMed links
Identify metabolites of interest from experimental data
Look up HMDB entries for each metabolite
Extract pathway associations and enzymatic reactions
Use linked SMPDB (Small Molecule Pathway Database) for pathway diagrams
Identify pathway enrichment for biological interpretation
Download HMDB data in XML or CSV format
Parse and extract relevant fields for local database
Link with external IDs (KEGG, PubChem, ChEBI) for cross-database queries
Build local tools or pipelines incorporating HMDB reference data
Related HMDB Resources The HMDB ecosystem includes related databases:
DrugBank : ~2,832 drug compounds with pharmaceutical informationT3DB (Toxin and Toxin Target Database) : ~3,670 toxic compoundsSMPDB (Small Molecule Pathway Database) : Pathway diagrams and mapsFooDB : ~70,000 food component compounds These databases share similar structure and identifiers, enabling integrated queries across human metabolome, drug, toxin, and food databases.
Best Practices
Verify metabolite identifications with multiple evidence types (spectra, structure, properties)
Check experimental vs. predicted data quality indicators
Review citations and evidence for biomarker associations
Note HMDB version used in research (current: v5.0)
Databases are updated periodically with new entries and corrections
Re-query for updates when publishing to ensure current information
Always cite HMDB in publications using the database
Reference specific HMDB IDs when discussing metabolites
Acknowledge data sources for downloaded datasets
For large-scale analysis, download complete datasets rather than repeated web queries
Use appropriate file formats (XML for comprehensive data, CSV for tabular analysis)
Consider local caching of frequently accessed metabolite information
Reference Documentation See references/hmdb_data_fields.md for detailed information about available data fields and their meanings.
