brenda-database

What this skill does

# 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**:
```python
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**:
```python
for entry in km_data:
    print(f"Km: {entry}")
    # Example output: "organism*Homo sapiens#substrate*ethanol#kmValue*1.2#commentary*"
```

**Extract Specific Information**:
```python
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**:
```python
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**:
```python
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**:
```python
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**:
```python
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**:
```python
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**:
```python
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**:
```python
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**:
```python
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**:
```python
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**:
```python
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**:
```python
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**:
```python
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**:
```python
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**:
```python
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**:
```python
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**:
```python
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']