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| license: cc-by-nc-4.0 |
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| # FlashPPI: Linear-time prediction of proteome-scale microbial protein interactions |
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| FlashPPI is a contrastively trained model for protein-protein interaction (PPI) prediction, grounded in residue-level interactions, that enables full-proteome interaction prediction in minutes. |
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| By reframing PPI prediction as a dense retrieval task, FlashPPI circumvents the quadratic computational bottleneck of traditional all-vs-all structural screening. |
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| - **Scalable:** Reduces proteome-wide screening from days/months to minutes. |
| - **Interpretable:** Predicts fine-grained, residue-level 2D contact maps for retrieved interaction candidates. |
| - **Genomic Priors:** Leverages [gLM2](https://huggingface.co/tattabio/gLM2_650M) to capture cross-protein, multi-gene co-evolutionary signals. |
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| ## Web Server |
| FlashPPI is integrated into [seqhub.org](https://seqhub.org). You can upload a FASTA and interactively explore whole-proteome networks and contact maps. Explore an example network [here](https://seqhub.org/tattabio/mycobacterium_tb?ppi=true). |
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| ## Usage |
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| See the github repo https://github.com/TattaBio/flashppi for usage and inference scripts. |
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| ## License |
| The model code and inference scripts in the GitHub repo are licensed under the Apache License 2.0. |
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| The FlashPPI model weights are hosted on Hugging Face and released under the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) license. The weights are freely available for academic and research purposes. |
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| ## Citing |
| If you use FlashPPI or our datasets in your research, please cite: |
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| ``` |
| @article {Cornman2026FlashPPI, |
| author = {Cornman, Andre and Tranzillo, Matt and Zulaybar, Nicolo G and Bouzit, Imane and Hwang, Yunha}, |
| title = {Linear-time prediction of proteome-scale microbial protein interactions}, |
| year = {2026}, |
| doi = {10.64898/2026.03.01.708874}, |
| publisher = {Cold Spring Harbor Laboratory}, |
| URL = {https://www.biorxiv.org/content/early/2026/03/02/2026.03.01.708874}, |
| journal = {bioRxiv} |
| } |
| ``` |
