De novo design of picomolar SARS-CoV-2 miniprotein inhibitors
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Abstract
Miniproteins against SARS-CoV-2: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is decorated with spikes, and viral entry into cells is initiated when these spikes bind to the host angiotensin-converting enzyme 2 (ACE2) receptor. Many monoclonal antibody therapies in development target the spike proteins. Cao et al. designed small, stable proteins that bind tightly to the spike and block it from binding to ACE2. The best designs bind with very high affinity and prevent SARS-CoV-2 infection of mammalian Vero E6 cells. Cryo–electron microscopy shows that the structures of the two most potent inhibitors are nearly identical to the computational models. Unlike antibodies, the miniproteins do not require expression in mammalian cells, and their small size and high stability may allow formulation for direct delivery to the nasal or respiratory system. Science , this issue p. 426
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The method yielded picomolar binders to the SARS-CoV-2 spike RBD near the ACE2 binding site, with an IC50 of 0.15 ng ml-1 in cell culture.
“Similar to FGFR2, IL-7Rα and VirB8, the method yielded picomolar binders, which are among the most potent compounds known to inhibit the virus in cell culture (half-maximal inhibitory concentration (IC50) of 0.15 ng ml–1).”
From Design of protein-binding proteins from the target structure alone (2022) · cites this paper as [38]
Cryo-EM structures of SARS-CoV-2 binders LCB1 and LCB3 in complex with the virus were nearly identical to the design models, with Cα r.m.s.d. values of 1.27 Å and 1.9 Å, respectively.
“Further highlighting the accuracy of the protein interface design method, cryogenic electron microscopy (cryo-EM) structures of the SARS-CoV-2 binders LCB1 and LCB3 in complex with the virus were also nearly identical to the design models, with Cα r.m.s.d. value of 1.27 Å and 1.9 Å, respectively38 (Fig. 5f).”
From Design of protein-binding proteins from the target structure alone (2022) · cites this paper as [38]
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Cites
UCSF Chimera—A visualization system for exploratory research and analysis
Pettersen, E. F., Goddard, T. D., Huang, C. C., Couch, G. S., Greenblatt, D. M., Meng, E. C., & Ferrin, T. E. (2004) · Journal of Computational Chemistry · doi:10.1002/jcc.20084 · Cited by 45,260 · see citing works
cryoSPARC: algorithms for rapid unsupervised cryo-EM structure determination
Punjani, A., Rubinstein, J. L., Fleet, D. J., & Brubaker, M. A. (2017) · Nature Methods · doi:10.1038/nmeth.4169 · Cited by 9,168 · see citing works
Structure, function and antigenicity of the SARS-CoV-2 spike glycoprotein
Walls, A. C., Park, Y.-J., Tortorici, M. A., Wall, A., McGuire, A. T., & Veesler, D. (2020) · doi:10.1101/2020.02.19.956581 · Cited by 8,586 · see citing works
Self-citationLiebschner, D. C., Afonine, P. V., Baker, M. L., Bunkòczi, G., Chen, V. B., Croll, T. I., Hintze, B. J., Hung, L., Jain, S., McCoy, A. J., et al. (2019) · Acta Crystallographica Section D Structural Biology · doi:10.1107/s2059798319011471 · Cited by 6,709 · see citing works
Structure of the SARS-CoV-2 spike receptor-binding domain bound to the ACE2 receptor
Lan, J., Ge, J., Yu, J., Shan, S., Zhou, H., Fan, S., Zhang, Q., Shi, X., Wang, Q., Zhang, L., et al. (2020) · Nature · doi:10.1038/s41586-020-2180-5 · Cited by 5,983 · see citing works
UCSF ChimeraX: Meeting modern challenges in visualization and analysis
Goddard, T. D., Huang, C. C., Meng, E. C., Pettersen, E. F., Couch, G. S., Morris, J. H., & Ferrin, T. E. (2018) · Protein Science · doi:10.1002/pro.3235 · Cited by 5,267 · see citing works
Structural basis for the recognition of SARS-CoV-2 by full-length human ACE2
Yan, R., Zhang, Y., Li, Y., Xia, L., Guo, Y., & Zhou, Q. (2020) · Science · doi:10.1126/science.abb2762 · Cited by 4,950 · see citing works
MolProbity: More and better reference data for improved all‐atom structure validation
Williams, C. J., Headd, J. J., Moriarty, N. W., Prisant, M. G., Videau, L. L., Deis, L. N., Verma, V., Keedy, D. A., Hintze, B. J., Chen, V. B., et al. (2018) · Protein Science · doi:10.1002/pro.3330 · Cited by 4,599 · see citing works
New tools for automated high-resolution cryo-EM structure determination in RELION-3
Zivanov, J., Nakane, T., Forsberg, B., Kimanius, D., Hagen, W., Lindahl, E., & Scheres, S. (2018) · eLife · doi:10.7554/elife.42166 · Cited by 4,377 · see citing works
Structural basis of receptor recognition by SARS-CoV-2
Shang, J., Ye, G., Shi, K., Wan, Y., Luo, C., Aihara, H., Geng, Q., Auerbach, A., & Li, F. (2020) · Nature · doi:10.1038/s41586-020-2179-y · Cited by 3,661 · see citing works
Structural and Functional Basis of SARS-CoV-2 Entry by Using Human ACE2
Wang, Q., Zhang, Y., Wu, L., Niu, S., Song, C., Zhang, Z., Lu, G., Qiao, C., Hu, Y., Yuen, K.-Y., et al. (2020) · Cell · doi:10.1016/j.cell.2020.03.045 · Cited by 2,892 · see citing works
Structural and functional analysis of a potent sarbecovirus neutralizing antibody
Pinto, D., Park, Y.-J., Beltramello, M., Walls, A. C., Tortorici, M. A., Bianchi, S., Jaconi, S., Culap, K., Zatta, F., De Marco, A., et al. (2020) · doi:10.1101/2020.04.07.023903 · Cited by 1,752 · see citing works
Self-citationAutomated molecular microscopy: The new Leginon system
Suloway, C. J. M., Pulokas, J., Fellmann, D., Cheng, A., Guerra, F., Quispe, J. D., Stagg, S. M., Potter, C. S., & Carragher, B. O. (2005) · Journal of Structural Biology · doi:10.1016/j.jsb.2005.03.010 · Cited by 1,681 · see citing works
Non-uniform refinement: adaptive regularization improves single-particle cryo-EM reconstructionPreprint
Punjani, A., Zhang, H.-W., & Fleet, D. J. (2019) · Nature Methods · doi:10.1101/2019.12.15.877092 · Cited by 1,580 · see citing works
Non-uniform refinement: adaptive regularization improves single-particle cryo-EM reconstruction
Punjani, A., Zhang, H., & Fleet, D. J. (2020) · Nature Methods · doi:10.1038/s41592-020-00990-8 · Cited by 1,559 · see citing works
SARS-CoV-2 Reverse Genetics Reveals a Variable Infection Gradient in the Respiratory Tract
Hou, Y. J., Okuda, K., Edwards, C. E., Martinez, D. R., Asakura, T., Dinnon, K. H., Kato, T., Lee, R. E., Yount, B. L., Mascenik, T. M., et al. (2020) · Cell · doi:10.1016/j.cell.2020.05.042 · Cited by 1,488 · see citing works
A highly conserved cryptic epitope in the receptor binding domains of SARS-CoV-2 and SARS-CoV
Yuan, M., Wu, N. C., Zhu, X., Lee, C.-C. D., So, R. T. Y., Lv, H., Mok, C. K. P., & Wilson, I. A. (2020) · Science · doi:10.1126/science.abb7269 · Cited by 1,405 · see citing works
Structure-based design of prefusion-stabilized SARS-CoV-2 spikes
Hsieh, C.-L., Goldsmith, J. A., Schaub, J. M., DiVenere, A. M., Kuo, H.-C., Javanmardi, K., Le, K. C., Wrapp, D., Lee, A. G., Liu, Y., et al. (2020) · Science · doi:10.1126/science.abd0826 · Cited by 1,303 · see citing works
A human neutralizing antibody targets the receptor-binding site of SARS-CoV-2
Shi, R., Shan, C., Duan, X., Chen, Z., Liu, P., Song, J., Song, T., Bi, X., Han, C., Wu, L., et al. (2020) · Nature · doi:10.1038/s41586-020-2381-y · Cited by 1,286 · see citing works
Chen, S., McMullan, G., Faruqi, A. R., Murshudov, G. N., Short, J. M., Scheres, S. H. W., & Henderson, R. A. (2013) · Ultramicroscopy · doi:10.1016/j.ultramic.2013.06.004 · Cited by 1,005 · see citing works
Wu, Y., Wang, F., Shen, C., Peng, W., Li, D., Zhao, C., Li, Z., Li, S., Bi, Y., Yang, Y., et al. (2020) · Science · doi:10.1126/science.abc2241 · Cited by 955 · see citing works
A Bayesian approach to beam-induced motion correction in cryo-EM single-particle analysis
Zivanov, J., Nakane, T., & Scheres, S. H. W. (2018) · IUCrJ · doi:10.1107/s205225251801463x · Cited by 947 · see citing works
Real-time cryo–EM data pre-processing with Warp
Tegunov, D., & Cramer, P. (2018) · Nature Methods · doi:10.1038/s41592-019-0580-y · Cited by 923 · see citing works
Accelerated cryo-EM structure determination with parallelisation using GPUs in RELION-2
Kimanius, D., Forsberg, B. O., Scheres, S. H. W., & Lindahl, E. R. (2016) · eLife · doi:10.7554/elife.18722 · Cited by 903 · see citing works
EMRinger: side chain–directed model and map validation for 3D cryo-electron microscopy
Barad, B. A., Echols, N., Wang, R. Y.-R., Cheng, Y., DiMaio, F., Adams, P. D., & Fraser, J. S. (2015) · Nature Methods · doi:10.1038/nmeth.3541 · Cited by 886 · see citing works
Casañal, A., Lohkamp, B., & Emsley, P. (2019) · Protein Science · doi:10.1002/pro.3791 · Cited by 812 · see citing works
Rapid COVID-19 vaccine development
Graham, B. S. (2020) · Science · doi:10.1126/science.abb8923 · Cited by 771 · see citing works
Structure-based Design of Prefusion-stabilized SARS-CoV-2 SpikesPreprint
Hsieh, C., Goldsmith, J., Schaub, J. M., et al. (2020) · bioRxiv · doi:10.1101/2020.05.30.125484 · Cited by 588 · see citing works
Principles for designing ideal protein structures
Koga, N., Tatsumi-Koga, R., Liu, G., Xiao, R., Acton, T. B., Montelione, G. T., & Baker, D. (2012) · Nature · doi:10.1038/nature11600 · Cited by 564 · see citing works
Self-citationDe novo design of potent and selective mimics of IL-2 and IL-15
Silva, D.-A., Yu, S., Ulge, U. Y., Spangler, J. B., Jude, K. M., Labão-Almeida, C., Ali, L. R., Quijano-Rubio, A., Ruterbusch, M., Leung, I., et al. (2019) · Nature · doi:10.1038/s41586-018-0830-7 · Cited by 531 · see citing works
Self-citationDNAWorks: an automated method for designing oligonucleotides for PCR-based gene synthesis
Hoover, D. M. (2002) · Nucleic Acids Research · doi:10.1093/nar/30.10.e43 · Cited by 521 · see citing works
Automated structure refinement of macromolecular assemblies from cryo-EM maps using Rosetta
Wang, R. Y.-R., Song, Y., Barad, B. A., Cheng, Y., Fraser, J. S., & DiMaio, F. (2016) · eLife · doi:10.7554/elife.17219 · Cited by 457 · see citing works
Massively parallel de novo protein design for targeted therapeutics
Chevalier, A., Silva, D.-A., Rocklin, G. J., Hicks, D. R., Vergara, R., Murapa, P., Bernard, S. M., Zhang, L., Lam, K.-H., Yao, G., et al. (2017) · Nature · doi:10.1038/nature23912 · Cited by 453 · see citing works
Self-citationRosettaRemodel: A Generalized Framework for Flexible Backbone Protein Design
Huang, P., Ban, Y. A., Richter, F. M., André, I., Vernon, R. M., Schief, W. R., & Baker, D. A. (2011) · PLoS ONE · doi:10.1371/journal.pone.0024109 · Cited by 373 · see citing works
Self-citationPrivateer: software for the conformational validation of carbohydrate structures
Agirre, J., Iglesias‐Fernández, J., Rovira, C., Davies, G. J., Wilson, K. S., & Cowtan, K. D. (2015) · Nature Structural & Molecular Biology · doi:10.1038/nsmb.3115 · Cited by 373 · see citing works
De novo design of a fluorescence-activating β-barrel
Dou, J., Vorobieva, A. A., Sheffler, W., Doyle, L. A., Park, H., Bick, M. J., Mao, B., Foight, G. W., Lee, M. Y., Gagnon, L. A., et al. (2018) · Nature · doi:10.1038/s41586-018-0509-0 · Cited by 351 · see citing works
Self-citationDiMaio, F., Song, Y., Li, X., Brunner, M. J., Xu, C., Conticello, V. P., Egelman, E. H., Marlovits, T. C., Cheng, Y., & Baker, D. A. (2015) · Nature Methods · doi:10.1038/nmeth.3286 · Cited by 309 · see citing works
Self-citationFc receptors in antibody‐dependent enhancement of viral infections
Taylor, A., Foo, S., Bruzzone, R., Dinh, L. V., King, N. J. C., & Mahalingam, S. (2015) · Immunological Reviews · doi:10.1111/imr.12367 · Cited by 251 · see citing works
A Potently Neutralizing Antibody Protects Mice against SARS-CoV-2 Infection
Alsoussi, W. B., Turner, J. S., Case, J. B., Zhao, H., Schmitz, A. J., Zhou, J. Q., Chen, R. E., Lei, T., Rizk, A. A., McIntire, K. M., et al. (2020) · The Journal of Immunology · doi:10.4049/jimmunol.2000583 · Cited by 181 · see citing works
Self-citationAutomatically Fixing Errors in Glycoprotein Structures with Rosetta
Frenz, B., Rämisch, S., Borst, A. J., Walls, A. C., Adolf‐Bryfogle, J., Schief, W. R., Veesler, D., & DiMaio, F. (2018) · Structure · doi:10.1016/j.str.2018.09.006 · Cited by 104 · see citing works
Self-citationWinarski, K. L., Tang, J., Klenow, L., et al. (2019) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1821317116 · Cited by 85 · see citing works
Structural and functional analysis of a potent sarbecovirus neutralizing antibody
Pinto, D., Park, Y., Beltramello, M., Walls, A. C., Tortorici, M. A., Bianchi, S., Jaconi, S., Culap, K., Zatta, F., Marco, A. D., et al. (2020) · Worldwide Protein Data Bank · doi:10.2210/pdb6ws6/pdb · Cited by 84 · see citing works
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Chen, R. E., Zhang, X., Case, J. B., Winkler, E. S., Liu, Y., VanBlargan, L. A., Liu, J., Errico, J. M., Xie, X., Suryadevara, N., et al. (2021) · Nature Medicine · doi:10.1038/s41591-021-01294-w · Cited by 881 · see citing works
Self-citationDesign of protein-binding proteins from the target structure alone
Cao, L., Coventry, B., Goreshnik, I., Huang, B., Sheffler, W., Park, J. S., Jude, K. M., Marković, I., Kadam, R. U., Verschueren, K. H. G., et al. (2022) · Nature · doi:10.1038/s41586-022-04654-9 · Cited by 577 · see citing works
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Quijano-Rubio, A., Yeh, H.-W., Park, J., Lee, H., Langan, R. A., Boyken, S. E., Lajoie, M. J., Cao, L., Chow, C. M., Miranda, M. C., et al. (2021) · Nature · doi:10.1038/s41586-021-03258-z · Cited by 260 · see citing works
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Zahradník, J., Marciano, S., Shemesh, M., Zoler, E., Chiaravalli, J., Meyer, B., Rudich, Y., Dym, O., Elad, N., & Schreiber, G. (2021) · doi:10.1101/2021.01.06.425392 · Cited by 458 · see citing works
Case, J. B., Chen, R. E., Cao, L., Ying, B., Winkler, E. S., Johnson, M., Goreshnik, I., Pham, M. N., Shrihari, S., Kafai, N. M., et al. (2021) · Cell Host & Microbe · doi:10.1016/j.chom.2021.06.008 · Cited by 73 · see citing works
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- Authors
- Cao, L., Goreshnik, I., Coventry, B., Case, J. B., Miller, L., Kozodoy, L., Chen, R. E., Carter, L., Walls, A. C., Park, Y.-J., Strauch, E.-M., Stewart, L., Diamond, M. S., Veesler, D., & Baker, D.
- Affiliations
- University of Washington (US)
- Washington University in St. Louis (US)
- University of Georgia (US)
- Howard Hughes Medical Institute (US)
- Corresponding author
- Baker, David
- ORCID
- Venue
- Science
- Published
- 2020-10-23
- Volume
- 370
- Issue
- 6515
- Pages
- 426-431
- ISSN
- 0036-8075 (ISSN-L)
- 1095-9203
- PMC
- PMC7857403
- OpenAlex
- W3084236163
- Cited by
- 742
- References
- 42
- Citations by year
- 2026: 72 · 2025: 92 · 2024: 105 · 2023: 114 · 2022: 138 · 2021: 183 · 2020: 37
- FWCI
- 15.46
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Science (publishedVersion, cc-by)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- PubMed Central (submittedVersion)
- Funders
- National Institutes of Health (5r01ai140245-05, 1s10od023476-01)
- National Institute of General Medical Sciences (R01GM120553)
- National Institute of Allergy and Infectious Diseases (HHSN272201700059C, R01-AI140245)
- Topics
- Health Sciences › Medicine › Infectious Diseases › SARS-CoV-2 and COVID-19 Research
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › vaccines and immunoinformatics approaches
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
- Keywords
- SARS-CoV-2, miniproteins, de novo protein design, spike protein, ACE2 receptor, antiviral agents, viral entry inhibition, intranasal drug delivery, Vero E6 cells
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