KEGG Database Reference

KEGG Database Reference

Overview

KEGG (Kyoto Encyclopedia of Genes and Genomes) is a comprehensive bioinformatics resource that maintains manually curated pathway maps and molecular interaction networks. It provides "wiring diagrams of molecular interactions, reactions and relations" for understanding biological systems.

Base URL: https://rest.kegg.jp Official Documentation: https://www.kegg.jp/kegg/rest/keggapi.html Access Restrictions: KEGG API is made available only for academic use by academic users.

KEGG Databases

KEGG integrates 16 primary databases organized into systems information, genomic information, chemical information, and health information categories:

Systems Information

• PATHWAY: Manually drawn pathway maps for metabolism, genetic information processing, environmental information processing, cellular processes, organismal systems, human diseases, and drug development
• MODULE: Functional units and building blocks of pathways
• BRITE: Hierarchical classifications and ontologies

Genomic Information

• GENOME: Complete genomes with annotations
• GENES: Gene catalogs for all organisms
• ORTHOLOGY: Ortholog groups (KO: KEGG Orthology)
• SSDB: Sequence similarity database

Chemical Information

• COMPOUND: Metabolites and other chemical substances
• GLYCAN: Glycan structures
• REACTION: Chemical reactions
• RCLASS: Reaction class (chemical structure transformation patterns)
• ENZYME: Enzyme nomenclature
• NETWORK: Network variations

Health Information

• DISEASE: Human diseases with genetic and environmental factors
• DRUG: Approved drugs with chemical structures and target information
• DGROUP: Drug groups

External Database Links

KEGG cross-references to external databases including:

• PubMed: Literature references
• NCBI Gene: Gene database
• UniProt: Protein sequences
• PubChem: Chemical compounds
• ChEBI: Chemical entities of biological interest

REST API Operations

1. INFO - Database Metadata

Syntax: /info/<database>

Retrieves release information and statistics for a database.

Examples:

• /info/kegg - KEGG system information
• /info/pathway - Pathway database information
• /info/hsa - Human organism information

2. LIST - Entry Listings

Syntax: /list/<database>[/<organism>]

Lists entry identifiers and associated names.

Parameters:

• database - Database name (pathway, enzyme, genes, etc.) or entry (hsa:10458)
• organism - Optional organism code (e.g., hsa for human, eco for E. coli)

Examples:

• /list/pathway - All reference pathways
• /list/pathway/hsa - Human-specific pathways
• /list/hsa:10458+ece:Z5100 - Specific gene entries (max 10)

Organism Codes: Three or four letter codes

• hsa - Homo sapiens (human)
• mmu - Mus musculus (mouse)
• dme - Drosophila melanogaster (fruit fly)
• sce - Saccharomyces cerevisiae (yeast)
• eco - Escherichia coli K-12 MG1655

3. FIND - Search Entries

Syntax: /find/<database>/<query>[/<option>]

Searches for entries by keywords or molecular properties.

Parameters:

• database - Database to search
• query - Search term or molecular property
• option - Optional: formula, exact_mass, mol_weight

Search Fields (database dependent):

• ENTRY, NAME, SYMBOL, GENE_NAME, DESCRIPTION, DEFINITION
• ORGANISM, TAXONOMY, ORTHOLOGY, PATHWAY, etc.

Examples:

• /find/genes/shiga toxin - Keyword search in genes
• /find/compound/C7H10N4O2/formula - Exact formula match
• /find/drug/300-310/exact_mass - Mass range search (300-310 Da)
• /find/compound/300-310/mol_weight - Molecular weight range

4. GET - Retrieve Entries

Syntax: /get/<entry>[+<entry>...][/<option>]

Retrieves full database entries or specific data formats.

Parameters:

• entry - Entry ID(s) (max 10, joined with +)
• option - Output format (optional)

Output Options:

• aaseq - Amino acid sequences (FASTA)
• ntseq - Nucleotide sequences (FASTA)
• mol - MOL format (compounds/drugs)
• kcf - KCF format (KEGG Chemical Function, compounds/drugs)
• image - PNG image (pathway maps, single entry only)
• kgml - KGML XML (pathway structure, single entry only)
• json - JSON format (pathway only, single entry only)

Examples:

• /get/hsa00010 - Glycolysis pathway (human)
• /get/hsa:10458+ece:Z5100 - Multiple genes (max 10)
• /get/hsa:10458/aaseq - Protein sequence
• /get/cpd:C00002 - ATP compound entry
• /get/hsa05130/json - Pathways in cancer as JSON
• /get/hsa05130/image - Pathway map as PNG

Image Restrictions: Only one entry allowed with image option

5. CONV - ID Conversion

Syntax: /conv/<target_db>/<source_db>

Converts identifiers between KEGG and external databases.

Supported Conversions:

• ncbi-geneid ↔ KEGG genes
• ncbi-proteinid ↔ KEGG genes
• uniprot ↔ KEGG genes
• pubchem ↔ KEGG compounds/drugs
• chebi ↔ KEGG compounds/drugs

Examples:

• /conv/ncbi-geneid/hsa - All human genes to NCBI Gene IDs
• /conv/hsa/ncbi-geneid - NCBI Gene IDs to human genes (reverse)
• /conv/uniprot/hsa:10458 - Specific gene to UniProt
• /conv/pubchem/compound - All compounds to PubChem IDs

6. LINK - Cross-References

Syntax: /link/<target_db>/<source_db>

Finds related entries within and between KEGG databases.

Common Links:

• genes ↔ pathway
• pathway ↔ compound
• pathway ↔ enzyme
• genes ↔ orthology (KO)
• compound ↔ reaction

Examples:

• /link/pathway/hsa - All pathways linked to human genes
• /link/genes/hsa00010 - Genes in glycolysis pathway
• /link/pathway/hsa:10458 - Pathways containing specific gene
• /link/compound/hsa00010 - Compounds in pathway

7. DDI - Drug-Drug Interactions

Syntax: /ddi/<drug>[+<drug>...]

Retrieves drug-drug interaction information extracted from Japanese drug labels.

Parameters:

• drug - Drug entry ID(s) (max 10, joined with +)

Examples:

• /ddi/D00001 - Interactions for single drug
• /ddi/D00001+D00002 - Interactions between multiple drugs

Pathway Classification

KEGG organizes pathways into seven major categories:

1. Metabolism

Carbohydrate, energy, lipid, nucleotide, amino acid, glycan biosynthesis and metabolism, cofactor and vitamin metabolism, terpenoid and polyketide metabolism, secondary metabolite biosynthesis, xenobiotics biodegradation

Example pathways:

• map00010 - Glycolysis / Gluconeogenesis
• map00020 - Citrate cycle (TCA cycle)
• map00190 - Oxidative phosphorylation

2. Genetic Information Processing

Transcription, translation, folding/sorting/degradation, replication and repair

Example pathways:

• map03010 - Ribosome
• map03020 - RNA polymerase
• map03040 - Spliceosome

3. Environmental Information Processing

Membrane transport, signal transduction

Example pathways:

• map02010 - ABC transporters
• map04010 - MAPK signaling pathway

4. Cellular Processes

Transport and catabolism, cell growth and death, cellular community, cell motility

Example pathways:

• map04140 - Autophagy
• map04210 - Apoptosis

5. Organismal Systems

Immune, endocrine, circulatory, digestive, nervous, sensory, development, environmental adaptation

Example pathways:

• map04610 - Complement and coagulation cascades
• map04910 - Insulin signaling pathway

6. Human Diseases

Cancer, immune diseases, neurodegenerative diseases, cardiovascular diseases, metabolic diseases, infectious diseases

Example pathways:

• map05200 - Pathways in cancer
• map05010 - Alzheimer disease

7. Drug Development

Chronological classification and target-based classification

Common Identifiers and Naming

Pathway IDs

• map##### - Reference pathway (generic)
• hsa##### - Human-specific pathway
• mmu##### - Mouse-specific pathway
• Format: organism code + 5-digit number

Gene IDs

• hsa:10458 - Human gene (organism:gene_id)
• Format: organism code + colon + gene number

Compound IDs

• cpd:C00002 - ATP
• Format: cpd:C#####

Drug IDs

• dr:D00001 - Drug entry
• Format: dr:D#####

Enzyme IDs

• ec:1.1.1.1 - Alcohol dehydrogenase
• Format: ec:EC_number

KO (KEGG Orthology) IDs

• ko:K00001 - Ortholog group
• Format: ko:K#####

API Limitations and Best Practices

Rate Limits and Restrictions

• Maximum 10 entries per single operation (except image/kgml: 1 entry)
• Academic use only - commercial use requires separate licensing
• No explicit rate limit documented, but avoid rapid-fire requests

HTTP Status Codes

• 200 - Success
• 400 - Bad request (syntax error in query)
• 404 - Not found (entry or database doesn't exist)

Best Practices

1. Always check HTTP status codes in responses
2. For bulk operations, batch entries using + (up to 10)
3. Cache results locally to reduce API calls
4. Use specific organism codes when possible for faster results
5. For pathway visualization, use the web interface or KGML/JSON formats
6. Parse tab-delimited output carefully (consistent format across operations)

Integration with Other Tools

Biopython Integration

Biopython provides Bio.KEGG.REST module for easier Python integration:

from Bio.KEGG import REST
result = REST.kegg_list("pathway").read()

KEGGREST (R/Bioconductor)

R users can use the KEGGREST package:

library(KEGGREST)
pathways <- keggList("pathway")

Common Analysis Workflows

Workflow 1: Gene to Pathway Mapping

1. Get gene ID(s) from your organism
2. Use /link/pathway/<gene_id> to find associated pathways
3. Use /get/<pathway_id> to retrieve detailed pathway information

Workflow 2: Pathway Enrichment Context

1. Use /list/pathway/<org> to get all organism pathways
2. Use /link/genes/<pathway_id> to get genes in each pathway
3. Perform statistical enrichment analysis

Workflow 3: Compound to Reaction Mapping

1. Use /find/compound/<name> to find compound ID
2. Use /link/reaction/<compound_id> to find reactions
3. Use /link/pathway/<reaction_id> to find pathways containing reactions

Workflow 4: ID Conversion for Integration

1. Use /conv/uniprot/<org> to map KEGG genes to UniProt
2. Use /conv/ncbi-geneid/<org> to map to NCBI Gene IDs
3. Integrate with other databases using converted IDs

Additional Resources

• KEGG Mapper: https://www.kegg.jp/kegg/mapper/ - Interactive pathway mapping
• BlastKOALA: Automated annotation for sequenced genomes
• GhostKOALA: Annotation for metagenomes and metatranscriptomes
• KEGG Modules: https://www.kegg.jp/kegg/module.html
• KEGG Brite: https://www.kegg.jp/kegg/brite.html