关键词:
抗菌肽
抗菌肽挖掘
天然抗菌肽
抗菌肽改造
机器学习
人工智能
深度学习
摘要:
随着抗生素的不合理使用,微生物耐药性问题日益严重,成为人类健康的巨大威胁。世界卫生组织(WHO)和美国传染病学会(IDSA)已将抗生素耐药问题列为威胁公共卫生的三大问题之一,迫切需要发现新型抗菌物质。抗菌肽是一类具有广谱抗菌活性、低耐药性倾向和多种作用机制的天然小分子,具有抗多重耐药菌、抗真菌、抗病毒、抗癌等多种生物活性,在治疗疾病方面有广阔的应用前景。由于氨基酸的多样性排列以及复杂的结构,发现、识别和筛选抗菌肽十分困难。计算机技术和人工智能的发展使抗菌肽的挖掘方法取得进展。本文旨在系统总结抗菌肽发现方法的研究进展,为新型方法的应用提供参考,促进抗菌肽领域的创新和发展。With the irrational use of antibiotics, the problem of microbial resistance has become increasingly serious and a great threat to human health. The World Health Organization (WHO) and the Infectious Diseases Society of America (IDSA) have listed antibiotic resistance as one of the three major problems threatening public health, and there is an urgent need to discover new antibacterial substances. Antimicrobial peptides (AMPs), a class of natural small molecules with broad-spectrum antimicrobial activity, low resistance potential, and diverse mechanisms of action, exhibit various biological activities such as anti-multidrug-resistant bacteria, antifungal, antiviral, and anticancer properties, showing promising potential in disease treatment. However, the discovery, identification, and screening of AMPs are challenging due to the diverse arrangements of amino acids and their complex structures. Advances in computer technology and artificial intelligence have facilitated progress in AMPs mining methods. This article aims to systematically summarize the research progress in AMPs discovery methods, provide references for the application of novel approaches, and promote innovation and development in the field of antimicrobial peptides.