ersiliaos/eos2ta5 repository overview

⁠Ligand-based prediction of hERG blockade

A robust predictor for hERG channel blockade based on an ensemble of five deep learning models. The authors have collected a dataset from public sources, such as BindingDB and ChEMBL on hERG blockers and non-blockers. The cut-off for hERG blockade was set at IC50 < 10 uM for the classifier.

This model was incorporated on 2021-10-18.Last packaged on 2026-07-21.

⁠Information

⁠Identifiers

• Ersilia Identifier: eos2ta5
• Slug: cardiotoxnet-herg

⁠Domain

• Task: Annotation
• Subtask: Property calculation or prediction
• Biomedical Area: ADMET
• Target Organism: Homo sapiens
• Tags: hERG, Toxicity, Cardiotoxicity

⁠Input

• Input: Compound
• Input Dimension: 1

⁠Output

• Output Dimension: 1
• Output Consistency: Fixed
• Interpretation: Probability that the compound inhibits hERG (IC50 < 10 uM)

Below are the Output Columns of the model:

⁠Source and Deployment

• Source: Local
• Source Type: External
• DockerHub: https://hub.docker.com/r/ersiliaos/eos2ta5⁠
• Docker Architecture: AMD64
• S3 Storage: https://ersilia-models-zipped.s3.eu-central-1.amazonaws.com/eos2ta5.zip⁠

⁠Resource Consumption

• Model Size (Mb): 415
• Environment Size (Mb): 1563
• Image Size (Mb): 2275.86

Computational Performance (seconds):

• 10 inputs: 29.51
• 100 inputs: 42.91
• 10000 inputs: 1389.3

⁠References

• Source Code: https://github.com/Abdulk084/CardioTox⁠
• Publication: https://doi.org/10.1186/s13321-021-00541-z⁠
• 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 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 eos2ta5

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

# serve the model
ersilia serve eos2ta5
# 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!