ersiliaos/eos8c0o repository overview

⁠ImageMol human beta-secretase-1 (BACE-1) inhibition

This model has been developed using ImageMol, a deep learning model pretrained on 10 million unlabelled small molecules and fine-tuned in a second step to predict the binding of inhibitors to the human beta secretase 1 (BACE-1) protein. The BACE-1 dataset from MoleculeNet contains 1522 compounds with their associated pIC50. A compound with pIC50 => 7 is considered a BACE-1 inhibitor.

This model was incorporated on 2023-01-11.Last packaged on 2026-09-25.

⁠Information

⁠Identifiers

• Ersilia Identifier: eos8c0o
• Slug: image-mol-bace

⁠Domain

• Task: Annotation
• Subtask: Activity prediction
• Biomedical Area: Alzheimer
• Target Organism: Homo sapiens
• Tags: BACE, Chemical graph model, MoleculeNet

⁠Input

• Input: Compound
• Input Dimension: 1

⁠Output

• Output Dimension: 1
• Output Consistency: Fixed
• Interpretation: Probability of BACE-1 inhibition (>0.5: Inhibitor). Compounds with pIC50 => 7 are considered BACE-1 inhibitors

Below are the Output Columns of the model:

⁠Source and Deployment

• Source: Local
• Source Type: External
• DockerHub: https://hub.docker.com/r/ersiliaos/eos8c0o⁠
• Docker Architecture: AMD64, ARM64
• S3 Storage: https://ersilia-models-zipped.s3.eu-central-1.amazonaws.com/eos8c0o.zip⁠

⁠Resource Consumption

• Model Size (Mb): 44
• Environment Size (Mb): 1215
• Image Size (Mb): 1337.83

Computational Performance (seconds):

• 10 inputs: 26.69
• 100 inputs: 17.04
• 10000 inputs: 171.51

⁠References

• Source Code: https://github.com/ChengF-Lab/ImageMol⁠
• Publication: https://doi.org/10.1038/s42256-022-00557-6⁠
• Publication Type: Peer reviewed
• Publication Year: 2022
• Ersilia Contributor: DhanshreeA⁠

⁠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 eos8c0o

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

# serve the model
ersilia serve eos8c0o
# 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!