/Smiles-TO-iUpac-Translator

Transformer based SMILES to IUPAC Translator

Primary LanguagePythonMIT LicenseMIT


STOUT Logo
STOUT V2.0

Smiles TO iUpac Translator: Advanced Chemical Nomenclature Translation

License Maintenance Workflow
GitHub issues GitHub contributors tensorflow
GitHub release PyPI version Python versions DOI

Key FeaturesInstallationHow To UseTraining STOUTAcknowledgementsCitation

STOUT Demo

Key Features

  • 🧪 Translate SMILES to IUPAC names
  • 🔬 Convert IUPAC names back to valid SMILES strings
  • 🤖 Powered by advanced transformer models
  • 💻 Cross-platform support (Linux, macOS, Windows via Ubuntu shell)
  • 🚀 High-performance chemical nomenclature translation
  • 🧠 Training code available for custom model development

Installation

Choose your preferred installation method:

📦 PyPI Installation
pip install STOUT-pypi
🐍 Conda Environment Setup
conda create --name STOUT python=3.10 
conda activate STOUT
conda install -c decimer stout-pypi
📥 Direct Repository Installation
pip install git+https://github.com/Kohulan/Smiles-TO-iUpac-Translator.git

How To Use

from STOUT import translate_forward, translate_reverse

# SMILES to IUPAC name translation
SMILES = "CN1C=NC2=C1C(=O)N(C(=O)N2C)C"
IUPAC_name = translate_forward(SMILES)
print(f"🧪 IUPAC name of {SMILES} is: {IUPAC_name}")

# IUPAC name to SMILES translation
IUPAC_name = "1,3,7-trimethylpurine-2,6-dione"
SMILES = translate_reverse(IUPAC_name)
print(f"🔬 SMILES of {IUPAC_name} is: {SMILES}")

Training STOUT

For researchers interested in training their own STOUT models or understanding the training process, we provide the training code in a separate repository:

STOUT Training Repository

This repository contains the necessary scripts and instructions for training STOUT models. Please note that training requires significant computational resources and a large dataset. Refer to the README in the training repository for detailed instructions.

Model Card

Rajan, K., Steinbeck, C., & Zielesny, A. (2024). STOUT V2 - Model library (Version v3). Zenodo. https://doi.org/10.5281/zenodo.13318286

Model Use

  • Primary intended uses: Translation between SMILES and IUPAC names for chemical compounds
  • Primary intended users: Chemists, researchers, and developers in the field of cheminformatics
  • Out-of-scope use cases: Not intended for critical applications where 100% accuracy is required

Acknowledgements

Research supported with Cloud TPUs from Google's TPU Research Cloud (TRC)

Part of the DECIMER Project

DECIMER Logo

About Us

Cheminformatics and Computational Metabolomics Group

Citation

  1. Rajan, K., Zielesny, A. & Steinbeck, C. STOUT: SMILES to IUPAC names using neural machine translation. J Cheminform 13, 34 (2021). https://doi.org/10.1186/s13321-021-00512-4

  2. Rajan K, Zielesny A, Steinbeck C. STOUT V2.0: SMILES to IUPAC name conversion using transformer models. ChemRxiv. 2024; https://doi.org/10.26434/chemrxiv-2024-089vs

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