Department of Integrative Oncology, Fudan University Shanghai Cancer Center, and Shanghai Key Laboratory of Medical Epigenetics, Institutes of Biomedical Sciences, Fudan University, Shanghai 200032, China.
Department of Oncology, Shanghai Medical College, Fudan University, Shanghai 200032, China.
Bioinformatics. 2024 Oct 1;40(10). doi: 10.1093/bioinformatics/btae585.
Tumor polyvalent neoantigen mRNA vaccines are gaining prominence in immunotherapy. The design of sequences in vaccine development is crucial for enhancing both the immunogenicity and safety of vaccines. However, a major challenge lies in selecting the optimal sequences from the large pools generated by multiple peptide combinations and synonymous codons.
We introduce NeoDesign, a computational tool designed to tackle the challenge of sequence design. NeoDesign comprises four modules: Library Construction, Optimal Path Filtering, Linker Addition, and λ-Evaluation. It aims to identify the optimal protein sequence for tumor polyvalent neoantigen vaccines by minimizing linker usage, avoiding unexpected neoantigens and functional domains, and simplifying the structure. It also provides a preference scheme to balance mRNA stability and protein expression when designing mRNA sequences for the optimal protein sequence. This tool can potentially improve the sequence design of tumor polyvalent neoantigen mRNA vaccines, thereby significantly advancing immunotherapy strategies.
NeoDesign is freely available on https://github.com/HuangLab-Fudan/neoDesign and https://figshare.com/projects/NeoDesign/221704.
肿瘤多价新抗原 mRNA 疫苗在免疫疗法中越来越受到关注。在疫苗开发中设计序列对于提高疫苗的免疫原性和安全性至关重要。然而，一个主要的挑战在于从多个肽组合和同义密码子产生的大量库中选择最佳序列。
我们引入了 NeoDesign，这是一种旨在解决序列设计挑战的计算工具。NeoDesign 由四个模块组成：文库构建、最优路径过滤、接头添加和 λ-评估。它旨在通过最小化接头使用、避免意外的新抗原和功能域以及简化结构，来确定肿瘤多价新抗原疫苗的最佳蛋白质序列。当为最优蛋白质序列设计 mRNA 序列时，它还提供了一个偏好方案来平衡 mRNA 稳定性和蛋白质表达。该工具有可能改进肿瘤多价新抗原 mRNA 疫苗的序列设计，从而显著推进免疫疗法策略。
NeoDesign 可在 https://github.com/HuangLab-Fudan/neoDesign 和 https://figshare.com/projects/NeoDesign/221704 上免费获得。
