ersiliaos/eos9p57 repository overview

⁠CReM Growth-Based Structure Generation

Generates new analogues of an input molecule by attaching a small fragment (1-2 heavy atoms) from a curated ChEMBL fragment database to an available hydrogen position. Every atom and bond of the original structure is preserved intact. Uses the GROW mode of the CReM framework. When more than 100 analogues exist, K-Means clustering picks 100 diverse ones; otherwise all are returned, so many inputs get fewer than 100. Cannot create new ring systems, so ring diversity is limited by the fragment database.

This model was incorporated on 2026-09-28.Last packaged on 2026-10-26.

⁠Information

⁠Identifiers

• Ersilia Identifier: eos9p57
• Slug: crem-grow

⁠Domain

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

⁠Input

• Input: Compound
• Input Dimension: 1

⁠Output

• Output Dimension: 100
• Output Consistency: Variable
• Interpretation: Up to 100 new molecules per input, each retaining the original structure with new fragments added at hydrogen positions.

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/eos9p57⁠
• Docker Architecture: AMD64, ARM64
• S3 Storage: https://ersilia-models-zipped.s3.eu-central-1.amazonaws.com/eos9p57.zip⁠

⁠Resource Consumption

• Model Size (Mb): 688
• Environment Size (Mb): 661
• Image Size (Mb): 2013.12

Computational Performance (seconds):

• 10 inputs: 33.06
• 100 inputs: 132.58
• 10000 inputs: -1

⁠References

• Source Code: https://github.com/DrrDom/crem⁠
• Publication: https://doi.org/10.1186/s13321-020-00431-w⁠
• Publication Type: Peer reviewed
• Publication Year: 2020
• Ersilia Contributor: arnaucoma24⁠

⁠License

This package is licensed under a GPL-3.0⁠ license. The model contained within this package is licensed under a BSD-3-Clause⁠ 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 eos9p57

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

# serve the model
ersilia serve eos9p57
# 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!