Diffusing protein binders to intrinsically disordered proteins
Open accessPublished version of a preprint
Abstract
Proteins that bind to intrinsically disordered proteins (IDPs) and intrinsically disordered regions (IDRs) with high affinity and specificity could be useful for therapeutic and diagnostic applications 1–4 . However, a general methodology for targeting IDPs or IDRs has yet to be developed. Here we show that starting only from the target sequence of the input, and freely sampling both target and binding protein conformations, RFdiffusion 5 can generate binders to IDPs and IDRs in a wide range of conformations. We used this approach to generate binders to the IDPs amylin, C-peptide, VP48 and BRCA1_ARATH in diverse conformations with a dissociation constant ( K d ) ranging from 3 to 100 nM. For the IDRs G3BP1, common cytokine receptor γ-chain (IL-2RG) and prion protein, we diffused binders to β-strand conformations of the targets, obtaining K d between 10 and 100 nM. Fluorescence imaging experiments show that the binders bind to their respective targets in cells. The G3BP1 binder disrupts stress granule formation in cells, and the amylin binder inhibits amyloid fibril formation and dissociates existing fibres, enables targeting of both monomeric and fibrillar amylin to lysosomes, and increases the sensitivity of mass spectrometry-based amylin detection. Our approach should be useful for creating binders to flexible IDPs or IDRs spanning a wide range of intrinsic conformational preferences.
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Cites
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
Intrinsically unstructured proteins and their functions
Dyson, H. J., & Wright, P. E. (2005) · Nature Reviews Molecular Cell Biology · doi:10.1038/nrm1589 · Cited by 3,871 · see citing works
Watson, J. L., Juergens, D., Bennett, N. R., Trippe, B. L., Yim, J., Eisenach, H. E., Ahern, W., Borst, A. J., Ragotte, R. J., Milles, L. F., et al. (2022) · doi:10.1101/2022.12.09.519842 · Cited by 2,369 · see citing works
Self-citationDe novo design of protein structure and function with RFdiffusion
Watson, J. L., Juergens, D., Bennett, N. R., Trippe, B. L., Yim, J., Eisenach, H. E., Ahern, W., Borst, A. J., Ragotte, R. J., Milles, L. F., et al. (2023) · Nature · doi:10.1038/s41586-023-06415-8 · Cited by 2,325 · see citing works
Self-citationRobust deep learning based protein sequence design using ProteinMPNN
Dauparas, J., Anishchenko, I., Bennett, N., Bai, H., Ragotte, R. J., Milles, L. F., Wicky, B. I. M., Courbet, A., de Haas, R. J., Bethel, N., et al. (2022) · doi:10.1101/2022.06.03.494563 · Cited by 2,107 · see citing works
Self-citationRobust deep learning–based protein sequence design using ProteinMPNN
Dauparas, J., Anishchenko, I., Bennett, N., Bai, H., Ragotte, R. J., Milles, L. F., Wicky, B. I. M., Courbet, A., de Haas, R. J., Bethel, N., et al. (2022) · Science · doi:10.1126/science.add2187 · Cited by 2,070 · see citing works
Self-citationReproducibility crisis: Blame it on the antibodies
Baker, M. (2015) · Nature · doi:10.1038/521274a · Cited by 830 · see citing works
Reproducibility: Standardize antibodies used in research
Bradbury, A., & Plückthun, A. (2015) · Nature · doi:10.1038/518027a · Cited by 647 · see citing works
Hoofnagle, A. N., Becker, J. O., Wener, M. H., & Heinecke, J. W. (2008) · Clinical Chemistry · doi:10.1373/clinchem.2008.109652 · Cited by 314 · cited 2× · see citing works
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- Authors
- Liu, C., Wu, K., Choi, H., Han, H. L., Zhang, X., Watson, J. L., Ahn, G., Zhang, J. Z., Shijo, S., Good, L. L., Fischer, C. M., Bera, A. K., Kang, A., Brackenbrough, E., Coventry, B., Hick, D. R., Qamar, S., Li, X., Decarreau, J., Gerben, S. R., Yang, W., Goreshnik, I., Vafeados, D., Wang, X., Lamb, M., Murray, A., Kenny, S., Bauer, M. S., Hoofnagle, A. N., Zhu, P., Knowles, T. P. J., & Baker, D.
- Affiliations
- University of Washington (US)
- Chinese Academy of Sciences (CN)
- National Institutes of Health (US)
- University of Cambridge (GB)
- Howard Hughes Medical Institute (US)
- Corresponding author
- Wu, Kejia
- Baker, David
- ORCID
- Liu, Caixuan
- Wu, Kejia
- Choi, Hojun
- Han, Hannah L.
- Zhang, Xueli
- Watson, Joseph L.
- Ahn, Green
- Zhang, Jason Z.
- Good, Lydia L.
- Fischer, Charlotte M.
- Bera, Asim K.
- Kang, Alex
- Brackenbrough, Evans
- Coventry, Brian
- Hick, Derrick R.
- Qamar, Seema
- Li, Xinting
- Decarreau, Justin
- Gerben, Stacey R.
- Yang, Wei
- Goreshnik, Inna
- Vafeados, Dionne
- Wang, Xinru
- Lamb, Mila
- Murray, Analisa
- Kenny, Sebastian
- Bauer, Magnus S.
- Hoofnagle, Andrew N.
- Zhu, Ping
- Knowles, Tuomas P. J.
- Baker, David
- Venue
- Nature
- Published
- 2025-07-30
- Volume
- 644
- Issue
- 8077
- Pages
- 809-817
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- PMC
- PMC12367549
- OpenAlex
- W4412737078
- Cited by
- 79
- References
- 9
- Citations by year
- 2026: 65 · 2025: 14
- FWCI
- 23.75
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Nature (publishedVersion, cc-by-nc-nd)
- PubMed Central (publishedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- Funders
- National Institutes of Health (1k99ca293001-01)
- National Institute of General Medical Sciences (P30GM133893)
- National Institute of Diabetes and Digestive and Kidney Diseases (P30DK017047, U01DK137097)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Chemical Synthesis and Analysis
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Monoclonal and Polyclonal Antibodies Research
- Keywords
- intrinsically disordered proteins, intrinsically disordered regions, protein binder design, RFdiffusion, protein design, amylin, amyloid fibril formation, stress granules, G3BP1, prion protein, BRCA1, C-peptide, dissociation constant, lysosomal targeting
- MeSH terms
- RNA Recognition Motif Proteins, Prion Proteins, Amyloid, Humans, Lysosomes, Models, Molecular, Protein Binding, Islet Amyloid Polypeptide, Intrinsically Disordered Proteins
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