ersiliaos/eos92m1 repository overview

⁠TransPharmer Pharmacophore-Informed Molecule Generation

Generates new molecules that share the topological pharmacophore of an input reference compound while often changing its scaffold, useful for scaffold hopping. A GPT-style SMILES decoder prompted with a 72-bit pharmacophore fingerprint was trained on about 1.27 million GuacaMol (ChEMBL-derived) molecules. Designs seeded with a PLK1 inhibitor were synthesised, and three of four were sub-micromolar, the best at 5.1 nM. Sampling is stochastic, only about 18% of raw samples were valid and unique in that run, and outputs often keep moieties of the reference.

This model was incorporated on 2026-09-24.Last packaged on 2026-10-01.

⁠Information

⁠Identifiers

• Ersilia Identifier: eos92m1
• Slug: transpharmer

⁠Domain

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

⁠Input

• Input: Compound
• Input Dimension: 1

⁠Output

• Output Dimension: 100
• Output Consistency: Variable
• Interpretation: Up to 100 generated molecules as SMILES that share the input compounds topological pharmacophore.

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/eos92m1⁠
• Docker Architecture: AMD64
• S3 Storage: https://ersilia-models-zipped.s3.eu-central-1.amazonaws.com/eos92m1.zip⁠

⁠Resource Consumption

• Model Size (Mb): 26
• Environment Size (Mb): 1170
• Image Size (Mb): 1235.5

Computational Performance (seconds):

• 10 inputs: 36.82
• 100 inputs: 884.09
• 10000 inputs: -1

⁠References

• Source Code: https://github.com/iipharma/transpharmer-repo⁠
• Publication: https://doi.org/10.1038/s41467-025-56349-0⁠
• Publication Type: Peer reviewed
• Publication Year: 2025
• 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 eos92m1

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

# serve the model
ersilia serve eos92m1
# 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!