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Toolkit for harmonizing SMILES strings to canonical + isomeric + Kekulized convention (RDKit)

Project description

HARMONSMILE: Harmonize SMILES Strings for Cheminformatics and Machine Learning

License: LGPL v3 Version PyPI Python Docs


Description

HARMONSMILE solves a common problem in cheminformatics: SMILES strings for the same molecule look different depending on the source (PubChem, ChEMBL, COCONUT, in-house databases). This inconsistency breaks comparisons, deduplication, and machine learning pipelines that expect a uniform molecular representation.


Purpose

The primary objective of HARMONSMILE is to automate the preparation of molecular datasets for cheminformatics workflows and phase 1 machine learning applications within the computational drug discovery pipeline.

The platform enables:

  • Data Harmonization: Standardizes SMILES strings to a consistent format - canonical + isomeric + Kekulized - ensuring that the same molecule is represented identically across different datasets and sources. It follows the RDKit convention for canonicalization, which is widely adopted in the cheminformatics community.

Installation

pip install harmonsmile

RDKit is required and installed automatically (rdkit>=2022.09).


Quick Start

Python API

Standardize a single SMILES string:

from harmonsmile import RDKitStandardizer

std = RDKitStandardizer()
print(std.to_iso_kek("c1ccccc1"))    # canonical + isomeric + Kekulized
print(std.to_conn_kek("c1ccccc1"))   # canonical + connectivity-only + Kekulized

Fetch properties from PubChem and harmonize:

from harmonsmile import PubChemIngest, PubChemConfig

cfg = PubChemConfig(
    input_path="examples/example_pubchem.csv",   # requires: id, PubChem CID
    output_path="results/example_pubchem_harmonized.csv",
)
PubChemIngest(cfg).run()

Fetch properties from ChEMBL and harmonize:

from harmonsmile import ChEMBLIngest, ChEMBLConfig

cfg = ChEMBLConfig(
    input_path="examples/example_chembl.csv",    # requires: id, ChEMBL ID
    output_path="results/example_chembl_harmonized.csv",
)
ChEMBLIngest(cfg).run()

Harmonize any file with a SMILES column (COCONUT, in-house, etc.):

from harmonsmile import SMILESPrep, SMILESConfig

cfg = SMILESConfig(
    input_path="examples/example_smiles.csv",
    smiles_col="SMILES",                      # any column name
    output_path="results/example_smiles_harmonized.csv",
)
SMILESPrep(cfg).run()

Command-Line Interface

# PubChem pipeline
harmonsmile --pubchem-in examples/database1.csv --pubchem-out results/database1_harmonized.csv

# SMILES pipeline (COCONUT, independent, etc.)
harmonsmile --smiles-in examples/database2.csv --smiles-col canonical_smiles \
            --smiles-out results/database2_harmonized.csv

# Both pipelines in one run
harmonsmile \
  --pubchem-in examples/database1.csv --pubchem-out results/database1_harmonized.csv \
  --smiles-in  examples/database2.csv --smiles-col  canonical_smiles \
  --smiles-out results/database2_harmonized.csv

# Single Entry - fetch one compound by ID
harmonsmile --pubchem-cid 2723949
harmonsmile --chembl-id CHEMBL294199

# Check version
harmonsmile --version

Also available as a Python module:

python -m harmonsmile --pubchem-in examples/database1.csv --pubchem-out results/out.csv

Pipelines

Pipeline Config Source Input API
PubChemIngest PubChemConfig PubChem CSV with PubChem CID column REST (public)
ChEMBLIngest ChEMBLConfig ChEMBL CSV with ChEMBL ID column REST (public)
SMILESPrep SMILESConfig Any CSV/Excel with any SMILES column Local file

All pipelines append a SMILES_RDKit column with the harmonized SMILES.


Input Format

Pipeline Required columns
PubChemIngest id (optional), PubChem CID
ChEMBLIngest id (optional), ChEMBL ID
SMILESPrep id (optional), <smiles_col> (any name)

Supported file formats: CSV, TSV, XLSX, XLS.


Roadmap

  • v0.3.0 - ML-ready features: ECFP fingerprints (with/without chirality), InChI/InChIKey for deduplication and robust cross-database matching.

Development

Project Structure

HARMONSMILE/
|-- harmonsmile/
|   |-- __init__.py        # Public API
|   |-- __main__.py        # python -m harmonsmile entry point
|   |-- _cli.py            # CLI implementation
|   |-- chembl.py          # ChEMBL REST client
|   |-- config.py          # PubChemConfig, ChEMBLConfig, SMILESConfig dataclasses
|   |-- io.py              # Table I/O utilities
|   |-- pipelines.py       # PubChemIngest, ChEMBLIngest, SMILESPrep
|   |-- pubchem.py         # PubChem REST client
|   |-- standardize.py     # RDKitStandardizer
|   `-- version.py         # Package version metadata
|-- tests/                 # Unit test suite (pytest) - 146 tests
|-- examples/              # Example scripts and datasets
|-- results/               # Output data (not installed)
|-- logs/                  # Error logs (not installed)
|-- pyproject.toml
|-- environment.yml
|-- mkdocs.yml
|-- requirements-dev.txt
|-- CHANGELOG.md
|-- CITATION.cff
|-- COPYING
|-- COPYING.LESSER
|-- LICENSE
`-- README.md

Running Tests

python -m pytest tests -p no:cacheprovider --basetemp .pytest_tmp

Contributing

Contributions are welcome. Please open an issue before submitting a pull request. Follow the existing code style: NumPy-style docstrings, type hints, and SPDX license headers in all source files.


Citation

If you use HARMONSMILE in your research, please cite it using the metadata in CITATION.cff or the format below:

Contreras-Torres, F. F. (2026). HARMONSMILE: Harmonize SMILES Strings for
Cheminformatics and Machine Learning (v0.2.3). Tecnologico de Monterrey.
https://github.com/NanoBiostructuresRG/harmonsmile

Author

Developed by Flavio F. Contreras-Torres (Tecnologico de Monterrey) Monterrey, Mexico - May 2026


License

This project is licensed under the terms of the GNU Lesser General Public License v3.0 or later. SPDX identifier: LGPL-3.0-or-later.

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