ersiliaos/eos3f8h repository overview

⁠Antimicrobial activity prediction from EU OpenScreen data

High throughput screening of the EU OpenScreen library (~100.000 compounds) against 7 pathogens of reference (A. baumannii, C. albicans, E. coli, E. faecalis, K. pneumoniae, P. aeruginosa, S. aureus). Assays were obtained from the European Chemical Biology Database and correspond to single point inhibitions with cut-offs ranging from 50 to 70% and incubation concentrations between 41.7 to 50 uM. Models were trained by Ersilia using LazyQSAR v3, achieving a mean AUROC of 0.94 (range 0.84-0.99) upon 5-fold crossvalidation.

This model was incorporated on 2026-08-06.Last packaged on 2026-08-11.

⁠Information

⁠Identifiers

• Ersilia Identifier: eos3f8h
• Slug: eu-openscreen-hts

⁠Domain

• Task: Annotation
• Subtask: Activity prediction
• Biomedical Area: Antimicrobial resistance, Candidiasis, Fungal infections
• Target Organism: Acinetobacter baumannii, Candida albicans, Escherichia coli, Enterococcus faecalis, Klebsiella pneumoniae, Pseudomonas aeruginosa, Staphylococcus aureus
• Tags: Antimicrobial activity, Antifungal activity, ESKAPE, Gram-negative bacteria, Gram-positive bacteria, Fungi

⁠Input

• Input: Compound
• Input Dimension: 1

⁠Output

• Output Dimension: 7
• Output Consistency: Fixed
• Interpretation: Rank score per pathogen between 0 and 1; higher values indicate greater predicted probability of growth inhibition.

Below are the Output Columns of the model:

⁠Source and Deployment

• Source: Local
• Source Type: Internal
• DockerHub: https://hub.docker.com/r/ersiliaos/eos3f8h⁠
• Docker Architecture: AMD64, ARM64
• S3 Storage: https://ersilia-models-zipped.s3.eu-central-1.amazonaws.com/eos3f8h.zip⁠

⁠Resource Consumption

• Model Size (Mb): 529
• Environment Size (Mb): 3573
• Image Size (Mb): 4540.66

Computational Performance (seconds):

• 10 inputs: 84.89
• 100 inputs: 78.53
• 10000 inputs: -1

⁠References

• Source Code: https://github.com/ersilia-os/eu-openscreen-antimicrobial-tasks⁠
• Publication: https://doi.org/10.1093/nar/gkae904⁠
• Publication Type: Peer reviewed
• Publication Year: 2024
• 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 eos3f8h

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

# serve the model
ersilia serve eos3f8h
# 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!