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ChEMBL Integration
Drug-target interactions and bioactivity data integration
Overview
Omic's ChEMBL integration connects you to the EMBL-EBI's manually curated database of bioactive molecules with drug-like properties. Access millions of compound-target interactions extracted from scientific literature to inform your drug discovery decisions.
Key Capabilities
- ✓Query 2.4M+ compounds with curated bioactivity data
- ✓Access 15,000+ protein targets with activity measurements
- ✓Retrieve IC50, Ki, Kd, and EC50 values from literature
- ✓Track compound progression through clinical trials
Data Flow
1. Input: Target protein, compound, or assay query
2. ChEMBL: Retrieve curated bioactivity measurements
3. Omic: AI analysis of activity cliffs and selectivity
4. Output: Target engagement predictions and lead candidates
Technical Specifications
Query Types
- • Target-based (UniProt ID, gene symbol)
- • Compound-based (ChEMBL ID, SMILES)
- • Assay-based (assay type, organism)
- • Activity-based (IC50 range, activity type)
- • Document-based (PubMed ID, DOI)
Output Data
- • Standardized activity values (pIC50, pKi)
- • Assay descriptions and conditions
- • Target selectivity profiles
- • Clinical development status
- • Source publication references
Example API Call
# Query ChEMBL for target bioactivity
from omic import ChEMBL
# Get all compounds active against EGFR
egfr_compounds = ChEMBL.get_activities(
target="EGFR_HUMAN",
activity_type="IC50",
max_value=100, # nM
organism="Homo sapiens"
)
# Analyze selectivity across kinase family
selectivity = ChEMBL.selectivity_profile(
compounds=egfr_compounds[:50],
target_family="Kinase"
)
# Predict activity for novel compounds
predictions = omic.predict_activity(
compounds=my_compounds,
training_data=egfr_compounds
)ChEMBL Database Coverage
2.4M+
Compounds
15K+
Targets
20M+
Activities
88K+
Documents
Common Use Cases
Target Validation
Assess target tractability by analyzing existing compounds and their bioactivity profiles against your target of interest.
Lead Optimization
Learn from historical SAR data to guide medicinal chemistry decisions and predict activity cliffs.
Selectivity Profiling
Identify potential off-target liabilities by analyzing compound activity across related protein families.
Competitive Intelligence
Track compounds in clinical development and understand the competitive landscape for your therapeutic area.