Back

Trivalent cocktail of de novo designed immunogens enables the robust induction and focusing of functional antibodies in vivo

Sesterhenn, F.; Yang, C.; Cramer, J.; Bonet, J.; Wen, X.; Abriata, L.; Kucharska, I.; Chiang, C.-I.; Wang, Y.; Castoro, G.; Vollers, S.; Galloux, M.; Charles-Adrien, R.; Rosset, S.; Corthesy, P.; Georgeon, S.; Villard, M.; Descamps, D.; Rameix-Welti, M.-A.; Mas, V.; Ervin, S.; Eleouet, J.-f.; Riffault, S.; Bates, J.; Julien, J.-P.; Li, Y.; Jardetzky, T. S.; Krey, T.; Correia, B.

2019-06-28 bioengineering
10.1101/685867 bioRxiv
Show 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 novel protein design algorithm, termed TopoBuilder, with which we engineered epitope-focused immunogens displaying complex structural motifs. Both in mice and non-human primates, cocktails of three de novo designed immunogens induced robust neutralizing responses against the respiratory syncytial virus. Furthermore, the immunogens refocused pre-existing antibody responses towards defined neutralization epitopes. Overall, our de novo design approach opens the possibility of targeting specific epitopes for vaccine and therapeutic antibody development, and more generally will be applicable to design de novo proteins displaying complex functional motifs.

Matching journals

The top 2 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.