De novo-designed pMHC binders facilitate T cell–mediated cytotoxicity toward cancer cells
Open accessPublished version of a preprint
Abstract
The recognition of intracellular antigens by CD8 + T cells through T cell receptors (TCRs) is central for adaptive immunity against infections and cancer. However, the identification of TCRs from patient material remains complex. We present a rapid de novo minibinder (miBd) design platform leveraging state-of-the-art generative models to engineer miBds targeting the cancer-associated peptide-bound major histocompatibility complex (pMHC) SLLMWITQC/HLA-A*02:01 (NY-ESO-1). Incorporating in silico cross-panning enabled computational prescreening of specificity, and molecular dynamics simulations allowed for improved predictability of in vitro success. We identified a high-affinity NY-ESO-1 binder and confirmed its structure using cryo–electron microscopy, which, when incorporated in a chimeric antigen receptor, induced killing of NY-ESO-1 + melanoma cells. We further designed and validated binders to a neoantigen pMHC complex, RVTDESILSY/HLA-A*01:01, with unknown structure, demonstrating the potential for precision immunotherapy.
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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
Abramson, J., Adler, J., Dunger, J., Evans, R., Green, T., Pritzel, A., Ronneberger, O., Willmore, L., Ballard, A. J., Bambrick, J., et al. (2024) · Nature · doi:10.1038/s41586-024-07487-w · Cited by 15,861 · see citing works
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
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
De 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
Robust 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
Robust 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
Flagged first, then by citations
- Authors
- Johansen, K. H., Wolff, D. S., Scapolo, B., Fernández-Quintero, M. L., Risager Christensen, C., Loeffler, J. R., Rivera-de-Torre, E., Overath, M. D., Kjærgaard Munk, K., Morell, O., Viuff, M. C., Lacunza, I., Damm Englund, A. T., Due, M., Gharpure, A., Forli, S., Rodriguez Pardo, C., Tamhane, T., Qingjie Andersen, E., Haldrup Björnsson, K., Fernandes, J. S., Voss, L. F., Thumtecho, S., Ward, A. B., Ormhøj, M., Reker Hadrup, S., & Jenkins, T. P.
- Affiliations
- Technical University of Denmark (DK)
- Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA, USA.
- Department of Health Technology, Technical University of Denmark, Kongens Lyngby, Denmark.
- Scripps Research Institute (US)
- Department of Biotechnology and Biomedicine, Technical University of Denmark, Kongens Lyngby, Denmark.
- Corresponding author
- Johansen, Kristoffer Haurum
- Wolff, Darian Stephan
- Scapolo, Beatrice
- Jenkins, Timothy P.
- ORCID
- Johansen, Kristoffer Haurum
- Wolff, Darian Stephan
- Scapolo, Beatrice
- Fernández-Quintero, Monica L.
- Risager Christensen, Charlotte
- Loeffler, Johannes R.
- Rivera-de-Torre, Esperanza
- Overath, Max D.
- Kjærgaard Munk, Kamilla
- Morell, Oliver
- Viuff, Marie Christine
- Lacunza, Iñigo
- Damm Englund, Alberte T.
- Due, Mathilde
- Gharpure, Anant
- Forli, Stefano
- Rodriguez Pardo, Carlos
- Tamhane, Tripti
- Haldrup Björnsson, Kasper
- Fernandes, Jordan Sylvester
- Voss, Lasse Frank
- Thumtecho, Suthimon
- Ward, Andrew B.
- Ormhøj, Maria
- Reker Hadrup, Sine
- Jenkins, Timothy P.
- Venue
- Science
- Published
- 2025-07-24
- Volume
- 389
- Issue
- 6758
- Pages
- 380-385
- ISSN
- 0036-8075 (ISSN-L)
- 1095-9203
- OpenAlex
- W4412622989
- Cited by
- 77
- References
- 7
- Citations by year
- 2026: 61 · 2025: 15 · 2024: 1
- FWCI
- 22.85
- Type
- journal article
- Language
- en
- Open access
- green
- doi.org
- Licence
- cc-by-nc
- Locations
- Science (publishedVersion)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc)
- PubMed (publishedVersion)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › vaccines and immunoinformatics approaches
- Health Sciences › Medicine › Oncology › CAR-T cell therapy research
- Life Sciences › Immunology and Microbiology › Immunology › Immunotherapy and Immune Responses
- Keywords
- NY-ESO-1, HLA-A*0201, T cell cytotoxicity, chimeric antigen receptor, melanoma, neoantigens, T cell receptor engineering, generative models, precision immunotherapy, cancer immunotherapy
- MeSH terms
- Protein Conformation, alpha-Helical, Receptors, Chimeric Antigen, Antigens, Neoplasm, Cytotoxicity, Immunologic, Humans, Major Histocompatibility Complex, Melanoma, Membrane Proteins, Peptides, Protein Binding, Receptors, Antigen, T-Cell, Protein Engineering, HLA-A2 Antigen, CD8-Positive T-Lymphocytes, Molecular Mimicry, Cryoelectron Microscopy, Cell Line, Tumor, Molecular Dynamics Simulation
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