ersiliaos/eos9f6t repository overview

⁠SARS-CoV inhibition

This model was developed to support the early efforts in the identification of novel drugs against SARS-CoV2. It predicts the probability that a small molecule inhibits SARS-3CLpro-mediated peptide cleavage. It was developed using a high-throughput screening against the 3CL protease of SARS-CoV1, as no data was yet available for the new virus (SARS-CoV2) causing the COVID-19 pandemic. It uses the ChemProp model.

This model was incorporated on 2021-04-29.Last packaged on 2025-10-08.

⁠Information

⁠Identifiers

• Ersilia Identifier: eos9f6t
• Slug: chemprop-sars-cov-inhibition

⁠Domain

• Task: Annotation
• Subtask: Activity prediction
• Biomedical Area: COVID-19
• Target Organism: SARS-CoV-2
• Tags: COVID19, Antiviral activity, Sars-CoV-2, Chemical graph model

⁠Input

• Input: Compound
• Input Dimension: 1

⁠Output

• Output Dimension: 1
• Output Consistency: Fixed
• Interpretation: Probability of 3CL protease inhibition (%) The classifier was trained using a threshold of 12% of inhibition

Below are the Output Columns of the model:

⁠Source and Deployment

• Source: Local
• Source Type: External
• DockerHub: https://hub.docker.com/r/ersiliaos/eos9f6t⁠
• Docker Architecture: AMD64, ARM64
• S3 Storage: https://ersilia-models-zipped.s3.eu-central-1.amazonaws.com/eos9f6t.zip⁠

⁠Resource Consumption

• Model Size (Mb): 9
• Environment Size (Mb): 5852
• Image Size (Mb): 5760.92

Computational Performance (seconds):

• 10 inputs: 36.21
• 100 inputs: 28.61
• 10000 inputs: 612.21

⁠References

• Source Code: http://chemprop.csail.mit.edu/checkpoints⁠
• Publication: https://pubmed.ncbi.nlm.nih.gov/32084340/⁠
• Publication Type: Peer reviewed
• Publication Year: 2020
• 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 eos9f6t

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

# serve the model
ersilia serve eos9f6t
# 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!