ersiliaos/eos9ivc repository overview

⁠Antituberculosis activity prediction

Prediction of the activity of small molecules against Mycobacterium tuberculosis. This model has been developed by Ersilia thanks to the data provided by the Seattle Childrens (Dr. Tanya Parish research group). In vitro activity against M. tuberculosis was measured in a single point inhibition assay (10000 molecules) and selected compounds (259) were assayed in MIC50 and MIC90 assays. Cut-offs have been determined according to the researchers guidance. The models have been trained using LazyQSAR and achieved an AUROC of >0.8 in a 3-fold crossvalidation

This model was incorporated on 2023-11-24.Last packaged on 2026-08-07.

⁠Information

⁠Identifiers

• Ersilia Identifier: eos9ivc
• Slug: anti-mtb-seattle

⁠Domain

• Task: Annotation
• Subtask: Activity prediction
• Biomedical Area: Tuberculosis
• Target Organism: Mycobacterium tuberculosis
• Tags: Antimicrobial activity, MIC90

⁠Input

• Input: Compound
• Input Dimension: 1

⁠Output

• Output Dimension: 3
• Output Consistency: Fixed
• Interpretation: Probability of inhibition of M.tb in vitro in the MIC50, MIC90 and whole cell assays at cut-offs 10 uM and 70%, respectively

Below are the Output Columns of the model:

⁠Source and Deployment

• Source: Local
• Source Type: Internal
• DockerHub: https://hub.docker.com/r/ersiliaos/eos9ivc⁠
• Docker Architecture: AMD64, ARM64
• S3 Storage: https://ersilia-models-zipped.s3.eu-central-1.amazonaws.com/eos9ivc.zip⁠

⁠Resource Consumption

• Model Size (Mb): 7
• Environment Size (Mb): 5841
• Image Size (Mb): 5877.77

Computational Performance (seconds):

• 10 inputs: 35.27
• 100 inputs: 39.28
• 10000 inputs: 886.25

⁠References

• Source Code: https://github.com/ersilia-os/lazy-qsar⁠
• Publication: https://doi.org/10.1371/journal.pone.0205479⁠
• Publication Type: Peer reviewed
• Publication Year: 2019
• Ersilia Contributor: GemmaTuron⁠

⁠License

This package is licensed under a GPL-3.0⁠ license. The model contained within this package is licensed under a GPL-3.0-or-later⁠ 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 eos9ivc

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

# serve the model
ersilia serve eos9ivc
# 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!