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智能质谱数据处理技术的进步用于自然药物的体内分析

Simian Chen¹, Binxin Dai¹, Dandan Zhang¹

¹Fujian Provincial Key Laboratory of Innovative Drug Target Research and State Key Laboratory of Cellular Stress Biology, School of Pharmaceutical Sciences, Xiamen University, Xiamen 361102, China.

Chinese journal of natural medicines

|October 20, 2024

概括

智能数据处理增强了使用HPLC-HRMS的自然药物 (NM) 的体内分析. 这些先进的技术提高了灵敏度和化合物覆盖率,以更好地了解NM代谢和活性成分.

科学领域:

药理学和分析化学分析化学
自然产品研究自然产品研究

背景情况:

自然药物 (NM) 对于疾病治疗至关重要,但其生物活性成分的体内表征仍然具有挑战性.
高性能液体染色学-高分辨率质谱学 (HPLC-HRMS) 是一种强大的 in vivo NM 分析工具,但传统的数据处理方法对于复杂的 NM 样品是不够的.

研究的目的:

审查过去二十年内体内自然医学分析方面的进展,重点关注智能光谱数据处理技术.
突出这些技术在克服分析生物系统中复杂的NM混合物的传统方法的局限性方面的作用.

主要方法:

对应用在体内自然医学分析中的智能光谱数据处理技术的研究进行审查.
讨论各种原则和算法,包括人工智能 (AI) 神经网络算法.
分析与化合物结构多样性和生物样本可变性相关的挑战.

主要成果:

智能数据处理技术在没有硬件更改的情况下显著提高了分析性能.
改进包括提高灵敏度,扩大化合物覆盖范围,以及智能识别未针对的体内化合物.
这些方法为研究NM代谢和查药理活性成分提供了强大的工具.

结论:

智能光谱数据处理对于推进天然药物的体内分析至关重要.
未来的方向包括NMS的体内追踪,对生物活性成分的选,以及识别药理动力学标记.
这一综述是整合未来体内NM分析新技术的参考.

关键词:

人工智能的人工智能数据获取 - 数据获取数据处理数据处理.高性能液态色谱学高分辨率质谱学代谢学代谢学代谢学

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