ersiliaos/eos633t repository overview

⁠Extending molecular scaffolds with building blocks

MoLeR is a graph-based generative model that combines fragment-based and atom-by-atom generation of new molecules with scaffold-constrained optimization. It does not depend on generation history and therefore MoLeR is able to complete arbitrary scaffolds. The model has been trained on the GuacaMol dataset. Here we sample the 300k building blocks library from Enamine.

This model was incorporated on 2023-11-03.Last packaged on 2026-09-29.

⁠Information

⁠Identifiers

• Ersilia Identifier: eos633t
• Slug: moler-enamine-blocks

⁠Domain

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

⁠Input

• Input: Compound
• Input Dimension: 1

⁠Output

• Output Dimension: 100
• Output Consistency: Variable
• Interpretation: Up to 100 new molecules are sampled for each input molecule, preserving its scaffold.

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/eos633t⁠
• Docker Architecture: AMD64
• S3 Storage: https://ersilia-models-zipped.s3.eu-central-1.amazonaws.com/eos633t.zip⁠

⁠Resource Consumption

• Model Size (Mb): 33
• Environment Size (Mb): 2094
• Image Size (Mb): 2181.22

Computational Performance (seconds):

• 10 inputs: 38.1
• 100 inputs: 1341.74
• 10000 inputs: -1

⁠References

• Source Code: https://github.com/microsoft/molecule-generation⁠
• Publication: https://doi.org/10.48550/arXiv.2103.03864⁠
• Publication Type: Preprint
• Publication Year: 2022
• 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 eos633t

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

# serve the model
ersilia serve eos633t
# 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!