ersiliaos/eos7kpb repository overview

⁠H3D virtual screening cascade light

This panel of models provides predictions for the H3D virtual screening cascade. It leverages the Ersilia Compound Embedding and FLAML. The H3D virtual screening cascade contains models for Mycobacterium tuberculosis and Plasmodium falciparum IC50 predictions, as well as ADME, cytotoxicity and solubility assays

This model was incorporated on 2023-05-09.Last packaged on 2026-07-06.

⁠Information

⁠Identifiers

• Ersilia Identifier: eos7kpb
• Slug: h3d-virtual-screening-cascade-light

⁠Domain

• Task: Annotation
• Subtask: Activity prediction
• Biomedical Area: ADMET, Malaria, Tuberculosis
• Target Organism: Mycobacterium tuberculosis, Plasmodium falciparum, Homo sapiens, Rattus norvegicus, Mus musculus
• Tags: Antimicrobial activity, ADME, Cytotoxicity, Solubility

⁠Input

• Input: Compound
• Input Dimension: 1

⁠Output

• Output Dimension: 28
• Output Consistency: Fixed
• Interpretation: The raw scores are the ones emerging from the FLAML model. The ones with a sufix _norm represent the percentile in the scale 0-1 over a ChEMBL dataset of 200k compounds.

Below are the Output Columns of the model:

10 of 28 columns are shown

⁠Source and Deployment

• Source: Local
• Source Type: Internal
• DockerHub: https://hub.docker.com/r/ersiliaos/eos7kpb⁠
• Docker Architecture: AMD64, ARM64
• S3 Storage: https://ersilia-models-zipped.s3.eu-central-1.amazonaws.com/eos7kpb.zip⁠

⁠Resource Consumption

• Model Size (Mb): 117
• Environment Size (Mb): 1114
• Image Size (Mb): 1365.45

Computational Performance (seconds):

• 10 inputs: 33.07
• 100 inputs: 24.38
• 10000 inputs: 190.44

⁠References

• Source Code: https://github.com/ersilia-os/h3d-screening-cascade-models⁠
• Publication: https://doi.org/10.1038/s41467-023-41512-2⁠
• Publication Type: Peer reviewed
• Publication Year: 2023
• Ersilia Contributor: miquelduranfrigola⁠

⁠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 eos7kpb

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

# serve the model
ersilia serve eos7kpb
# 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!