Skip to main content

A Python package to extract chemical, biochemical, and bioactivity data from public databases like ORD, ChEMBL and PubChem.

Project description

biochemical-data-connectors

biochemical-data-connectors is a Python package for extracting chemical, biochemical, and bioactivity data from public databases like ORD, ChEMBL and PubChem.

Overview

biochemical-data-connectors provides a simple and consistent interface to query major cheminformatics bioinformatics databases for compounds. It is designed to be a modular and reusable tool for researchers and developers in cheminformatics and drug discovery.

Key Features

  1. Bioactive Compounds
    • Unified Interface: A single, easy-to-use abstract base class for fetching bioactives for a given target.
    • Multiple Data Sources: Includes concrete connectors for major public databases:
      1. ChEMBL (ChEMBLBioactivesExtractor)
      2. PubChem (PubChemBioactivesExtractor)
    • Powerful Filtering: Filter compounds by bioactivity type (e.g., Kd, IC50) and potency value.
    • Efficient Fetching: Uses concurrency to fetch data from APIs efficiently.
  2. Chemical Reactions
    • Local ORD Processing: Includes a connector (OpenReactionDatabaseConnector) to efficiently process a local copy of the Open Reaction Database.
    • Reaction Role Correction: Uses RDKit to automatically correct and reassign reactant/product roles from the source data, improving data quality.
    • Robust SMILES Extraction: Canonicalizes and validates SMILES strings for both reactants and products to ensure high-quality, standardized output.
    • Memory-Efficient Processing: Employs a generator-based extraction method, allowing for iteration over massive reaction datasets with a low memory footprint.

Installation

You can install this package locally via:

pip install biochemical-data-connectors

Quick Start

Here is a simple example of how to retrieve all compounds from ChEMBL with a measured Kd of less than or equal to 1000 nM for the EGFR protein (UniProt ID: P00533).

import logging
from biochemical_data_connectors import ChEMBLConnector

logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)

# 1. Instantiate the connector for the desired database
chembl_connector = ChEMBLConnector(
    bioactivity_measure='Kd',
    bioactivity_threshold=1000.0, # in nM
    logger=logger
)

# 2. Specify the target's UniProt ID
target_uniprot_id = "P00533" # EGFR

# 3. Get the bioactive compounds
print(f"Fetching bioactive compounds for {target_uniprot_id} from ChEMBL...")
smiles_list = chembl_connector.get_bioactive_compounds(target_uniprot_id)

# 4. Print the results
if smiles_list:
    print(f"\nFound {len(smiles_list)} compounds.")
    print("First 5 compounds:")
    for smiles in smiles_list[:5]:
        print(smiles)
else:
    print("No compounds found matching the criteria.")

Package Structure

biochemical-data-connectors/
├── pyproject.toml
├── requirements-dev.txt
├── src/
│   └── biochemical_data_connectors/
│       ├── __init__.py
│       ├── constants.py
│       ├── connectors/
│       │   ├── __init__.py
│       │   ├── bioactive_compounds_connectors.py
│       │   └── ord_connectors.py
│       └── utils/
│           ├── __init__.py
│           └── api/
│               ├── __init__.py
│               ├── mappings.py
│               └── pubchem_api.py
├── tests/
│   └── ...
└── README.md

License

This project is licensed under the terms of the MIT License.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

biochemical_data_connectors-1.1.0.tar.gz (18.4 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

biochemical_data_connectors-1.1.0-py3-none-any.whl (20.6 kB view details)

Uploaded Python 3

File details

Details for the file biochemical_data_connectors-1.1.0.tar.gz.

File metadata

File hashes

Hashes for biochemical_data_connectors-1.1.0.tar.gz
Algorithm Hash digest
SHA256 df87a16a09d624ee453c7eb7bce1ebc41dffc76fda4b93f1a854cf1f9f067c91
MD5 75bb796a93c3b5583d05c8aea3d7aa60
BLAKE2b-256 8a159740cd51a138e111fe6c84d1ab21b11d7f2363fc2d8923095358f6ba2453

See more details on using hashes here.

Provenance

The following attestation bundles were made for biochemical_data_connectors-1.1.0.tar.gz:

Publisher: publish-to-pypi.yml on c-vandenberg/biochemical-data-connectors

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file biochemical_data_connectors-1.1.0-py3-none-any.whl.

File metadata

File hashes

Hashes for biochemical_data_connectors-1.1.0-py3-none-any.whl
Algorithm Hash digest
SHA256 fe2bc4c673c38e4b924aa82d136431e8a7a66074301bdbbd8399ba99626c4bd8
MD5 a1fc590ea3456bc0f3ce887c71e16726
BLAKE2b-256 17380d76f4d633ca5bbd160badbd2121c501885d1877e8a011ec664cd3104546

See more details on using hashes here.

Provenance

The following attestation bundles were made for biochemical_data_connectors-1.1.0-py3-none-any.whl:

Publisher: publish-to-pypi.yml on c-vandenberg/biochemical-data-connectors

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page