ersiliaos/eos5j3l repository overview

⁠Ensemble-Conditioned Molecular Design

Generates 10 molecules conditioned on the 3D shape and pharmacophore profile of an input compound, using flow matching with ensemble-conditioned guidance from AstraZeneca and Chalmers. Trained on 300K GEOM-Drugs molecules with CREST conformer ensembles and 35K PDB-derived protein-ligand complexes. Drug-like inputs yield structurally distinct compounds; small rigid molecules are instead often reproduced, so guidance is weakened from the published defaults and the input compound and duplicates are filtered from the returned set.

This model was incorporated on 2026-09-22.Last packaged on 2026-09-23.

⁠Information

⁠Identifiers

• Ersilia Identifier: eos5j3l
• Slug: enscondflow-shape

⁠Domain

• Task: Sampling
• Subtask: Generation
• Biomedical Area: Any
• Target Organism: Any
• Tags: Compound generation

⁠Input

• Input: Compound
• Input Dimension: 1

⁠Output

• Output Dimension: 10
• Output Consistency: Fixed
• Interpretation: 10 generated molecules sharing the 3D shape and pharmacophore profile of the input compound.

Below are the Output Columns of the model:

⁠Source and Deployment

• Source: Local
• Source Type: External
• DockerHub: https://hub.docker.com/r/ersiliaos/eos5j3l⁠
• Docker Architecture: AMD64
• S3 Storage: https://ersilia-models-zipped.s3.eu-central-1.amazonaws.com/eos5j3l.zip⁠

⁠Resource Consumption

• Model Size (Mb): 1101
• Environment Size (Mb): 1893
• Image Size (Mb): 4044.08

Computational Performance (seconds):

• 10 inputs: 161.78
• 100 inputs: -1
• 10000 inputs: -1

⁠References

• Source Code: https://github.com/rssrwn/ensemble-cond-design⁠
• Publication: https://doi.org/10.48550/arXiv.2609.15077⁠
• Publication Type: Preprint
• Publication Year: 2026
• Ersilia Contributor: arnaucoma24⁠

⁠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 eos5j3l

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

# serve the model
ersilia serve eos5j3l
# 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!