ersiliaos/eos6a1h repository overview

⁠CoCoGraph Small-Fragment Inpainting

Attaches a randomly selected small fragment (2–6 heavy atoms, one of 500 molecular formulas) to a random hydrogen-bearing atom of the input and refines it with CoCoGraphs constrained graph diffusion, which swaps bond pairs so every intermediate stays valence-valid. Each output is re-parsed with RDKit and redrawn if invalid or already drawn; after 30 failed tries its cell stays empty. The models were trained on 2.25 million PubChem, ChEMBL, ZINC and NIST molecules; in a Turing-like test, 121 organic chemists distinguished its outputs from real molecules with only 62% accuracy.

This model was incorporated on 2026-08-28.Last packaged on 2026-10-26.

⁠Information

⁠Identifiers

• Ersilia Identifier: eos6a1h
• Slug: cocograph-small

⁠Domain

• Task: Sampling
• Subtask: Generation
• Biomedical Area: Any
• Target Organism: Any
• Tags: Compound generation, Chemical graph model

⁠Input

• Input: Compound
• Input Dimension: 1

⁠Output

• Output Dimension: 100
• Output Consistency: Variable
• Interpretation: Up to 100 different molecules, each the input with a new small fragment attached at a hydrogen-bearing atom and refined by graph diffusion; empty cells where none could be made.

Below are the Output Columns of the model:

10 of 100 columns are shown

⁠Source and Deployment

• Source: Local
• Source Type: External
• DockerHub: https://hub.docker.com/r/ersiliaos/eos6a1h⁠
• Docker Architecture: AMD64
• S3 Storage: https://ersilia-models-zipped.s3.eu-central-1.amazonaws.com/eos6a1h.zip⁠

⁠Resource Consumption

• Model Size (Mb): 52
• Environment Size (Mb): 1511
• Image Size (Mb): 1594.3

Computational Performance (seconds):

• 10 inputs: 232.66
• 100 inputs: -1
• 10000 inputs: -1

⁠References

• Source Code: https://doi.org/10.5281/zenodo.18940151⁠
• Publication: https://doi.org/10.1038/s42256-026-01229-5⁠
• Publication Type: Peer reviewed
• 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 eos6a1h

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

# serve the model
ersilia serve eos6a1h
# 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!