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人工设计及深度学习在抗菌肽改造策略上的研究进展

  • 徐浩然 ,
  • 毕重朋 ,
  • 王家俊 ,
  • 单安山 ,
  • 冯兴军
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  • (东北农业大学 动物科学技术学院,黑龙江 哈尔滨,150030)
第一作者: 博士研究生(毕重朋高级实验师和王家俊教授为共同通信作者,E-mail:bnm0722@163.com;wjj1989@neau.edu.cn)

收稿日期: 2025-01-20

  修回日期: 2025-02-21

  网络出版日期: 2025-08-04

基金资助

黑龙江省重点研发计划项目(2024ZXDXB58)

Advances in artificial design and deep learning for antimicrobial peptide modification strategies

  • XU Haoran ,
  • BI Chongpeng ,
  • WANG Jiajun ,
  • SHAN Anshan ,
  • FENG Xingjun
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  • (College of Animal Science and Technology, Northeast Agricultural University, Harbin 150030, China)

Received date: 2025-01-20

  Revised date: 2025-02-21

  Online published: 2025-08-04

摘要

近年来,多重耐药病原体引发的感染显著增加,抗生素耐药性已成为全球公共卫生领域的重大挑战。抗菌肽因其独特的作用机制,被认为是对抗抗生素耐药性的潜在解决方案。然而,其在临床应用中仍面临稳定性差、活性不足及高生产成本等障碍。为此,文中总结了多种改造策略,包括结构优化、靶向设计、活性增强以及生产工艺改进。同时,深度学习技术的引入,为抗菌肽序列的设计与优化提供了高效的新途径,通过预测抗菌活性和优化参数显著提升研发效率,为抗菌肽的开发与应用带来了新的希望。

本文引用格式

徐浩然 , 毕重朋 , 王家俊 , 单安山 , 冯兴军 . 人工设计及深度学习在抗菌肽改造策略上的研究进展[J]. 食品与发酵工业, 2025 , 51(13) : 362 -368 . DOI: 10.13995/j.cnki.11-1802/ts.042190

Abstract

In recent years, infections caused by multi-drug-resistant pathogens have escalated, posing a significant global public health threat.Antimicrobial peptides (AMPs) offer a promising alternative to combat antibiotic resistance due to their unique mechanisms of action.However, their clinical application is hindered by challenges, such as poor stability, limited activity, and high production costs.Various strategies have been explored to improve AMPs, including structural optimization, target-specific design, activity improvement, and refining production processes.Additionally, the integration of deep learning techniques has introduced efficient approaches for the design and optimization of AMP sequences.By predicting antimicrobial activity and optimizing key parameters, these technologies significantly improve research and development efficiency, providing new opportunities for the advancement and clinical applications of antimicrobial peptides.

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