A paradigm shift in simulating affinity maturation to elicit broadly neutralizing antibodies

模拟亲和力成熟以诱导广谱中和抗体的范式转变

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Abstract

Broadly neutralizing antibodies (bnAbs) offer a promising route to protect against rapidly evolving pathogens such as HIV, influenza, and SARS-CoV-2, yet eliciting them through vaccination remains a significant challenge. A key to this problem lies in understanding antibody affinity maturation (AM), the evolutionary process within germinal centers (GCs) that shapes the B cell and thus antibody response. Traditionally, AM has been viewed as favoring the selection of B cells with the highest-affinity B cell receptors (BCRs) through competitive interplays. However, emerging evidence suggests that GCs are more permissive, allowing B cells with a broad range of affinities to persist, thereby promoting clonal diversity and enabling the rare emergence of bnAbs. This review reassesses affinity-based selection models and proposes a new paradigm that integrates multifactorial processes, including stochastic B cell decisions within GC dynamics, antigen extraction efficiency influenced by probabilistic bond rupture, and avidity-driven BCR binding alterations and representations on multivalent antigens. We highlight how advanced AM simulations that move beyond affinity as the sole determinant provide a more realistic and predictive representation of AM, marking a major step forward in developing strategies to promote effective immune responses against highly mutable, complex antigens.

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