利用人工智能用于抗微生物发现和优化
Ashley E Clements1, Maureen R Fieldhouse1, Allison S Walker2
1Department of Chemistry, Center for Structural Biology, Vanderbilt Institute of Chemical Biology, Vanderbilt University, Nashville, TN, USA.
Current opinion in microbiology
|February 26, 2026
概括
人工智能 (AI) 加快了对抗抗菌素耐药性的新抗生素的发现. 人工智能有助于识别,设计和优化抗微生物和小分子,克服传统药物发现挑战.
科学领域:
- 微生物学 微生物学
- 计算化学计算化学
- 药物发现 药物发现 药物发现
背景情况:
- 抗生素耐药性病原体的日益增长需要新的抗生素发现方法.
- 传统的药物发现管道在速度和效率方面面临重大挑战.
- 人工智能 (AI) 为识别和设计新的抗菌剂提供了变革性的潜力.
研究的目的:
- 审查人工智能驱动的抗微生物发现和设计方面的进展.
- 探索AI如何克服传统抗生素开发的局限性.
- 突出AI在识别和优化生物活性分子中的作用.
主要方法:
- 人工智能驱动的基因组挖掘用于识别和优先考虑生物合成基因集群.
- 先进的AI模型用于预测分子性质和结合相互作用.
- 在设计新型抗微生物结构 (小分子和) 中的人工智能应用.
主要成果:
- 人工智能显著加快了潜在抗生素候选者的识别和优化.
- 人工智能有助于预测分子性质和结合效率.
- 人工智能使新型抗微生物小分子和的设计成为可能.
结论:
- 人工智能是一个强大的工具,可以解决对抗耐药病原体的新抗生素的迫切需求.
- 人工智能驱动的方法提高了抗微生物药物发现的效率和范围.
- 进一步开发和应用人工智能对于打击抗菌素耐药性危机至关重要.
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