Hongjun Bai, PhD

My research interests focus on developing new vaccines and vaccine techniques for pressing global health needs and optimizing current ones for greater impact. As a structural bioinformatics scientist, my early research focus on study structural determinants in protein-protein interactions and design immune modulator, including protein and peptide, targeting innate immune system proteins.

A key area of my recent research focuses on how broadly neutralizing antibodies (bnAbs) recognize and interact with the HIV‑1 envelope (Env). We discovered that the breadth of the most potent bnAbs depends more on how they engage their epitopes than on the simple conservation of those epitope sites. Building on this, we developed an “epitope distance” metric to capture how sequence variation is perceived structurally by antibodies. Notably, in the AMP trials, this structurally informed epitope distance performed as well as the traditional—yet resource‑intensive—IC80 neutralization biomarker in predicting prevention efficacy, and it outperformed models based solely on linear Env sequence features.

Another direction of my work brings together antibody-antigen interaction principles with advanced AI technologies to design improved vaccine antigens and protein nanoparticles. For example, I have engineered HIV‑1 Env hypervariable loops with enhanced antigenicity, and I am now applying AI‑driven strategies to optimize self‑assembling protein nanoparticles. These efforts aim to expand nanoparticle capabilities—such as improving assembly efficiency and exploring new ways to incorporate adjuvant‑like properties—to drive stronger immune responses to displayed antigens.