Target prediction approach to inhibit SARS-CoV-2 replication based on metabolic difference analysis(PDF)
《中国医学物理学杂志》[ISSN:1005-202X/CN:44-1351/R]
- Issue:
- 2023年第12期
- Page:
- 1577-1584
- Research Field:
- 其他（激光医学等）
- Publishing date:
Info
- Title:
- Target prediction approach to inhibit SARS-CoV-2 replication based on metabolic difference analysis
- Author(s):
- QI Yupeng; ZHAO Yanlong; ZHENG Haoran
- School of Computer Science and Technology, University of Science and Technology of China, Hefei 230027, China
- Keywords:
- Keywords: COVID-19 SARS-CoV-2 metabolic difference analysis target prediction
- PACS:
- R318
- DOI:
- DOI:10.3969/j.issn.1005-202X.2023.12.019
- Abstract:
- Abstract: A target prediction approach to inhibit SARS-CoV-2 replication through metabolic difference analysis is presented. The approach is based on gene expression data from lung host cells, reconstructs a network model of the parts of the host cell metabolic system that are reprogrammed after viral invasion, and identifies candidate targets using single-gene knockout and cytotoxicity test. The robustness of antiviral targets against multiple currently known variants of SARS-CoV-2 is also analyzed. The results indicate that D-alanine is a key metabolite affecting SARS-CoV-2 replication and is applicable to all current SARS-CoV-2 variants. The gene regulating D-alanine (PLPBP) is the main gene target. The proposed approach is applicable to the existing viruses and host cells, providing new ideas for viral disease management.
Last Update: 2023-12-27