Thermopred

This repository contains the official data, algorithms, and ML models present in the paper "AI-Enhanced Quantum Chemistry Dataset for Thermochemical Properties of API-Like Compounds and Their Degradants".

We recommend using Python 3.10, as this version has been thoroughly tested with Thermopred.

How to use

Download the repository manually or via git:

$ git clone https://github.com/jeffrichardchemistry/thermopred

Enter the thermopred directory and run the following command to install the python package:

$ cd thermopred

$ python3 setup.py install

Once this is done, it is now possible to use the package by simply importing the modules. Import the modules as described below and pass a smiles for prediction.

from Thermopred.Enthalpie import EnthalpieEnergy
from Thermopred.GibbsEnergy import GibbsFreeEnergy

smiles='CN1C=CN(CCCN(c2cc(Cl)ccc2O)c2ccccc2S)CC1'

ee = EnthalpieEnergy()
result_enthalpie = ee.predict(smiles)

gfe = GibbsFreeEnergy()
gfe.predict(smiles=smiles)

You can also install this package directly from PyPI using:

pip install thermopred

How to cite

• LaTeX

@article{doi:10.1021/acs.jcim.5c01320,
author = {Santos, Diullio P. and Dias-Silva, Jefferson R. and Júnior, Luiz H. K. Q. and de Oliveira, Heibbe C. B.},
title = {ThermoPred: AI-Enhanced Quantum Chemistry Data Set and ML Toolkit for Thermochemical Properties of API-Like Compounds and Their Degradants},
journal = {Journal of Chemical Information and Modeling},
volume = {0},
number = {0},
pages = {null},
year = {0},
doi = {10.1021/acs.jcim.5c01320},
note ={PMID: 41334815}
}

• Text

Santos, D. P.; Dias-Silva, J. R.; Júnior, L. H. K. Q.; de Oliveira, H. C. B. ThermoPred: AI-Enhanced Quantum Chemistry Data Set and ML Toolkit for Thermochemical Properties of API-Like Compounds and Their Degradants. J. Chem. Inf. Model. 2025