alterlab-brenda

BRENDA Database

Overview

BRENDA (BRaunschweig ENzyme DAtabase) is the world's most comprehensive enzyme information system, containing detailed enzyme data from scientific literature. Query kinetic parameters (Km, kcat), reaction equations, substrate specificities, organism information, and optimal conditions for enzymes using the official SOAP API. Access over 45,000 enzymes with millions of kinetic data points for biochemical research, metabolic engineering, and enzyme discovery.

When to Use This Skill

This skill should be used when:

• Searching for enzyme kinetic parameters (Km, kcat, Vmax)
• Retrieving reaction equations and stoichiometry
• Finding enzymes for specific substrates or reactions
• Comparing enzyme properties across different organisms
• Investigating optimal pH, temperature, and conditions
• Accessing enzyme inhibition and activation data
• Supporting metabolic pathway reconstruction and retrosynthesis
• Performing enzyme engineering and optimization studies
• Analyzing substrate specificity and cofactor requirements

Does NOT Trigger

Scenario	Use Instead
Metabolic pathway maps, KEGG Orthology, or compound-to-pathway mapping	alterlab-kegg
Genome-scale flux simulation (FBA/FVA, knockouts)	alterlab-cobrapy
Drug/compound bioactivity (IC50, Ki) against drug targets	alterlab-chembl
Protein sequence, domains, or GO annotation of an enzyme	alterlab-uniprot

Core Capabilities

BRENDA access is organized into nine capability areas. Copy-ready snippets for each live in references/capabilities.md.

1. Kinetic parameter retrieval — Km, kcat, Vmax by EC number / organism / substrate.
2. Reaction information — reaction equations and stoichiometry.
3. Enzyme discovery — find enzymes by substrate, product, or reaction pattern.
4. Organism-specific data — compare enzyme properties across organisms.
5. Environmental parameters — optimal/stability pH and temperature, cofactors.
6. Substrate specificity — Km/Vmax/kcat per substrate, affinity ranking.
7. Inhibition and activation — Ki, IC50, activators and mechanisms.
8. Enzyme engineering support — thermophilic homologs, pH-stable variants.
9. Kinetic modeling — modeling parameters and Michaelis-Menten plots.

Core Workflow

The typical entry point retrieves kinetic data by EC number, then parses the delimited response:

from scripts.brenda_client import get_km_values
from scripts.brenda_queries import parse_km_entry

km_data = get_km_values("1.1.1.1", organism="Saccharomyces cerevisiae")
for entry in km_data:
    parsed = parse_km_entry(entry)
    # parse_km_entry keys mirror the raw BRENDA fields: 'kmValue' (string)
    # plus a derived 'km_value_numeric' (float). There is no 'km_value' key.
    print(parsed.get("organism"), parsed.get("substrate"), parsed.get("km_value_numeric"))

EC numbers must be fully qualified (e.g. 1.1.1.1, not 1.1.1). Wildcards (*) broaden searches. See references/data_formats.md for the response format and parsing helpers.

SOAP calling convention. The brenda_zeep.wsdl operations take separate arguments in WSDL order — client.service.getKmValue(email, sha256_pw, "ecNumber*1.1.1.1", "organism*Homo sapiens", "kmValue*", "kmValueMaximum*", "substrate*", "commentary*", "ligandStructureId*", "literature*") — and return lists of typed objects. A single comma-joined string fails in zeep ("Missing element password"). scripts/brenda_client.py handles the argument order and converts results to field*value#… strings for the parsers.

Usage policy. BRENDA asks clients to send at most one request per second (the client enforces this), and its data are licensed CC BY 4.0 — cite BRENDA in derived work.

Installation Requirements

uv pip install zeep requests pandas matplotlib seaborn

Authentication Setup

BRENDA requires authentication credentials:

1. Create .env file:

BRENDA_EMAIL=your.email@example.com
BRENDA_PASSWORD=your_brenda_password

1. Or set environment variables:

export BRENDA_EMAIL="your.email@example.com"
export BRENDA_PASSWORD="your_brenda_password"

1. Register for BRENDA access:
   • Visit https://www.brenda-enzymes.org/
   • Create an account
   • Check your email for credentials
   • Note: There's also BRENDA_EMIAL (note the typo) for legacy support

Helper Scripts

This skill ships three Python helper scripts under scripts/:

• scripts/brenda_queries.py — high-level enzyme data analysis (parsing, search, cross-organism comparison, environmental parameters, specificity, inhibitors/activators, engineering targets).
• scripts/brenda_visualization.py — kinetic/pH/temperature/substrate plots and Michaelis-Menten curves.
• scripts/enzyme_pathway_builder.py — enzymatic pathway and retrosynthetic route construction.

Full function inventories and usage are in references/helper_scripts.md.

Reference Index

• references/api_reference.md — Complete SOAP API method docs, parameter lists/formats, EC number structure/validation, response specs, error codes, literature citation formats.
• references/capabilities.md — Copy-ready code for all nine capability areas.
• references/workflows.md — Six end-to-end workflows (discovery, cross-organism comparison, engineering targets, pathway construction, kinetic analysis, industrial selection).
• references/helper_scripts.md — Function inventory and usage for the three helper scripts.
• references/data_formats.md — BRENDA response formats, parsing patterns, rate limits, error handling, troubleshooting, and additional resources.