open-targets

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SKILL.md (first lines)

# Open Targets Platform Lookup

Query the Open Targets Platform GraphQL API to explore gene-drug-disease associations, evidence from genetic studies, known drugs, pathway data, and overall target validation scores.

## API Base URL

```
https://api.platform.opentargets.org/api/v4/graphql
```

All requests use HTTP POST with a JSON body containing `query` and optionally `variables`.

## API Endpoints

### Search Targets by Gene Symbol

```bash
curl -s -X POST https://api.platform.opentargets.org/api/v4/graphql \
  -H "Content-Type: application/json" \
  -d '{
    "query": "query { search(queryString: \"BRAF\", entityNames: [\"target\"], page: {size: 5, index: 0}) { total hits { id name entity description } } }"
  }' | python3 -m json.tool | head -40
```

### Get Target Details

Retrieve detailed information about a specific target by Ensembl gene ID:

```bash
curl -s -X POST https://api.platform.opentargets.org/api/v4/graphql \
  -H "Content-Type: application/json" \
  -d '{
    "query": "query { target(ensemblId: \"ENSG00000157764\") { id approvedSymbol approvedName biotype functionDescriptions subcellularLocations { location } } }"
  }' | python3 -m json.tool
```

### Get Disease Associations for a Target

Find diseases associated with a gene/target, ranked by overall association score:

```bash
curl -s -X POST https://api.platform.opentargets.org/api/v4/graphql \
  -H "Content-Type: application/json" \
  -d '{
    "query": "query { target(ensemblId: \"ENSG00000157764\") { approvedSymbol associatedDiseases(page: {size: 10, index: 0}) { count rows { disease { id name } score datatypeScores { id score } } } } }"
  }' | python3 -m json.tool | head -60
```

### Get Target Associations for a Disease

Find targets associated with a specific disease by EFO ID:

```bash
curl -s -X POST https://api.platform.opentargets.org/api/v4/graphql \
  -H "Content-Type: application/json" \
  -d '{
    "query": "query { disease(efoId: \"EFO_0000616\") { id name associatedTargets(page: {size: 10, index: 0}) { count rows { target { id approvedSymbol } score datatypeScores { id score } } } } }"
  }' | python3 -m json.tool | head -60
```

### Get Drug Evidence for a Target

Retrieve known drugs and clinical evidence for a target-disease pair:

```bash
curl -s -X POST https://api.platform.opentargets.org/api/v4/graphql \
  -H "Content-Type: application/json" \
  -d '{
    "query": "query { target(ensemblId: \"ENSG00000157764\") { approvedSymbol knownDrugs(page: {size: 10, index: 0}) { count rows { drug { id name mechanismsOfAction { rows { mechanismOfAction } } } phase status diseaseFromSource } } } }"
  }' | python3 -m json.tool | head -80
```

### Search Diseases

```bash
curl -s -X POST https://api.platform.opentargets.org/api/v4/graphql \
  -H "Content-Type: application/json" \
  -d '{
    "query": "query { search(queryString: \"melanoma\", entityNames: [\"disease\"], page: {size: 5, index: 0}) { total hits { id name entity description } } }"
  }' | python3 -m json.tool | head -40
```

## Evidence Types

The `datatypeScores` array contains scores for each evidence category:

- **genetic_association** -- GWAS and gene-burden analyses linking gene variants to disease
- **known_drug** -- approved or clinical-stage drugs with established target-disease evidence
- **affected_pathway** -- pathway-level evidence from Reactome and other pathway databases
- **somatic_mutation** -- cancer somatic mutation data from COSMIC, IntOGen, and others
- **literature** -- text-mined co-occurrences from Europe PMC literature
- **rna_expression** -- differential expression data from Expression Atlas
- **animal_model** -- phenotype evidence from mouse model knockouts (MGI, IMPC)

## Common Queries

```bash
# Resolve gene symbol to Ensembl ID
curl -s -X POST https://api.platform.opentargets.org/api/v4/graphql \
  -H "Content-Type: application/json" \
  -d '{"query": "query { search(queryString: \"TP53\", entityNames: [\"target\"], page: {size: 1, index: 0}) { hits { id name } } }"}' | python3 -m json.tool

# Resolve disease name to EFO ID
curl -s -X POST https://api.platform.opentargets.org/api/v4/graphql \
  -H "Content-Type: application/json" \
  -d '{"query": "query { search(queryString: \"breast cancer\", entityNames: [\"disease\"], page: {size: 1, index: 0}) { hits { id name } } }"}' | python3 -m json.tool

# Get drug details by ChEMBL ID
curl -s -X POST https://api.platform.opentargets.org/api/v4/graphql \
  -H "Content-Type: application/json" \
  -d '{"query": "query { drug(chemblId: \"CHEMBL941\") { id name drugType maximumClinicalTrialPhase mechanismsOfAction { rows { mechanismOfAction targets { id approvedSymbol } } } } }"}' | python3 -m json.tool
```

## Best Practices

1. Always resolve gene symbols to Ensembl IDs and disease names to EFO IDs before querying associations.
2. Use `page: {size: N, index: 0}` to control result counts; default pages can be large.
3. Filter by `datatypeScores` to focus on specific evidence types relevant to the research question.
4. Scores range from 0 to 1; values above 0.5 indicate strong association evidence.

From beita6969/ScienceClaw, MIT.

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