AntigenBoost: enhanced mRNA-based antigen expression through rational amino acid substitution
Year: 2024
Type: article
Abstract: Messenger RNA (mRNA) vaccines represent a groundbreaking advancement in immunology and public health, particularly highlighted by their role in combating the COVID-19 pandemic. Optimizing mRNA-based antigen expression is a crucial focus in this emerging industry. We have developed a bioinformatics tool named AntigenBoost to address the challenge posed by destabilizing dipeptides that hinder ribosomal translation. AntigenBoost identifies these dipeptides within specific antigens and provides a range of potential amino acid substitution strategies using a two-dimensional scoring system. Through a combination of bioinformatics analysis and experimental validation, we significantly enhanced the in vitro expression of mRNA-derived Respiratory Syncytial Virus fusion glycoprotein and Influenza A Hemagglutinin antigen. Notably, a single amino acid substitution improved the immune response in mice, underscoring the effectiveness of AntigenBoost in mRNA vaccine design.
Source: Briefings in Bioinformatics
DOI: 10.1093/bib/bbae468
Authors: Yumiao Gao, Siran Zhu, Huichun Li, Xueting Hao, Wen Chen, Deng Pan, Zhikang Qian
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $3,922
OpenAlex ID: W4403380435