计算生物学
反应性
信使核糖核酸
生物
退化(生物学)
编码
序列(生物学)
计算机科学
生物信息学
遗传学
基因
免疫原性
抗原
作者
Yoo-Ah Kim,Kambiz Mousavi,Aliakbar Khalili Yazdi,Magda Zwierzyna,Marco Cardinali,Dillion M. Fox,Thomas Peel,Jeff Coller,Kunal Aggarwal,Giulietta Maruggi
出处
期刊:Vaccine
[Elsevier]
日期:2023-07-01
标识
DOI:10.1016/j.vaccine.2023.07.024
摘要
mRNA technology has emerged as a successful vaccine platform that offered a swift response to the COVID-19 pandemic. Accumulating evidence shows that vaccine efficacy, thermostability, and other important properties, are largely impacted by intrinsic properties of the mRNA molecule, such as RNA sequence and structure, both of which can be optimized. Designing mRNA sequence for vaccines presents a combinatorial problem due to an extremely large selection space. For instance, due to the degeneracy of the genetic code, there are over 10632 possible mRNA sequences that could encode the spike protein, the COVID-19 vaccines’ target. Moreover, designing different elements of the mRNA sequence simultaneously against multiple objectives such as translational efficiency, reduced reactogenicity, and improved stability requires an efficient and sophisticated optimization strategy. Recently, there has been a growing interest in utilizing computational tools to redesign mRNA sequences to improve vaccine characteristics and expedite discovery timelines. In this review, we explore important biophysical features of mRNA to be considered for vaccine design and discuss how computational approaches can be applied to rapidly design mRNA sequences with desirable characteristics.
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