Chai-1: Decoding the molecular interactions of life
Open accessAbstract
We introduce Chai-1, a multi-modal foundation model for molecular structure prediction that performs at the state-of-the-art across a variety of tasks relevant to drug discovery. Chai-1 can optionally be prompted with experimental restraints (e.g. derived from wet-lab data) which boosts performance by double-digit percentage points. Chai-1 can also be run in single-sequence mode with-out MSAs while preserving most of its performance. We release Chai-1 model weights and inference code as a Python package for non-commercial use and via a web interface where it can be used for free including for commercial drug discovery purposes.
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Structural modeling of Fli1-Spi1 and Cebpa-Gata2 interactions suggested that steric hindrance cannot explain these effects.
“Structural modeling50,51 of the Fli1-Spi1 and Cebpa-Gata2 interactions suggested that steric hinderance cannot explain these effects (Figures 4F and S3H–S3K; see STAR Methods, section structural prediction of TF-TF-DNA complexes).”
From Design principles of cell-state-specific enhancers in hematopoiesis (2025) · cites this paper as [51]
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Highly accurate protein structure prediction with AlphaFold
Jumper, J., Evans, R., Pritzel, A., Green, T., Figurnov, M., Ronneberger, O., Tunyasuvunakool, K., Bates, R., Žídek, A., Potapenko, A., et al. (2021) · Nature · doi:10.1038/s41586-021-03819-2 · Cited by 43,764 · see citing works
Accurate structure prediction of biomolecular interactions with AlphaFold 3
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ColabFold - Making protein folding accessible to all
Mirdita, M., Schütze, K., Moriwaki, Y., Heo, L., Ovchinnikov, S., & Steinegger, M. (2021) · doi:10.1101/2021.08.15.456425 · Cited by 9,391 · see citing works
Varadi, M., Anyango, S., Deshpande, M., Nair, S., Natassia, C., Yordanova, G., Yuan, D., Stroe, O., Wood, G., Laydon, A., et al. (2022) · Nucleic Acids Research · doi:10.1093/nar/gkab1061 · Cited by 7,850 · see citing works
Evolutionary-scale prediction of atomic level protein structure with a language model
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Self-citationRives, A., Meier, J., Sercu, T., Goyal, S., Lin, Z., Liu, J., Guo, D., Ott, M., Zitnick, C. L., Ma, J., et al. (2019) · doi:10.1101/622803 · Cited by 3,280 · see citing works
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Design principles of cell-state-specific enhancers in hematopoiesis
Frömel, R., Rühle, J., Bernal Martinez, A., Szu-Tu, C., Pacheco Pastor, F., Martinez-Corral, R., & Velten, L. (2025) · Cell · doi:10.1016/j.cell.2025.04.017 · Cited by 29 · see citing works
Wang, B., Wang, C., Chen, J., Liu, D., Sun, C., Zhang, J., Zhang, K., & Li, H. (2026) · Nature Machine Intelligence · doi:10.1038/s42256-026-01198-9 · Cited by 5 · see citing works
Optimizing Stability in Dynamic Small-Molecule Binding Proteins
Scherer, M., Kriegel, M., Höcker, B., & Fleishman, S. J. (2026) · Journal of the American Chemical Society · doi:10.1021/jacs.5c19571 · Cited by 2 · see citing works
Liu, L., Liu, Y., Ye, X., Zhang, S., Li, Y., Zhu, K., Xue, Y., Zhou, J., Zhang, X., & Fang, X. (2026) · Nature Machine Intelligence · doi:10.1038/s42256-026-01264-2 · Cited by 1 · see citing works
- Authors
- Discovery, C., Boitreaud, J., Dent, J., McPartlon, M., Meier, J., Reis, V., Rogozhnikov, A., & Wu, K.
- Corresponding author
- Meier, Joshua
- Venue
- bioRxiv (Cold Spring Harbor Laboratory)
- Publisher
- openRxiv
- Published
- 2024-10-11
- OpenAlex
- W4403324307
- Cited by
- 517
- References
- 7
- Citations by year
- 2026: 308 · 2025: 203 · 2024: 6
- Type
- posted content
- Language
- en
- Open access
- green
- doi.org
- Licence
- Locations
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc)
- Topics
- Physical Sciences › Computer Science › Computational Theory and Mathematics › Computational Drug Discovery Methods
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Machine Learning in Bioinformatics
- Keywords
- Chai-1, multimodal foundation models, molecular structure prediction, protein structure prediction, drug discovery, molecular interactions
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