ersiliaos/eos3mk2 repository overview

⁠BBBP model tested on marine-derived kinase inhibitors

A set of three binary classifiers (random forest, gradient boosting classifier, and logistic regression) to predict the Blood-Brain Barrier (BBB) permeability of small organic compounds. The best models were applied to natural products of marine origin, able to inhibit kinases associated with neurodegenerative disorders. The training set size was around 300 compounds.

This model was incorporated on 2024-10-23.Last packaged on 2026-04-13.

⁠Information

⁠Identifiers

• Ersilia Identifier: eos3mk2
• Slug: bbbp-marine-kinase-inhibitors

⁠Domain

• Task: Annotation
• Subtask: Activity prediction
• Biomedical Area: ADMET
• Target Organism: Homo sapiens
• Tags: Drug-likeness, Permeability

⁠Input

• Input: Compound
• Input Dimension: 1

⁠Output

• Output Dimension: 3
• Output Consistency: Fixed
• Interpretation: Classification score over three classifiers, namely random forest (rfc), gradient boosting classifier (gbc), and logistic regression (logreg).

Below are the Output Columns of the model:

⁠Source and Deployment

• Source: Local
• Source Type: Replicated
• DockerHub: https://hub.docker.com/r/ersiliaos/eos3mk2⁠
• Docker Architecture: AMD64, ARM64
• S3 Storage: https://ersilia-models-zipped.s3.eu-central-1.amazonaws.com/eos3mk2.zip⁠

⁠Resource Consumption

• Model Size (Mb): 9
• Environment Size (Mb): 711
• Image Size (Mb): 741.72

Computational Performance (seconds):

• 10 inputs: 32.45
• 100 inputs: 249.57
• 10000 inputs: -1

⁠References

• Source Code: https://github.com/plissonf/BBB-Models⁠
• Publication: https://pubmed.ncbi.nlm.nih.gov/30699889/⁠
• Publication Type: Peer reviewed
• Publication Year: 2019
• Ersilia Contributor: miquelduranfrigola⁠

⁠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 eos3mk2

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

# serve the model
ersilia serve eos3mk2
# 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!