Computational Antibody Papers
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structure prediction
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2026
TitleKey points
- First fully open-source reproduction of the diffusion-based AlphaFold3 architecture that matches or exceeds its performance while strictly adhering to the same training data cutoff and model scale (especially on antibodies!).
- Unlike previous open-source models, it exhibits a consistent improvement in accuracy as more computational budget is allocated (you sample more).
- Protenix-v1 beats others in antibody-antigen interface prediction, outperforming AlphaFold3 52.31% vs. 48.75% success rate (dockq better than .23). That is nearly doubling the accuracy of open-source like Chai-1 23.12%.