Growing Glycans in Rosetta: Accurate de novo glycan modeling, density fitting, and rational sequon design.

Carbohydrates and glycoproteins modulate key biological functions. However, experimental structure determination of sugar polymers is notoriously difficult. Computational approaches can aid in carbohydrate structure prediction, structure determination, and design. In this work, we developed a glycan-modeling algorithm, GlycanTreeModeler, that computationally builds glycans layer-by-layer, using adaptive kernel density estimates (KDE) of common glycan conformations derived from data in the Protein Data Bank (PDB) and from quantum mechanics (QM) calculations. GlycanTreeModeler was benchmarked on a test set of glycan structures of varying lengths, or "trees". Structures predicted by GlycanTreeModeler agreed with native structures at high accuracy for both de novo modeling and experimental density-guided building. We employed these tools to design de novo glycan trees into a protein nanoparticle vaccine to shield regions of the scaffold from antibody recognition, and experimentally verified shielding. This work will inform glycoprotein model prediction, glycan masking, and further aid computational methods in experimental structure determination and refinement.

Heterologous prime-boost vaccination drives early maturation of HIV broadly neutralizing antibody precursors in humanized mice.

A protective HIV vaccine will likely need to induce broadly neutralizing antibodies (bnAbs). Vaccination with the germline-targeting immunogen eOD-GT8 60mer adjuvanted with AS01B was found to induce VRC01-class bnAb precursors in 97% of vaccine recipients in the IAVI G001 phase 1 clinical trial; however, heterologous boost immunizations with antigens more similar to the native glycoprotein will be required to induce bnAbs. Therefore, we designed core-g28v2 60mer, a nanoparticle immunogen to be used as a first boost after eOD-GT8 60mer priming. We found, using a humanized mouse model approximating human conditions of VRC01-class precursor B cell diversity, affinity, and frequency, that both protein- and mRNA-based heterologous prime-boost regimens induced VRC01-class antibodies that gained key mutations and bound to near-native HIV envelope trimers lacking the N276 glycan. We further showed that VRC01-class antibodies induced by mRNA-based regimens could neutralize pseudoviruses lacking the N276 glycan. These results demonstrated that heterologous boosting can drive maturation toward VRC01-class bnAb development and supported the initiation of the IAVI G002 phase 1 trial testing mRNA-encoded nanoparticle prime-boost regimens.

A generalized HIV vaccine design strategy for priming of broadly neutralizing antibody responses.

Vaccine induction of broadly neutralizing antibodies (bnAbs) to HIV remains a major challenge. Germline-targeting immunogens hold promise for initiating the induction of certain bnAb classes; yet for most bnAbs, a strong dependence on antibody heavy chain complementarity-determining region 3 (HCDR3) is a major barrier. Exploiting ultradeep human antibody sequencing data, we identified a diverse set of potential antibody precursors for a bnAb with dominant HCDR3 contacts. We then developed HIV envelope trimer-based immunogens that primed responses from rare bnAb-precursor B cells in a mouse model and bound a range of potential bnAb-precursor human naïve B cells in ex vivo screens. Our repertoire-guided germline-targeting approach provides a framework for priming the induction of many HIV bnAbs and could be applied to most HCDR3-dominant antibodies from other pathogens.