Novel Computational Approaches in the Discovery and Identification of Bioactive Peptides: A Bioinformatics Perspective
文献类型： 外文期刊
作者： Li, Mengjiao 1 ; Chen, Mengting 1 ; Sun, Yizhen 1 ; Shi, Liu 1 ; Guo, Xiaojia 1 ; Chen, Sheng 1 ; Chen, Lang 1 ; Xiong, Guangquan 1 ; Sun, Weiqing 2 ; Gao, Ruichang 4 ; Ke, Liang 5 ; Wang, Lan 1 ; Wu, Wenjin 1 ;
作者机构： 1.Hubei Acad Agr Sci, Inst Agroprod Proc & Nucl Agr Technol, Key Lab Agr Prod Cold Chain Logist, Minist Agr & Rural Affairs, Wuhan 430064, Peoples R China
2.Yangtze Univ, Coll Food Sci & Technol, Jingzhou 10489, Peoples R China
3.Huazhong Agr Univ, Coll Food Sci & Technol, Wuhan 430070, Peoples R China
4.Jiangsu Univ, Sch Food & Biol Engn, Zhenjiang 212013, Peoples R China
5.Hubei Monopterus Albus Ind Technol Res Inst, Xiantao 433012, Peoples R China
关键词： Bioactive peptides; Mechanism; Computer simulation technology; Machine learning; Bioinformatics
期刊名称：JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY （ 影响因子：6.2； 五年影响因子：6.4 ）
ISSN： 0021-8561
年卷期： 2025 年 73 卷 22 期
页码：
收录情况： SCI
摘要： Bioactive peptides are protein molecules known for their specific biological functions, offering promising applications across various fields including medicine, food, and cosmetics. Traditional approaches to the investigation of bioactive peptides typically encompass extraction, separation, purification, identification, and experimental evaluation. However, these methodologies are frequently subject to human-related variables, which consequently lead to reduced efficiency and compromised accuracy. Bioinformatics techniques, including computer simulation screening, quantitative structure-activity relationship (QSAR) analysis, and machine learning, have emerged as powerful tools in the field of bioactive peptide research. These advanced methodologies not only enhance the efficiency of bioactive peptide screening but also provide valuable insights into the underlying mechanisms of action of these peptides. This review discusses the identification, analysis, and evaluation of bioactive peptides through innovative bioinformatics technology while also highlighting traditional techniques that have been developed and improved. This review provides robust theoretical support and valuable references for future research and applications involving bioactive peptides.
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