ersiliaos/eos5smc repository overview

⁠Predicts activity of compounds accross the Tox21 panel

Reports activity across the twelve toxicity pathways assembled by the Tox21 initiative, covering nuclear receptor signalling and cellular stress response, as measured for 7,831 compounds in the MoleculeNet release of the 2014 Tox21 Data Challenge. Predictions come from a graph transformer pretrained on 10 million unlabelled ChEMBL and ZINC15 molecules, fine-tuned on the twelve endpoints together and averaged over three folds. The assays are heavily imbalanced towards inactives, and a hit reflects in vitro signalling rather than whole-organism toxicity.

This model was incorporated on 2022-07-12. Last packaged on 2026-11-03.

⁠Information

⁠Identifiers

• Ersilia Identifier: eos5smc
• Slug: grover-tox21

⁠Domain

• Task: Annotation
• Subtask: Activity prediction
• Biomedical Area: ADMET
• Target Organism: Homo sapiens
• Tags: Tox21, Toxicity, Chemical graph model

⁠Input

• Input: Compound
• Input Dimension: 1

⁠Output

• Output Dimension: 12
• Output Consistency: Fixed
• Interpretation: Probability of activity in each of the twelve Tox21 toxicity pathways.

Below are the Output Columns of the model:

10 of 12 columns are shown

⁠Source and Deployment

• Source: Local
• Source Type: External
• DockerHub: https://chstno1.isgood.host/r/ersiliaos/eos5smc⁠
• Docker Architecture: AMD64, ARM64
• S3 Storage: https://ersilia-models-zipped.s3.eu-central-1.amazonaws.com/eos5smc.zip⁠

⁠Resource Consumption

• Model Size (Mb): 1310
• Environment Size (Mb): 2404
• Image Size (Mb): 3685.96

Computational Performance (seconds):

• 10 inputs: 31.15
• 100 inputs: 156.58
• 10000 inputs: -1

⁠References

• Source Code: https://github.com/tencent-ailab/grover⁠
• Publication: https://doi.org/10.48550/arXiv.2007.02835⁠
• Publication Type: Preprint
• Publication Year: 2020
• Ersilia Contributor: Amna-28⁠

⁠License

This package is licensed under a GPL-3.0⁠ license. The model contained within this package is licensed under a MIT⁠ license.

Notice: Ersilia grants access to models as is, directly from the original authors, please refer to the original code repository and/or publication if you use the model in your research.

⁠Use

To use this model locally, you need to have the Ersilia CLI⁠ installed. The model can be fetched using the following command:

# fetch model from the Ersilia Model Hub
ersilia fetch eos5smc

Then, you can serve, run and close the model as follows:

# serve the model
ersilia serve eos5smc
# generate an example file
ersilia example -n 3 -f my_input.csv
# run the model
ersilia run -i my_input.csv -o my_output.csv
# close the model
ersilia close

⁠About Ersilia

The Ersilia Open Source Initiative⁠ is a tech non-profit organization fueling sustainable research in the Global South. Please cite⁠ the Ersilia Model Hub if you've found this model to be useful. Always let us know⁠ if you experience any issues while trying to run it. If you want to contribute to our mission, consider donating⁠ to Ersilia!