Skip to main content

chembl-database

Query the ChEMBL database for bioactive molecules, drug targets, bioactivity data, approved drugs, and chemical structures. Use when the user asks about compounds, targets, IC50/Ki values, drug mechanisms, or structure searches.

Source facts

Repository
google-deepmind/science-skills
Last source activity
July 1, 2026 at 20:05
Detected SKILL.md language
English
Stars
3,407
Forks
397

Install options

The review-first prompt is selected by default. You can switch to a direct command or download a local copy.

Review the source files

Read SKILL.md and any companion files shown by SkillsMP before deciding whether to install.

File Explorer
4 files

Showing SKILL.md

SKILL.md
Source instructions · Read-only preview
name
chembl-database
description
Query the ChEMBL database for bioactive molecules, drug targets, bioactivity data, approved drugs, and chemical structures. Use when the user asks about compounds, targets, IC50/Ki values, drug mechanisms, or structure searches.
# ChEMBL Database Query ## Prerequisites 1. **`uv`**: Read the `uv` skill and follow its Setup instructions to ensure `uv` is installed and on PATH. 2. **User Notification**: If .licenses/chembl_database_LICENSE.txt does not already exist in the workspace root directory then (1) prominently notify the user to check the terms at https://chembl.gitbook.io/chembl-interface-documentation/about, then (2) create the file recording the notification text and timestamp. ## Core Rules - [!IMPORTANT] **Use the Utility Scripts**: You MUST ALWAYS use the provided utility script `scripts/chembl_api.py` for all ChEMBL API interactions, including checking status. NEVER use `curl` or custom Python requests to query the ChEMBL API directly. This ensures rate limit is enfoced and also retries on network errors. - **Output to File (Required)**: The `--output` flag is **required** for every subcommand. All JSON results are written to the specified file. After running the command, read the output file with jq or your own code to extract the data. List results are typically wrapped in a JSON array keyed by the endpoint name (e.g., `molecules`, `activities`). - **Notification**: If this skill is used, ensure this is mentioned in the output. ## Utility Script All ChEMBL API queries use one script with subcommands: ```bash uv run scripts/chembl_api.py <subcommand> --output <file> [options] ``` -------------------------------------------------------------------------------- ### 1. Check API Status ```bash uv run scripts/chembl_api.py status --output /tmp/status.json ``` -------------------------------------------------------------------------------- ### 2. Molecule Queries **Fetch by ChEMBL ID:** `bash uv run scripts/chembl_api.py molecule --id CHEMBL25 --output /tmp/mol.json` **Search by name:** `bash uv run scripts/chembl_api.py molecule --search "aspirin" --limit 3 --output /tmp/mol_search.json` **Batch fetch:** `bash uv run scripts/chembl_api.py molecule --ids "CHEMBL25;CHEMBL1642" --limit 10 --output /tmp/mol_batch.json` **Filter by properties:** `bash uv run scripts/chembl_api.py molecule --filter molecule_properties__mw_freebase__lte=500 --limit 5 --output /tmp/mol_filter.json` **Filter by range:** `bash uv run scripts/chembl_api.py molecule --filter molecule_properties__mw_freebase__range=150,200 --limit 5 --output /tmp/mol_range.json` **Download SDF structure file:** `bash uv run scripts/chembl_api.py molecule --id CHEMBL25 --dl_format sdf --output /tmp/aspirin.sdf` > **Tip**: SDF/MOL files can be passed directly to tools like PyMOL or RDKit for > 3D visualization and analysis. -------------------------------------------------------------------------------- ### 3. Target Queries **Search for targets:** `bash uv run scripts/chembl_api.py target --search "EGFR" --limit 5 --output /tmp/targets.json` **Fetch by ID:** `bash uv run scripts/chembl_api.py target --id CHEMBL203 --output /tmp/egfr.json` -------------------------------------------------------------------------------- ### 4. Bioactivity Data **Fetch activity by ID:** `bash uv run scripts/chembl_api.py activity --id 31863 --output /tmp/act.json` **Search activities:** `bash uv run scripts/chembl_api.py activity --search "EGFR" --limit 5 --output /tmp/act_search.json` **Filter activities for a target:** `bash uv run scripts/chembl_api.py activity --filter target_chembl_id=CHEMBL203 standard_type=IC50 --limit 10 --output /tmp/egfr_ic50.json` **Normalize bioactivity units to nM:** `bash uv run scripts/chembl_api.py activity --filter target_chembl_id=CHEMBL203 standard_type=IC50 --limit 5 --normalize --output /tmp/egfr_normalized.json` > **Important**: Bioactivity values come in various units (nM, µM, pM). Use > `--normalize` to convert all values to nM for consistent comparison. Each > record will include `normalized_value_nM` and `normalization_note`. -------------------------------------------------------------------------------- ### 5. Drug Information **Fetch drug details:** `bash uv run scripts/chembl_api.py drug --id CHEMBL25 --output /tmp/drug.json` **Drug indications:** `bash uv run scripts/chembl_api.py drug_indication --filter molecule_chembl_id=CHEMBL25 --limit 10 --output /tmp/indications.json` **Filter indications by phase:** `bash uv run scripts/chembl_api.py drug_indication --filter molecule_chembl_id=CHEMBL25 max_phase_for_ind=4.0 --limit 10 --output /tmp/approved_indications.json` **Drug warnings:** `bash uv run scripts/chembl_api.py drug_warning --limit 5 --output /tmp/warnings.json` **Mechanisms of action:** `bash uv run scripts/chembl_api.py mechanism --filter molecule_chembl_id=CHEMBL25 --limit 5 --output /tmp/mech.json` -------------------------------------------------------------------------------- ### 6. Structure-Based Searches > **Note**: Both similarity and substructure searches are performed > **server-side** on ChEMBL's pre-indexed database. They do not require a local > RDKit installation. **Similarity search (SMILES + threshold):** `bash uv run scripts/chembl_api.py similarity --smiles "CC(=O)Oc1ccccc1C(=O)O" --similarity 85 --limit 5 --output /tmp/similar.json` **Substructure search (SMILES):** `bash uv run scripts/chembl_api.py substructure --smiles "c1ccccc1" --limit 5 --output /tmp/substruct.json` -------------------------------------------------------------------------------- ### 7. Compound Image Download a 2D structure image (SVG by default, scalable for publication): ```bash uv run scripts/chembl_api.py image --id CHEMBL25 --output /tmp/chembl25.svg ``` *Options:* - `--dimensions`: Image size in pixels (max 500, default 500). - `--engine`: Rendering engine (default: rdkit). - `--img_format`: Output format — `svg` (default, vector) or `png` (raster). -------------------------------------------------------------------------------- ### 8. Cross-Referencing with Other Databases ChEMBL integrates with UniProt, Ensembl, PubChem, and other databases. Common cross-referencing patterns: **Find a ChEMBL target from a UniProt accession:** `bash uv run scripts/chembl_api.py target --filter target_components__accession=P00533 --limit 5 --output /tmp/uniprot_target.json` **Resolve any ChEMBL ID to its entity type:** `bash uv run scripts/chembl_api.py chembl_id_lookup --id CHEMBL203 --output /tmp/lookup.json` **Look up cross-reference sources:** `bash uv run scripts/chembl_api.py xref_source --limit 10 --output /tmp/xrefs.json` > **Tip**: Use the `target_component` endpoint to find UniProt accessions, gene > names, and protein sequences for any ChEMBL target. -------------------------------------------------------------------------------- ### 9. Pagination All list endpoints support `--limit` and `--offset` for pagination: ```bash # First page: 2 results starting at offset 0 uv run scripts/chembl_api.py molecule --limit 2 --offset 0 --output /tmp/page1.json # Second page: next 2 results starting at offset 2 uv run scripts/chembl_api.py molecule --limit 2 --offset 2 --output /tmp/page2.json ``` The response includes `page_meta` with `total_count`, `limit`, `offset`, `next`, and `previous` links. Use successive `--offset` values to page through large result sets. -------------------------------------------------------------------------------- ### 10. Other Endpoints All remaining endpoints follow the same pattern: ```bash uv run scripts/chembl_api.py <subcommand> --output <file> [--id ID | --ids ID1;ID2 | --search QUERY] [--limit N] [--offset N] [--filter KEY=VAL ...] ``` **Key subcommands at a glance:** - `molecule` (searchable: true): Molecules/compounds — the primary entry point - `target` (searchable: true): Drug targets (proteins, organisms, etc.) - `activity` (searchable: true): Bioactivity data (IC50, Ki, EC50, etc.) - `drug` (searchable: false): Approved drugs - `mechanism` (searchable: false): Mechanisms of action - `assay` (searchable: true): Assay descriptions - `similarity` (searchable: false): Similarity search (special)
View on GitHub
This SKILL.md is very large, so SkillsMP previews the first section here. View on GitHub