| name | target-profile |
| description | Generate comprehensive target profiles including druggability assessment,
disease associations, pathway context, and competitive landscape.
Use this skill when analyzing drug targets for validation, dossier creation,
or competitive intelligence. Supports gene symbols (EGFR), protein names,
or UniProt IDs.
Keywords: target, dossier, validation, druggability, tractability, target analysis
|
| category | Target Analysis |
| tags | ["target","drug-discovery","dossier","validation"] |
| version | 1.0.0 |
| author | Drug Discovery Team |
| dependencies | ["opentargets-rest-api","uniprot-rest-api","chembl-rest-api"] |
Target Profile Skill
Generate comprehensive target dossiers for drug discovery decision-making.
Quick Start
/target EGFR
/target-profile KRAS G12C
Create a target dossier for HER2 including clinical trials
Analyze druggability of BRAF V600E
What's Included
| Section | Description | Data Source |
|---|
| Executive Summary | Key insights in one page | Aggregated |
| Target Overview | Gene/protein name, class, location | UniProt |
| Druggability | Tractability scores, target class | Open Targets |
| Disease Associations | Associated diseases, evidence scores | Open Targets |
| Pathways | Signaling pathways, interactions | KEGG, Reactome |
| Competition | Existing drugs, pipeline | ChEMBL, DrugBank |
| Safety | Known safety concerns | Pharos, SIDER |
Data Sources
| Source | API | Coverage |
|---|
| Open Targets | api.opentargets.org | 20k+ targets, 1.2M associations |
| UniProt | rest.uniprot.org | 200M+ proteins |
| ChEMBL | www.ebi.ac.uk/chembl/api | 2.5M+ compounds |
| KEGG | rest.kegg.jp | 500+ pathways |
| Reactome | reactome.org | 2600+ pathways |
Output Structure
# EGFR Target Profile
## Executive Summary
EGFR is a high-tractability receptor tyrosine kinase with strong validation
in NSCLC. 9 drugs approved, 34 in development. Key opportunity: resistance
mechanisms and combination therapies.
## Quick Stats
| Metric | Value |
|--------|-------|
| Tractability | 8.2/10 (Small molecule) |
| Disease Associations | 142 diseases |
| Approved Drugs | 9 |
| Pipeline Candidates | 34 |
| Safety Tier | 2 (Moderate risk) |
## 1. Target Overview
- **Gene**: EGFR (ERBB1)
- **Protein**: Epidermal growth factor receptor
- **Class**: Receptor tyrosine kinase
- **Location**: Cell membrane (Plasma membrane)
- **Length**: 1210 amino acids
- **MW**: 134 kDa
## 2. Druggability Assessment
### Tractability Scores
| Modality | Score | Evidence |
|----------|-------|----------|
| Small molecule | 8.2/10 | 9 approved drugs |
| Antibody | 7.8/10 | 4 approved antibodies |
| PROTAC | 6.5/10 | Emerging approach |
### Target Development Level
**Tclin (Highest)** - Target with drugs approved for clinical use
## 3. Disease Associations
| Disease | Association Score | Evidence Type |
|---------|------------------|---------------|
| Lung adenocarcinoma | 0.95 | Genetic association |
| Glioblastoma | 0.87 | Somatic mutation |
| Head and neck cancer | 0.82 | Genetic association |
## 4. Pathway Context
- **Primary Pathway**: ErbB signaling pathway (KEGG: hsa04012)
- **Upstream**: EGF, TGF-alpha, Amphiregulin
- **Downstream**: MAPK, PI3K-Akt, JAK-STAT
- **Cross-talk**: MET, HER2, HER3
## 5. Competitive Landscape
### Approved Drugs
| Drug | Company | Year | Type | Indication |
|------|---------|------|------|------------|
| Erlotinib | Astellas | 2004 | TKI | NSCLC |
| Gefitinib | AstraZeneca | 2003 | TKI | NSCLC |
| Osimertinib | AstraZeneca | 2015 | 3rd-gen TKI | NSCLC |
| Drug | Company | Phase | Differentiation |
|------|---------|-------|----------------|
| Lazertinib | Yuhan | III | 3rd-gen, wild-type sparing |
| Nazartinib | Novartis | III | 3rd-gen, CNS active |
: Skin rash, diarrhea (class effect)
: Cardiac toxicity (rare)
: 2 (Manageable risk)
Resistance mechanisms (C797S, MET amplification)
Combination therapies (EGFR + MET)
CNS-penetrant candidates
Biomarker-driven patient selection
Crowded competitive space
Generic competition (1st gen)
Resistance development
Examples
Basic Profile
/target EGFR
With Specific Focus
/target KRAS --focus safety
Analyze safety profile of BTK
/target HER2 --focus competition
Compare Multiple Targets
Compare targets EGFR, HER2, HER3 for NSCLC treatment
Rank KRAS, NRAS, HRAS by druggability
Specific Analysis
/target BRAF V600C
Assess druggability of mutant BRAF
What is the tractability of KRAS G12C?
Running Scripts
The scripts/ directory contains data fetching utilities:
python scripts/fetch_target_data.py EGFR --output data.json
python scripts/fetch_target_data.py EGFR --uniprot --chembl --pathways -o full.json
python scripts/fetch_target_data.py KRAS --diseases-only
Requirements
None for basic use (uses public APIs).
For advanced features and scripts:
pip install requests pandas
Additional Resources
Best Practices
- Use official gene symbols (HGNC nomenclature) for best results
- Include mutation if relevant (e.g., "KRAS G12C")
- Specify focus when you need deeper analysis on one area
- Compare targets to support decision-making
Common Pitfalls
| Pitfall | Solution |
|---|
| Ambiguous gene names | Use official HGNC symbols |
| Multiple isoforms | Specify isoform number if needed |
| Species confusion | Assume human unless specified |
| Outdated info | Data is current as of last API fetch |
