无细胞生物合成与深度学习相结合,加速了抗微生物的新开发
Amir Pandi1, David Adam2,3, Amir Zare2
1Department of Biochemistry and Synthetic Metabolism, Max Planck Institute for Terrestrial Microbiology, Marburg, Germany. amir.pandi@mpi-marburg.mpg.de.
Nature communications
|November 8, 2023
概括
研究人员开发了一种快速,低成本的无细胞蛋白质合成 (CFPS) 管道,以发现新型抗菌 (AMPs). 这种方法与深度学习相结合,确定了有效的AMP,对抗耐药细菌有效,而不会诱导耐药性.
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:
- 生物活性,特别是抗微生物 (AMP),在医学中至关重要.
- 深度学习显示了设计新型生物活性的潜力.
- 需要高吞吐量,具有成本效益的实验验证方法来发现.
研究的目的:
- 建立一个无细胞蛋白质合成 (CFPS) 管道,以快速,廉价地生产抗微生物 (AMPs).
- 通过生产和选使用深度学习生成的新设计的AMP来验证CFPS管道.
- 描述已识别的AMP的功能性质,包括抗菌活性和毒性.
主要方法:
- 开发一种无细胞蛋白质合成 (CFPS) 管道,用于直接DNA-to-peptide生产.
- 使用深度学习算法设计成千上万种抗微生物 (AMP).
- 500个AMP候选人的计算优先级通过CFPS进行生产和选.
- 使用分子动力学模拟,抗微生物测试和毒性测试对验证的AMP进行表征.
主要成果:
- 从选的候选人中确定了30种功能性抗微生物 (AMP).
- 六种新设计的AMP对抗多药耐药病原体表现出广泛的活性.
- 开发的AMPs没有诱导细菌耐药性.
- 在24小时内,CFPS管道使高吞吐量,低成本生产和测试成为可能.
结论:
- 已建立的CFPS管道为生产和选生物活性提供了快速和经济有效的解决方案.
- 深度学习与CFPS相结合,加速发现具有可取性质的新型抗菌.
- 这种综合方法对推动药物发现,特别是对抗抗菌素耐药性的进展具有重大前景.
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