ersiliaos/eos694w repository overview

⁠REINVENT 4 Mol2MolMediumSimilarity

Produces up to 100 novel structures of moderate similarity to a query molecule, populating the space around a starting point without straying far from it. A similarity-trained Mol2Mol prior from REINVENT 4 drives the generation, one of several transformer priors in an open framework that also supports linker design, scaffold hopping and R-group replacement. The prior is sampled at random, so repeated runs return different sets; sampling is repeated up to a limit until 100 distinct structures are collected. The query and its stereoisomers are discarded.

This model was incorporated on 2024-02-07.Last packaged on 2026-10-26.

⁠Information

⁠Identifiers

• Ersilia Identifier: eos694w
• Slug: reinvent4-mol2mol-medium-similarity

⁠Domain

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

⁠Input

• Input: Compound
• Input Dimension: 1

⁠Output

• Output Dimension: 100
• Output Consistency: Variable
• Interpretation: Up to 100 sampled molecules of moderate structural similarity to the input compound, listed from most to least similar (Morgan Tanimoto); sets differ between runs.

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/eos694w⁠
• Docker Architecture: AMD64, ARM64
• S3 Storage: https://ersilia-models-zipped.s3.eu-central-1.amazonaws.com/eos694w.zip⁠

⁠Resource Consumption

• Model Size (Mb): 233
• Environment Size (Mb): 2368
• Image Size (Mb): 2501.05

Computational Performance (seconds):

• 10 inputs: 138.72
• 100 inputs: -1
• 10000 inputs: -1

⁠References

• Source Code: https://github.com/MolecularAI/REINVENT4⁠
• Publication: https://doi.org/10.1186/s13321-024-00812-5⁠
• Publication Type: Peer reviewed
• Publication Year: 2024
• Ersilia Contributor: ankitskvmdam⁠

⁠License

This package is licensed under a GPL-3.0⁠ license. The model contained within this package is licensed under a Apache-2.0⁠ 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 eos694w

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

# serve the model
ersilia serve eos694w
# 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!