可解释的人工智能解码肠道微生物代谢物的血脑屏障透性
Chunyi Yang1,2, Lan Yang2, Yuyang Song1
1National Glycoengineering Research Center, Shandong University, Qingdao 266237, China.
Biochemistry
|February 4, 2026
概括
研究人员开发了一种新的计算方法来预测肠道微生物代谢物如何穿越血脑屏障 (BBB). 这种工具有助于识别具有潜在大脑活动的代谢物,推进肠-大脑轴研究.
科学领域:
- 微生物学 微生物学
- 神经科学是一个神经科学.
- 计算化学的计算化学
背景情况:
- 肠道微生物群通过代谢途径显著影响肠-大脑轴.
- 肠道微生物代谢物穿越血脑屏障 (BBB) 的能力对于它们对大脑的影响至关重要.
- 评估BBB透性的现有方法通常是昂贵的,耗时的,缺乏标准化.
研究的目的:
- 开发一种自动化工作流程,以生成高质量的肠道微生物代谢物及其与BBB透性相关的热力学特性数据集.
- 构建一个可解释的热力学评估框架,用于预测跨膜传输.
- 为智能BBB透性预测提供一个新的范式.
主要方法:
- 自动化分子模拟工作流程,生成肠道微生物代谢物的数据集.
- 具有与BBB透性相关的热力学特征的代谢物的注释.
- 开发一个可解释的热力学评估框架,用于预测运输.
主要成果:
- 产生了具有热力学特征的肠道微生物代谢物的高质量数据集.
- 开发了一个经过验证的热力学框架,准确地识别了影响跨膜传输的关键因素.
- 在基准数据集上证明了模型的稳定性和预测能力,区分了透性和非透性化合物.
结论:
- 肠道微生物群的新陈代谢有很大的潜力影响BBB的透性.
- 开发的工具有助于识别肠道微生物群衍生代谢物,在大脑中具有潜在的生物活性.
- 介绍了一种新的,智能方法来预测BBB透性.
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