/opentargets-database

name: "opentargets-database"
description: "Query Open Targets GraphQL API for target-disease associations, evidence, drug links, safety. Search targets by gene, diseases by EFO ID; scores from 20+ sources, drug mechanisms, tractability. For ChEMBL use chembl-database-bioactivity; for trials use clinicaltrials-database-search."
license: "Apache-2.0"

Open Targets Platform Database

Overview

Open Targets Platform integrates evidence from genetics, genomics, literature, and drug databases to systematically score target-disease associations for 60,000+ targets and 20,000+ diseases/phenotypes. The public GraphQL API (no authentication required) provides access to association scores, evidence from 20+ data sources (GWAS, ClinVar, ChEMBL, drugs, pathways, mouse models, expression), and detailed drug-target-disease triangles.

When to Use

• Ranking therapeutic targets for a disease by overall association score and evidence breakdown
• Finding all diseases associated with a gene of interest and their confidence scores
• Retrieving approved and investigational drugs for a target, with mechanism of action and clinical phase
• Assessing target druggability and tractability (small molecule, antibody, PROTAC likelihood)
• Pulling genetic association evidence (GWAS hits, variant-to-gene mappings) for a target-disease pair
• Exploring safety/adverse event data for a drug target from FAERS and literature
• For bioactivity IC50/Ki data use `chembl-database-bioactivity`; for clinical trial details use `clinicaltrials-database-search`

Prerequisites

• **Python packages**: `requests`
• **Data requirements**: gene symbols (HGNC), Ensembl gene IDs, disease EFO IDs, or drug names
• **Environment**: internet connection; no authentication needed
• **Rate limits**: no hard limit stated; use reasonable delays for large queries (>100 targets)

pip install requests

Quick Start

import requests

OT_URL = "https://api.platform.opentargets.org/api/v4/graphql"

def ot_query(gql, variables=None):
    r = requests.post(OT_URL, json={"query": gql, "variables": variables or {}})
    r.raise_for_status()
    return r.json()["data"]

# Top disease associations for BRCA1
query = """
query TargetDiseases($ensgId: String!) {
  target(ensemblId: $ensgId) {
    id
    approvedSymbol
    associatedDiseases(page: {index: 0, size: 5}) {
      rows {
        disease { id name }
        score
      }
    }
  }
}
"""
data = ot_query(query, {"ensgId": "ENSG00000012048"})
target = data["target"]
print(f"Target: {target['approvedSymbol']}")
for row in target["associatedDiseases"]["rows"]:
    print(f"  {row['disease']['name']}: {row['score']:.3f}")

Core API

Query 1: Target Lookup by Gene Symbol

Search for a target and retrieve basic metadata (Ensembl ID, biotype, description).

import requests

OT_URL = "https://api.platform.opentargets.org/api/v4/graphql"

def ot_query(gql, variables=None):
    r = requests.post(OT_URL, json={"query": gql, "variables": variables or {}})
    r.raise_for_status()
    return r.json()["data"]

# Search by gene symbol
query = """
query SearchTarget($sym: String!) {
  search(queryString: $sym, entityNames: ["target"]) {
    hits {
      id
      name
      entity
      object {
        ... on Target {
          approvedSymbol
          approvedName
          biotype
          functionDescriptions
        }
      }
    }
  }
}
"""
data = ot_query(query, {"sym": "BRCA1"})
for hit in data["search"]["hits"][:3]:
    obj = hit.get("object", {})
    print(f"ID: {hit['id']} | {obj.get('approvedSymbol')} | {obj.get('biotype')}")
    descs = obj.get("functionDescriptions", [])
    if descs:
        print(f"  Function: {descs[0][:120]}")

# Direct lookup by Ensembl ID
query2 = """
query Target($ensgId: String!) {
  target(ensemblId: $ensgId) {
    id approvedSymbol approvedName biotype
    tractability { label modality value }
  }
}
"""
data2 = ot_query(query2, {"ensgId": "ENSG00000141510"})  # TP53
t = data2["target"]
print(f"\n{t['approvedSymbol']} ({t['id']}): {t['biotype']}")
print("Tractability:")
for tr in t.get("tractability", [])[:5]:
    print(f"  {tr['modality']} | {tr['label']}: {tr['value']}")

Query 2: Target-Disease Associations

Retrieve association scores for a target across all associated diseases.

import requests, pandas as pd

OT_URL = "https://api.platform.opentargets.org/api/v4/graphql"

def ot_query(gql, variables=None):
    r = requests.post(OT_URL, json={"query": gql, "variables": variables or {}})
    r.raise_for_status()
    return r.json()["data"]

query = """
query Associations($ensgId: String!, $size: Int!) {
  target(ensemblId: $ensgId) {
    approvedSymbol
    associatedDiseases(page: {index: 0, size: $size}, orderByScore: "score") {
      count
      rows {
        disease { id name therapeuticAreas { name } }
        score
        datatypeScores { id score }
      }
    }
  }
}
"""
data = ot_query(query, {"ensgId": "ENSG00000012048", "size": 20})
target = data["target"]
assoc = target["associatedDiseases"]
print(f"{target['approvedSymbol']}: {assoc['count']} associated diseases")

rows = []
for r in assoc["rows"]:
    scores = {d["id"]: d["score"] for d in r.get("datatypeScores", [])}
    rows.append({
        "disease": r["disease"]["name"],
        "disease_id": r["disease"]["id"],
        "overall_score": round(r["score"], 4),
        "genetics": round(scores.get("genetic_association", 0), 3),
        "drugs": round(scores.get("known_drug", 0), 3),
        "literature": round(scores.get("literature", 0), 3),
    })

df = pd.DataFrame(rows)
print(df.head(10).to_string(index=False))

Query 3: Disease-Target Associations

Given a disease, retrieve all associated targets ranked by score.

import requests, pandas as pd

OT_URL = "https://api.platform.opentargets.org/api/v4/graphql"

def ot_query(gql, variables=None):
    r = requests.post(OT_URL, json={"query": gql, "var