STRING Protein-Protein Interaction Query
Query the STRING database to retrieve protein-protein interactions with comprehensive confidence scores.
When to Use
- Find interaction partners for a protein (by UniProt ID)
- Retrieve confidence scores for PPIs (experimental, text mining, database)
- Build protein interaction networks for pathway analysis
- Identify potential protein complexes or functional modules
Workflow
Basic Query
from open_biomed.tools.tool_registry import TOOLS
# Query STRING for interaction partners
tool = TOOLS["ppi_string_request"]
results, _ = tool.run(uniprot_id="P04637") # TP53
# Access results
for interaction in results:
print(f"{interaction['partner_gene']}: {interaction['combined_score']}")
Custom Parameters
# High confidence interactions only, limit to 20
results, _ = tool.run(
uniprot_id="P04637",
species=9606, # Human (default)
required_score=700, # High confidence (default)
limit=20 # Max interactors
)
Parameters
| Parameter | Type | Default | Description |
|---|
| ----------- | ------ | --------- | ------------- |
uniprot_id | str | required | UniProt accession (e.g., P04637) |
species | int | 9606 | NCBI taxonomy ID (9606=human) |
required_score | int | 700 | Min confidence (150/400/700/900) |
limit | int | 50 | Max interactors to return |
Confidence Score Thresholds
| Score | Level | Use Case |
|---|
| ------- | ------- | ---------- |
| 150 | Low | Exploratory analysis |
| 400 | Medium | Balanced retrieval |
| 700 | High | Reliable interactions (default) |
| 900 | Highest | Very confident only |
Expected Output
[
{
"query_protein": "TP53",
"partner_string_id": "9606.ENSP00000340989",
"partner_gene": "SFN",
"combined_score": 0.999,
"scores": {
"experimental": 0.981,
"text_mining": 0.859,
"database": 0.75,
"coexpression": 0.0,
"phylogenetic": 0.0,
"gene_fusion": 0.0,
"neighborhood": 0.0
},
"ncbi_taxon_id": 9606
}
]
Score Interpretation
| Score Type | Source | Range |
|---|
| ------------ | -------- | ------- |
combined_score | Weighted combination | 0-1 |
experimental | Wet-lab experiments | 0-1 |
text_mining | Literature co-occurrence | 0-1 |
database | Curated databases (BioGRID, etc.) | 0-1 |
coexpression | Expression correlation | 0-1 |
phylogenetic | Phylogenetic profiles | 0-1 |
gene_fusion | Fusion events | 0-1 |
neighborhood | Genomic proximity | 0-1 |
Error Handling
| Error | Solution |
|---|
| ------- | ---------- |
| No interactions found | Lower required_score threshold |
| UniProt ID not recognized | Verify ID format (e.g., P04637) |
| Rate limited | Wait and retry; STRING allows ~5 req/sec |
| Wrong species | Check NCBI taxonomy ID |
Common Organism IDs
| Organism | Taxonomy ID |
|---|
| ---------- | ------------- |
| Human | 9606 |
| Mouse | 10090 |
| Rat | 10116 |
| E. coli | 83333 |
| S. cerevisiae | 4932 |
References
examples/basic_query.py - Complete example scriptreferences/score_details.md - Detailed score methodology- STRING API Docs: https://string-db.org/help/api/