Download, open, and query ChEMBL through SQLite
Don't worry about downloading/extracting ChEMBL or versioning - just use
chembl_downloader to write code that knows
how to download it and use it automatically.
$ pip install chembl-downloader
Download A Specific Version
import chembl_downloader path = chembl_downloader.download_extract_sqlite(version='28')
After it's been downloaded and extracted once, it's smart and does not need to download again. It gets stored
pystow automatically in the
We'd like to implement something such that it could load directly into SQLite from the archive, but it appears this is a paid feature.
Download the Latest Version
First, you'll have to install
pip install bioversions, whose job it is to look up the latest version of many databases. Then, you can modify
the previous code slightly by omitting the
version keyword argument:
import chembl_downloader path = chembl_downloader.download_extract_sqlite()
version keyword argument is available for all functions in this package (e.g., including
query()), but will be omitted below for brevity.
Inside the archive is a single SQLite database file. Normally, people manually untar this folder then do something with the resulting file. Don't do this, it's not reproducible! Instead, the file can be downloaded and a connection can be opened automatically with:
import chembl_downloader with chembl_downloader.connect() as conn: with conn.cursor() as cursor: cursor.execute(...) # run your query string rows = cursor.fetchall() # get your results
cursor() function provides a convenient wrapper around this operation:
import chembl_downloader with chembl_downloader.cursor() as cursor: cursor.execute(...) # run your query string rows = cursor.fetchall() # get your results
Run a query and get a pandas DataFrame
The most powerful function is
query() which builds on the previous
connect() function in combination
to make a query and load the results into a pandas DataFrame for any downstream use.
import chembl_downloader sql = """ SELECT MOLECULE_DICTIONARY.chembl_id, MOLECULE_DICTIONARY.pref_name FROM MOLECULE_DICTIONARY JOIN COMPOUND_STRUCTURES ON MOLECULE_DICTIONARY.molregno == COMPOUND_STRUCTURES.molregno WHERE molecule_dictionary.pref_name IS NOT NULL LIMIT 5 """ df = chembl_downloader.query(sql) df.to_csv(..., sep='\t', index=False)
Suggestion 1: use
pystow to make a reproducible file path that's portable to other people's machines
(e.g., it doesn't have your username in the path).
Suggestion 2: RDKit is now pip-installable with
pip install rdkit-pypi, which means most users don't have to muck
around with complicated conda environments and configurations. One of the powerful but understated tools in RDKit is
Access an RDKit supplier over entries in the SDF dump
This example is a bit more fit-for-purpose than the last two. The
supplier() function makes sure that the latest SDF
dump is downloaded and loads it from the gzip file into a
using a context manager to make sure the file doesn't get closed until after parsing is done. Like the previous
examples, it can also explicitly take a
from rdkit import Chem import chembl_downloader with chembl_downloader.supplier() as suppl: data =  for i, mol in enumerate(suppl): if mol is None or mol.GetNumAtoms() > 50: continue fp = Chem.PatternFingerprint(mol, fpSize=1024, tautomerFingerprints=True) smi = Chem.MolToSmiles(mol) data.append((smi, fp))
This example was adapted from Greg Landrum's RDKit blog post on generalized substructure search.
Store in a Different Place
If you want to store the data elsewhere using
pystow (e.g., in
I also keep a copy of this file), you can use the
import chembl_downloader # It gets downloaded/extracted to # ~/.data/pyobo/raw/chembl/29/chembl_29/chembl_29_sqlite/chembl_29.db path = chembl_downloader.download_extract_sqlite(prefix=['pyobo', 'raw', 'chembl'])
pystow documentation on configuring the storage
prefix keyword argument is available for all functions in this package (e.g., including
Download via CLI
After installing, run the following CLI command to ensure it and send the path to stdout
--test to show two example queries
$ chembl_downloader --test
If you'd like to contribute, there's a submodule called
where you can add an SQL query along with a description of what it does for easy importing.
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