| Literature DB >> 32409444 |
Fabian Sesterhenn1,2, Che Yang1,2, Jaume Bonet1,2, Johannes T Cramer3, Xiaolin Wen4, Yimeng Wang5, Chi-I Chiang5, Luciano A Abriata1,2, Iga Kucharska6,7, Giacomo Castoro3, Sabrina S Vollers1,2, Marie Galloux8, Elie Dheilly9, Stéphane Rosset1,2, Patricia Corthésy1,2, Sandrine Georgeon1,2, Mélanie Villard1,2, Charles-Adrien Richard8, Delphyne Descamps8, Teresa Delgado10, Elisa Oricchio9, Marie-Anne Rameix-Welti11, Vicente Más10, Sean Ervin12, Jean-François Eléouët8, Sabine Riffault8, John T Bates13, Jean-Philippe Julien6,7, Yuxing Li5,14, Theodore Jardetzky4, Thomas Krey3,15,16,17,18, Bruno E Correia19,2.
Abstract
De novo protein design has been successful in expanding the natural protein repertoire. However, most de novo proteins lack biological function, presenting a major methodological challenge. In vaccinology, the induction of precise antibody responses remains a cornerstone for next-generation vaccines. Here, we present a protein design algorithm called TopoBuilder, with which we engineered epitope-focused immunogens displaying complex structural motifs. In both mice and nonhuman primates, cocktails of three de novo-designed immunogens induced robust neutralizing responses against the respiratory syncytial virus. Furthermore, the immunogens refocused preexisting antibody responses toward defined neutralization epitopes. Overall, our design approach opens the possibility of targeting specific epitopes for the development of vaccines and therapeutic antibodies and, more generally, will be applicable to the design of de novo proteins displaying complex functional motifs.Entities:
Mesh：
Substances：
Year: 2020 PMID： 32409444 PMCID： PMC7391827 DOI： 10.1126/science.aay5051
Source DB: PubMed Journal: Science ISSN： 0036-8075 Impact factor: 63.714