TTD — Therapeutic Target Database

Source: https://ttd.idrblab.cn/ Paper: https://academic.oup.com/nar/article/52/D1/D1465/7275004 Data dir: resources_metadata/dti/TTD

Data files (4 required)

File	Content
P1-01-TTD_target_download.txt	Target info: name, UniProt, gene, type, function, disease indication, pathway
P2-01-TTD_target_drug.txt	Target ↔ Drug links with clinical status (Approved / Phase I–III / Experimental)
P1-06-Target_disease.txt	Target ↔ Disease associations
P1-07-Drug_disease.txt	Drug ↔ Disease associations

File formats:

• P1-01, P2-01 — block format: blank-line separated records, each line <ID>\t<KEY>\t<VALUE>
• P1-06, P1-07 — TSV with header row

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Query API

query(entities, entity_type="auto", data_dir=DATA_DIR)

Returns a list of dicts, one per queried entity.

Parameter	Type	Description
entities	str or list[str]	One or more entity names / IDs
entity_type	"auto" / "target" / "drug" / "disease"	Restrict search; "auto" tries target → drug → disease
data_dir	str	Path to TTD data directory

query_json(entities, ...) → str

Same as query() but returns a JSON string. Use for LLM consumption.

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Input formats accepted

Input	Examples
Gene / protein name	"EGFR", "TP53", "BCR-ABL"
Drug name	"Imatinib", "Gefitinib", "Osimertinib"
Disease name	"Lung cancer", "Diabetes mellitus" (partial match supported)
TTD Target ID	"TTDTARGET00001"
TTD Drug ID	"D0Y4GH"

Matching is case-insensitive; disease names support partial matching.

---

Output structure

Target result

{
  "query": "EGFR",
  "entity_type": "target",
  "ttd_id": "TTDTARGET00001",
  "name": "Epidermal growth factor receptor",
  "uniprot": "P00533",
  "gene": "EGFR",
  "target_type": "Successful target",
  "function": "Receptor tyrosine kinase...",
  "disease": "Non-small-cell lung cancer [ICD-11: 2C25]",
  "pathway": "EGFR signaling pathway",
  "drugs": [
    {"drug_id": "D0Y4GH", "drug_name": "Gefitinib", "clinical_status": "Approved"},
    {"drug_id": "D08VGC", "drug_name": "Erlotinib", "clinical_status": "Approved"}
  ]
}

Drug result

{
  "query": "Imatinib",
  "entity_type": "drug",
  "drug_id": "D0IQX1",
  "drug_name": "Imatinib",
  "targets": [
    {"ttd_target_id": "TTDTARGET00002", "target_name": "BCR-ABL",
     "clinical_status": "Approved", "drug_id": "D0IQX1"}
  ],
  "diseases": ["Chronic myelogenous leukemia", "Gastrointestinal stromal tumor"]
}

Disease result

{
  "query": "Lung cancer",
  "entity_type": "disease",
  "disease_name": "non-small-cell lung cancer",
  "targets": [
    {"ttd_target_id": "TTDTARGET00001", "target_name": "EGFR"}
  ],
  "drugs": ["Gefitinib", "Osimertinib", "Erlotinib"]
}

Not found

{"query": "XYZ123", "entity_type": "not_found", "message": "No match found in TTD."}

---

Usage examples

from 17_TTD import query, query_json

# Single entity
results = query("EGFR")

# Multiple entities (mixed types — auto-detected)
results = query(["EGFR", "Imatinib", "Lung cancer"])

# Restrict to drug search only
results = query(["Gefitinib", "Osimertinib"], entity_type="drug")

# JSON string output (for LLM)
print(query_json("TP53"))

CLI (demo runs with EGFR / Imatinib / Lung cancer if no args):

python 17_TTD.py EGFR Imatinib "Lung cancer"
python 17_TTD.py TTDTARGET00001

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Notes

• entity_type="auto" stops at the first match type per entity (target → drug → disease). Use explicit type to resolve ambiguity.
• drugs in target results lists all TTD-linked drugs; filter clinical_status == "Approved" for marketed drugs.
• Disease partial matching — "lung cancer" will match "non-small-cell lung cancer". The first candidate is returned; use entity_type="disease" with a more specific name if needed.
• Multi-value fields (e.g. multiple pathways for one target) are returned as lists.