STOUT V2.0

Smiles TO iUpac Translator: Advanced Chemical Nomenclature Translation

Key Features • Installation • How To Use • Training STOUT • Acknowledgements • Citation

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

About Us

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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