ersiliaos/eos96ia repository overview

⁠Coloring molecules for interaction with CYP3A4

Flags inhibition of cytochrome P450 3A4, an enzyme central to drug clearance and a frequent source of drug-drug interactions. The model shares its architecture with the other MolGrad endpoints, pairing a message-passing graph neural network with integrated-gradients colouring of atomic contributions, and learns from 9,120 compounds characterised in a bioluminescent high-throughput assay. One caveat carries over from that dataset: substrates were never labelled separately from inhibitors and could not be excluded from the positives.

This model was incorporated on 2021-10-19. Last packaged on 2026-11-03.

⁠Information

⁠Identifiers

• Ersilia Identifier: eos96ia
• Slug: molgrad-cyp3a4

⁠Domain

• Task: Annotation
• Subtask: Activity prediction
• Biomedical Area: ADMET
• Target Organism: Homo sapiens
• Tags: CYP450, ADME, Chemical graph model

⁠Input

• Input: Compound
• Input Dimension: 1

⁠Output

• Output Dimension: 1
• Output Consistency: Fixed
• Interpretation: Probability that the compound inhibits cytochrome P450 3A4, from a binary high-throughput assay.

Below are the Output Columns of the model:

⁠Source and Deployment

• Source: Local
• Source Type: External
• DockerHub: https://chstno1.isgood.host/r/ersiliaos/eos96ia⁠
• Docker Architecture: AMD64
• S3 Storage: https://ersilia-models-zipped.s3.eu-central-1.amazonaws.com/eos96ia.zip⁠

⁠Resource Consumption

• Model Size (Mb): 17
• Environment Size (Mb): 2414
• Image Size (Mb): 2330.44

Computational Performance (seconds):

• 10 inputs: 24.66
• 100 inputs: 16.42
• 10000 inputs: 183.22

⁠References

• Source Code: https://github.com/josejimenezluna/molgrad/⁠
• Publication: https://doi.org/10.1021/acs.jcim.0c01344⁠
• Publication Type: Peer reviewed
• Publication Year: 2021
• Ersilia Contributor: miquelduranfrigola⁠

⁠License

This package is licensed under a GPL-3.0⁠ license. The model contained within this package is licensed under a AGPL-3.0-only⁠ 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 eos96ia

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

# serve the model
ersilia serve eos96ia
# 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!