ersiliaos/eos46ev repository overview

⁠Mycobacterium tuberculosis inhibitor prediction

Flags likely inhibitors of Mycobacterium tuberculosis H37Rv growth. Ye and colleagues pooled minimum inhibitory concentrations for three ChEMBL targets, called a compound active below 5 uM and ended with 2,424 inhibitors against 6,094 inactives. The served predictor is their best configuration, a stacked ensemble of support vector machine, random forest, XGBoost and deep neural network predictions over RDKit descriptors and Morgan fingerprints. It reached an AUC of 0.94 on a scaffold-split test set but 0.75 on compounds published later, so unfamiliar scaffolds are read with caution.

This model was incorporated on 2022-06-28.Last packaged on 2026-10-07.

⁠Information

⁠Identifiers

• Ersilia Identifier: eos46ev
• Slug: chemtb

⁠Domain

• Task: Annotation
• Subtask: Activity prediction
• Biomedical Area: Tuberculosis
• Target Organism: Mycobacterium tuberculosis
• Tags: IC50, Antimicrobial activity

⁠Input

• Input: Compound
• Input Dimension: 1

⁠Output

• Output Dimension: 1
• Output Consistency: Fixed
• Interpretation: Probability of Mycobacterium tuberculosis growth inhibition, with actives defined by a minimum inhibitory concentration below 5 uM.

Below are the Output Columns of the model:

⁠Source and Deployment

• Source: Local
• Source Type: External
• DockerHub: https://hub.docker.com/r/ersiliaos/eos46ev⁠
• Docker Architecture: AMD64, ARM64
• S3 Storage: https://ersilia-models-zipped.s3.eu-central-1.amazonaws.com/eos46ev.zip⁠

⁠Resource Consumption

• Model Size (Mb): 109
• Environment Size (Mb): 2095
• Image Size (Mb): 2187.65

Computational Performance (seconds):

• 10 inputs: 24.47
• 100 inputs: 15.86
• 10000 inputs: 161.94

⁠References

• Source Code: http://cadd.zju.edu.cn/chemtb/⁠
• Publication: https://doi.org/10.1093/bib/bbab068⁠
• Publication Type: Peer reviewed
• Publication Year: 2021
• 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 None⁠ 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 eos46ev

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

# serve the model
ersilia serve eos46ev
# 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!