Herbal medicine (HM) has made a major contribution to the drug discovery process with regard to identifying products compounds. Currently, more attention has been focused on drug discovery from natural compounds of HM. Despite the rapid advancement of modern analytical techniques, drug discovery is still a difficult and lengthy process. Fortunately, mass spectrometry (MS) can provide us with useful structural information for drug discovery, has been recognized as a sensitive, rapid, and high‐throughput technology for advancing drug discovery from HM in the post‐genomic era. It is essential to develop an efficient, high‐quality, high‐throughput screening method integrated with an MS platform for early screening of candidate drug molecules from natural products. We have developed a new chinmedomics strategy reliant on MS that is capable of capturing the candidate molecules, facilitating their identification of novel chemical structures in the early phase; chinmedomics‐guided natural product discovery based on MS may provide an effective tool that addresses challenges in early screening of effective constituents of herbs against disease. This critical review covers the use of MS with related techniques and methodologies for natural product discovery, biomarker identification, and determination of mechanisms of action. It also highlights high‐throughput chinmedomics screening methods suitable for lead compound discovery illustrated by recent successes.

中文翻译：

---

质谱驱动的发现药物开发草药

在鉴定产品化合物方面，草药（HM）在药物发现过程中做出了重大贡献。当前，更多的注意力集中在从HM的天然化合物中发现药物。尽管现代分析技术迅速发展，但是药物发现仍然是一个困难而漫长的过程。幸运的是，质谱（MS）可以为我们提供有关药物发现的有用结构信息，它已被公认为是灵敏，快速且高通量的技术，可促进后基因组时代从HM进行药物发现。开发一种与MS平台集成的高效，高质量，高通量筛选方法对于从天然产物中早期筛选候选药物分子至关重要。我们已经开发出了一种新的依赖于MS的chomedomics策略，该策略能够捕获候选分子，从而有助于他们在早期阶段识别出新的化学结构。基于MS的根部药物引导的天然产物发现可能提供了一种有效的工具，可以解决早期筛选有效的抗病草药有效成分方面的挑战。这篇重要的评论涵盖了将MS与相关技术和方法一起用于天然产物发现，生物标志物鉴定和作用机理的确定。它还强调了适用于铅化合物发现的高通量chindomdomics筛选方法，最近的成功表明了这一点。基于MS的根部药物引导的天然产物发现可能提供了一种有效的工具，可以解决早期筛选有效的抗病草药有效成分方面的挑战。这篇重要的评论涵盖了将MS与相关技术和方法一起用于天然产物发现，生物标志物鉴定和作用机理的确定。它还强调了适用于铅化合物发现的高通量chindomdomics筛选方法，最近的成功表明了这一点。基于MS的根部药物引导的天然产物发现可能提供了一种有效的工具，可以解决在早期筛查抗病草药的有效成分方面的挑战。这篇重要的评论涵盖了将MS与相关技术和方法一起用于天然产物发现，生物标志物鉴定和作用机理的确定。它还强调了适用于铅化合物发现的高通量chindomdomics筛选方法，最近的成功表明了这一点。