As a groundbreaking advancement in vaccinology, messenger RNA (mRNA) vaccines have transformed the field by offering rapid, flexible, and scalable solutions for combating infectious diseases. However, the efficacy, stability, and immunogenicity of mRNA vaccines are highly dependent on the optimization of their sequences. Recent progress in synthetic biology and computational methods has enabled the optimization of mRNA sequences to enhance their properties, holding the promise to provide deeper insights into the design principles of effective mRNA vaccines. However, it remains a major challenge to determine how to best optimize mRNA sequences for diverse biological contexts and therapeutic applications. In this review, we provide an in-depth analysis of the current advancements in optimizing mRNA vaccine sequences, put forward a comprehensive overview of the latest computational and biological approaches in this field, with a particular focus on the biological mechanisms underlying mRNA translation efficiency and stability, highlighting several quantitative indicators that may affect vaccines’ performance, and summarize some methods to optimize mRNA vaccine by algorithms. We also propose the limitations of current models and the need for further research to address the complexity of biological systems.
Wang et al. (Sun,) studied this question.