SemVac: A reverse vaccinology pipeline that uses LLMs to predict vaccine target antigens from protein sequence data.

Key Points

• The research aims to establish a pipeline that predicts vaccine target antigens using large language models.
• Developed a reverse vaccinology pipeline called SemVac.
• Utilized large language models to analyze protein sequence data.
• Leveraged literature evidence from PaperBLAST to identify potential vaccine candidates.
• Identified several proteins as potential vaccine targets through LLM reasoning.
• Results are available in the llm_outputs directory for further analysis.