This repo contains associated code for MolSkill: implcit molecular scoring via chemists in the loop.
We recommend that you make a fresh conda environment (currently only Python 3.9 is supported) and install the provided conda package for convenience:
conda install molskillAdditionally, you can also use the provided environment.yml file for manual installation.
A CUDA-enabled GPU is not required for usage, but strongly recommended for speed if you plan on scoring a large amount of compounds.
This work mainly exposes the MolSkillScorer class under the molskill.scorer module. We interface with RDKit to provide predictions accordingly. The user only has to provide a list of molecular strings that they wish to score.
from molskill.scorer import MolSkillScorer
smiles_strs = ["CCO", "O=C(Oc1ccccc1C(=O)O)C"]
scorer = MolSkillScorer()
scores = scorer.score(smiles_strs)We provide and use by default a pre-trained model on all the data that was collected during the original study. If a user wants to train custom models, please check the train.py script also included under this repository.
If you find this work or parts thereof useful, please consider citing the following BibTex entry:
@article{choung2023
...
}
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