Zhao Lanlan, Wang Yihui, Jiang Jun, Pan Hongwei, Wang Lijuan, Ma Shutao, Zhang Lei
Microbiome-X, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, China.
Department of Medicinal Chemistry, Key Laboratory of Chemical Biology (Ministry of Education), School of Pharmaceutical Sciences, Cheeloo College of Medicine Shandong University, Jinan, China.
Microbiol Spectr. 2025 Sep 2:e0150425. doi: 10.1128/spectrum.01504-25.
Novel antimicrobial agents are urgently needed to combat the antibiotic-resistance crisis, particularly in the face of multidrug-resistant (MDR) pathogens like carbapenem-resistant (CRAB) and methicillin-resistant (MRSA). In this study, we present an approach that combines generative large language model with sequence alignment to identify promising antimicrobial peptides. With this strategy, we rapidly identified five novel encrypted peptides based on a generated template, demonstrating significant antimicrobial activity against a broad spectrum of clinical MDR pathogens. Among them, PL-15 stood out as a potent, broad-spectrum AMP with comparable therapeutic efficacy to polymyxin B against CRAB infections . Mechanistic investigations revealed that PL-15 exerts its bactericidal effects by disrupting both the outer and cytoplasmic membranes, causing membrane depolarization, elevating intracellular reactive oxygen species (ROS) levels, and ultimately leading to rapid bacterial cell death. Additionally, PL-15 demonstrated remarkable antibiofilm activity, inhibiting biofilm formation and eradicating pre-existing biofilms, further reducing the risk of resistance development. This work highlights the potential of using generative model combined with sequence alignment to accelerate the discovery of novel analogs with enhanced properties.IMPORTANCEThe rise of multidrug-resistant pathogens, such as carbapenem-resistant and methicillin-resistant , poses a severe threat to public health, making the search for novel antimicrobial agents a critical priority. In this study, we present an innovative approach combining generative large language models and sequence alignment to identify promising antimicrobial peptides. This method allowed for the rapid discovery of five encrypted peptides with strong antimicrobial activity against a range of multidrug-resistant pathogens. Among them, PL-15 showed remarkable efficacy, comparable to polymyxin B, and exhibited potent antibiofilm properties, making it a strong candidate for further development. By providing a novel approach to discovering antimicrobial agents, this work presents a promising solution to the escalating crisis of antibiotic resistance.
迫切需要新型抗菌剂来应对抗生素耐药性危机，尤其是面对耐碳青霉烯类（CRAB）和耐甲氧西林（MRSA）等多重耐药（MDR）病原体时。在本研究中，我们提出了一种将生成式大语言模型与序列比对相结合的方法，以识别有前景的抗菌肽。通过这种策略，我们基于生成的模板快速鉴定出五种新型加密肽，它们对多种临床多重耐药病原体具有显著的抗菌活性。其中，PL-15脱颖而出，是一种强效的广谱抗菌肽，在治疗CRAB感染方面具有与多粘菌素B相当的疗效。机制研究表明，PL-15通过破坏外膜和细胞质膜发挥杀菌作用，导致膜去极化，提高细胞内活性氧（ROS）水平，最终导致细菌细胞迅速死亡。此外，PL-15表现出显著的抗生物膜活性，抑制生物膜形成并根除已形成的生物膜，进一步降低了耐药性产生的风险。这项工作突出了使用生成模型与序列比对相结合来加速发现具有增强特性的新型类似物的潜力。重要性耐碳青霉烯类和耐甲氧西林等多重耐药病原体的出现对公众健康构成了严重威胁，因此寻找新型抗菌剂成为一项至关重要的优先任务。在本研究中，我们提出了一种创新方法，将生成式大语言模型与序列比对相结合，以识别有前景的抗菌肽。该方法能够快速发现五种对多种多重耐药病原体具有强大抗菌活性的加密肽。其中，PL-15显示出与多粘菌素B相当的显著疗效，并表现出强大的抗生物膜特性，使其成为进一步开发的有力候选者。通过提供一种发现抗菌剂的新方法，这项工作为不断升级的抗生素耐药性危机提供了一个有前景的解决方案。
