NeoDesign: a computational tool for optimal selection of polyvalent neoantigen combinations

Abstract Motivation 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 l...

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Bibliographic Details
Published in:	Bioinformatics (Oxford, England) Vol. 40; no. 10
Main Authors:	Yu, Wenqian, Yu, Hongwu, Zhao, Jingjing, Zhang, Hena, Ke, Kalam, Hu, Zhixiang, Huang, Shenglin
Format:	Journal Article
Language:	English
Published:	England Oxford University Press 01-10-2024 Oxford Publishing Limited (England)
Subjects:	Amino acid sequence Antigens, Neoplasm - genetics Antigens, Neoplasm - immunology Applications Note Availability Cancer Vaccines - immunology Codons Computational Biology - methods Computer applications Design Gene expression Gene sequencing Humans Immunogenicity Immunotherapy Immunotherapy - methods mRNA stability mRNA vaccines Neoantigens Neoplasms - immunology Neoplasms - therapy Protein structure Proteins RNA, Messenger - genetics Software Tumors Vaccine development Vaccines
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Summary:	Abstract Motivation 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. Results 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. Availability and implementation NeoDesign is freely available on https://github.com/HuangLab-Fudan/neoDesign and https://figshare.com/projects/NeoDesign/221704.
Bibliography:	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23
ISSN:	1367-4811 1367-4803 1367-4811
DOI:	10.1093/bioinformatics/btae585