广AMP-GPT:人工智能驱动的广谱抗菌的生成,用于对抗多药耐药ESKAPE病原体
Yanru Li1,2, Xianghan Xu1,3, Xiaohui Zhang4
1Sanya Institute of Nanjing Agricultural University, Nanjing Agricultural University, Sanya, China.
Gut microbes
|June 26, 2025
概括
研究人员开发了BroadAMP-GPT,这是一个用于发现抗微生物 (AMP) 的AI平台. 这种工具可以快速识别强效的,广泛的AMP,如AMP_S13,以对抗抗菌素耐药性和感染.
科学领域:
- 生物技术是生物技术.
- 计算生物学 计算生物学
- 药物发现 药物发现 药物发现
背景情况:
- 抗微生物 (AMP) 为日益严重的抗微生物药物耐药性危机提供了一个有希望的解决方案.
- 传统的AMP设计方法往往是低效和耗时的.
- 迫切需要快速有效的方法来发现新的AMP.
研究的目的:
- 开发和验证BroadAMP-GPT,这是一个用于加速AMP发现的集成计算-实验框架.
- 识别具有强效,广泛的AMP,具有理想的稳定性和低毒性.
- 提供一种可扩展的策略,用于对抗多抗药性病原体.
主要方法:
- 使用BroadAMP-GPT.AI驱动的AMP候选人的生成.
- 多层次选,包括计算和实验验证.
- 在体外和体内测试有前途的AMP候选人对ESKAPE病原体和感染模型.
主要成果:
- 广AMP-GPT成功生成AMP候选物,其中57%显示对ESKAPE病原体有强效.
- 在各种生理条件 (pH,蛋白质分解,温度) 中,AMP_S13表现出异常稳定性.
- 在感染和伤口愈合模型中,AMP_S13表现出最小的细胞毒性,低血解活性和强大的体内疗效.
结论:
- BroadAMP-GPT是一种转型工具,可以加速发现稳定,广谱,低毒性的AMP.
- 该框架提供了一种可扩展的方法来应对多药耐药病原体的威胁.
- 这种由人工智能驱动的平台显著提高了抗微生物药物发现的效率.
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