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Induction of Potent Neutralizing Antibody Responses by a Designed Protein Nanoparticle Vaccine for Respiratory Syncytial Virus
Open accessAbstract
Respiratory syncytial virus (RSV) is a worldwide public health concern for which no vaccine is available. Elucidation of the prefusion structure of the RSV F glycoprotein and its identification as the main target of neutralizing antibodies have provided new opportunities for development of an effective vaccine. Here, we describe the structure-based design of a self-assembling protein nanoparticle presenting a prefusion-stabilized variant of the F glycoprotein trimer (DS-Cav1) in a repetitive array on the nanoparticle exterior. The two-component nature of the nanoparticle scaffold enabled the production of highly ordered, monodisperse immunogens that display DS-Cav1 at controllable density. In mice and nonhuman primates, the full-valency nanoparticle immunogen displaying 20 DS-Cav1 trimers induced neutralizing antibody responses ∼10-fold higher than trimeric DS-Cav1. These results motivate continued development of this promising nanoparticle RSV vaccine candidate and establish computationally designed two-component nanoparticles as a robust and customizable platform for structure-based vaccine design.
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The PyMOL Molecular Graphics System
DeLano, W. L. (2002) · Medical Entomology and Zoology · Cited by 18,147
Lozano, R., Naghavi, M., Foreman, K., Lim, S., Shibuya, K., Aboyans, V., Abraham, J., Adair, T., Aggarwal, R., Ahn, S. Y., et al. (2012) · The Lancet · doi:10.1016/s0140-6736(12)61728-0 · Cited by 14,070
MotionCor2: anisotropic correction of beam-induced motion for improved cryo-electron microscopy
Zheng, S. Q., Palovcak, E., Armache, J.-P., Verba, K. A., Cheng, Y., & Agard, D. A. (2017) · Nature Methods · doi:10.1038/nmeth.4193 · Cited by 7,777
Protein Identification and Analysis Tools in the ExPASy Server
Wilkins, M. R., Gasteiger, E., Bairoch, A., Sanchez, J.-C., Williams, K. L., Appel, R. D., & Hochstrasser, D. F. (2003) · 2-D Proteome Analysis Protocols · doi:10.1385/1-59259-584-7:531 · Cited by 6,155
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
The Proteomics Protocols Handbook
(2005) · Humana Press eBooks · doi:10.1385/1592598900 · Cited by 3,538
Gctf: Real-time CTF determination and correction
Zhang, K. (2016) · Journal of Structural Biology · doi:10.1016/j.jsb.2015.11.003 · Cited by 3,537
EMAN2: An extensible image processing suite for electron microscopy
Tang, G., Peng, L., Baldwin, P. R., Mann, D. S., Jiang, W., Rees, I., & Ludtke, S. J. (2007) · Journal of Structural Biology · doi:10.1016/j.jsb.2006.05.009 · Cited by 2,994
Rosenthal, P. B., & Henderson, R. (2003) · Journal of Molecular Biology · doi:10.1016/j.jmb.2003.07.013 · Cited by 2,416
The Burden of Respiratory Syncytial Virus Infection in Young Children
Hall, C. B., Weinberg, G. A., Iwane, M. K., Blumkin, A. K., Edwards, K. M., Staat, M. A., Auinger, P., Griffin, M. R., Poehling, K. A., Erdman, D., et al. (2009) · New England Journal of Medicine · doi:10.1056/nejmoa0804877 · Cited by 2,246
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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
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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
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Zhao, T., Cai, Y., Jiang, Y., He, X., Wei, Y., Yu, Y., & Tian, X. (2023) · Signal Transduction and Targeted Therapy · doi:10.1038/s41392-023-01557-7 · Cited by 1,020
Metadata
- Authors
- Marcandalli, J., Fiala, B., Ols, S., Perotti, M., de van der Schueren, W., Snijder, J., Hodge, E., Benhaim, M., Ravichandran, R., Carter, L., Sheffler, W., Brunner, L., Lawrenz, M., Dubois, P., Lanzavecchia, A., Sallusto, F., Lee, K. K., Veesler, D., Correnti, C. E., Stewart, L. J., Baker, D., Loré, K., Perez, L., & King, N. P.
- Venue
- Cell
- Publisher
- Elsevier BV
- Published
- 2019-03
- Volume
- 176
- Issue
- 6
- Pages
- 1420-1431.e17
- ISSN
- 0092-8674 (ISSN-L)
- OpenAlex
- W2921646015
- Cited by
- 448
- References
- 70
- FWCI
- 37.76
- Type
- journal article
- Language
- en
- Open access
- hybrid
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- Marcandalli, J., Fiala, B., Ols, S., Perotti, M., de van der Schueren, W., Snijder, J., Hodge, E., Benhaim, M., Ravichandran, R., Carter, L., Sheffler, W., Brunner, L., Lawrenz, M., Dubois, P., Lanzavecchia, A., Sallusto, F., Lee, K. K., Veesler, D., Correnti, C. E., . . . King, N. P. (2019). Induction of Potent Neutralizing Antibody Responses by a Designed Protein Nanoparticle Vaccine for Respiratory Syncytial Virus. Cell. https://doi.org/10.1016/j.cell.2019.01.046
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
