Design of immunogens for eliciting antibody responses that may protect against SARS-CoV-2 variants.

ABSTRACT: The rise of SARS-CoV-2 variants and the history of outbreaks caused by zoonotic coronaviruses point to the need for next-generation vaccines that confer protection against variant strains. Here, we combined analyses of diverse sequences and structures of coronavirus spikes with data from deep mutational scanning to design SARS-CoV-2 variant antigens containing the most significant mutations that may emerge. We trained a neural network to predict RBD expression and ACE2 binding from sequence, which allowed us to determine that these antigens are stable and bind to ACE2. Thus, they represent viable variants. We then used a computational model of affinity maturation (AM) to study the antibody response to immunization with different combinations of the designed antigens. The results suggest th

SUBMITTER: Wang E 

PROVIDER: S-EPMC9536555 | biostudies-literature | 2022 Sep

REPOSITORIES: biostudies-literature