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
Core Capabilities
1. Kinetic Parameter Retrieval
Access comprehensive kinetic data for enzymes:
Get Km Values by EC Number:
from brenda_client import get_km_values
# Get Km values for all organisms
km_data = get_km_values("1.1.1.1") # Alcohol dehydrogenase
# Get Km values for specific organism
km_data = get_km_values("1.1.1.1", organism="Saccharomyces cerevisiae")
# Get Km values for specific substrate
km_data = get_km_values("1.1.1.1", substrate="ethanol")
Parse Km Results:
for entry in km_data:
print(f"Km: {entry}")
# Example output: "organism*Homo sapiens#substrate*ethanol#kmValue*1.2#commentary*"
Extract Specific Information:
from scripts.brenda_queries import parse_km_entry, extract_organism_data
for entry in km_data:
parsed = parse_km_entry(entry)
organism = extract_organism_data(entry)
print(f"Organism: {parsed['organism']}")
print(f"Substrate: {parsed['substrate']}")
print(f"Km value: {parsed['km_value']}")
print(f"pH: {parsed.get('ph', 'N/A')}")
print(f"Temperature: {parsed.get('temperature', 'N/A')}")
2. Reaction Information
Retrieve reaction equations and details:
Get Reactions by EC Number:
from brenda_client import get_reactions
# Get all reactions for EC number
reactions = get_reactions("1.1.1.1")
# Filter by organism
reactions = get_reactions("1.1.1.1", organism="Escherichia coli")
# Search specific reaction
reactions = get_reactions("1.1.1.1", reaction="ethanol + NAD+")
Process Reaction Data:
from scripts.brenda_queries import parse_reaction_entry, extract_substrate_products
for reaction in reactions:
parsed = parse_reaction_entry(reaction)
substrates, products = extract_substrate_products(reaction)
print(f"Reaction: {parsed['reaction']}")
print(f"Organism: {parsed['organism']}")
print(f"Substrates: {substrates}")
print(f"Products: {products}")
3. Enzyme Discovery
Find enzymes for specific biochemical transformations:
Find Enzymes by Substrate:
from scripts.brenda_queries import search_enzymes_by_substrate
# Find enzymes that act on glucose
enzymes = search_enzymes_by_substrate("glucose", limit=20)
for enzyme in enzymes:
print(f"EC: {enzyme['ec_number']}")
print(f"Name: {enzyme['enzyme_name']}")
print(f"Reaction: {enzyme['reaction']}")
Find Enzymes by Product:
from scripts.brenda_queries import search_enzymes_by_product
# Find enzymes that produce lactate
enzymes = search_enzymes_by_product("lactate", limit=10)
Search by Reaction Pattern:
from scripts.brenda_queries import search_by_pattern
# Find oxidation reactions
enzymes = search_by_pattern("oxidation", limit=15)
4. Organism-Specific Enzyme Data
Compare enzyme properties across organisms:
Get Enzyme Data for Multiple Organisms:
from scripts.brenda_queries import compare_across_organisms
organisms = ["Escherichia coli", "Saccharomyces cerevisiae", "Homo sapiens"]
comparison = compare_across_organisms("1.1.1.1", organisms)
for org_data in comparison:
print(f"Organism: {org_data['organism']}")
print(f"Avg Km: {org_data['average_km']}")
print(f"Optimal pH: {org_data['optimal_ph']}")
print(f"Temperature range: {org_data['temperature_range']}")
Find Organisms with Specific Enzyme:
from scripts.brenda_queries import get_organisms_for_enzyme
organisms = get_organisms_for_enzyme("6.3.5.5") # Glutamine synthetase
print(f"Found {len(organisms)} organisms with this enzyme")
5. Environmental Parameters
Access optimal conditions and environmental parameters:
Get pH and Temperature Data:
from scripts.brenda_queries import get_environmental_parameters
params = get_environmental_parameters("1.1.1.1")
print(f"Optimal pH range: {params['ph_range']}")
print(f"Optimal temperature: {params['optimal_temperature']}")
print(f"Stability pH: {params['stability_ph']}")
print(f"Temperature stability: {params['temperature_stability']}")
Cofactor Requirements:
from scripts.brenda_queries import get_cofactor_requirements
cofactors = get_cofactor_requirements("1.1.1.1")
for cofactor in cofactors:
print(f"Cofactor: {cofactor['name']}")
print(f"Type: {cofactor['type']}")
print(f"Concentration: {cofactor['concentration']}")
6. Substrate Specificity
Analyze enzyme substrate preferences:
Get Substrate Specificity Data:
from scripts.brenda_queries import get_substrate_specificity
specificity = get_substrate_specificity("1.1.1.1")
for substrate in specificity:
print(f"Substrate: {substrate['name']}")
print(f"Km: {substrate['km']}")
print(f"Vmax: {substrate['vmax']}")
print(f"kcat: {substrate['kcat']}")
print(f"Specificity constant: {substrate['kcat_km_ratio']}")
Compare Substrate Preferences:
from scripts.brenda_queries import compare_substrate_affinity
comparison = compare_substrate_affinity("1.1.1.1")
sorted_by_km = sorted(comparison, key=lambda x: x['km'])
for substrate in sorted_by_km[:5]: # Top 5 lowest Km
print(f"{substrate['name']}: Km = {substrate['km']}")
7. Inhibition and Activation
Access enzyme regulation data:
Get Inhibitor Information:
from scripts.brenda_queries import get_inhibitors
inhibitors = get_inhibitors("1.1.1.1")
for inhibitor in inhibitors:
print(f"Inhibitor: {inhibitor['name']}")
print(f"Type: {inhibitor['type']}")
print(f"Ki: {inhibitor['ki']}")
print(f"IC50: {inhibitor['ic50']}")
Get Activator Information:
from scripts.brenda_queries import get_activators
activators = get_activators("1.1.1.1")
for activator in activators:
print(f"Activator: {activator['name']}")
print(f"Effect: {activator['effect']}")
print(f"Mechanism: {activator['mechanism']}")
8. Enzyme Engineering Support
Find engineering targets and alternatives:
Find Thermophilic Homologs:
from scripts.brenda_queries import find_thermophilic_homologs
thermophilic = find_thermophilic_homologs("1.1.1.1", min_temp=50)
for enzyme in thermophilic:
print(f"Organism: {enzyme['organism']}")
print(f"Optimal temp: {enzyme['optimal_temperature']}")
print(f"Km: {enzyme['km']}")
Find Alkaline/ Acid Stable Variants:
from scripts.brenda_queries import find_ph_stable_variants
alkaline = find_ph_stable_variants("1.1.1.1", min_ph=8.0)
acidic = find_ph_stable_variants("1.1.1.1", max_ph=6.0)
9. Kinetic Modeling
Prepare data for kinetic modeling:
Get Kinetic Parameters for Modeling:
from scripts.brenda_queries import get_modeling_parameters
model_data = get_modeling_parameters("1.1.1.1", substrate="ethanol")
print(f"Km: {model_data['km']}")
print(f"Vmax: {model_data['vmax']}")
print(f"kcat: {model_data['kcat']}