Chen Xin, Ung Choong Yong, Chen Yuzong
Department of Computational Science, National University of Singapore, Blk S17, Level 7, 3 Science Drive 2, Singapore 117543.
Nat Prod Rep. 2003 Aug;20(4):432-44. doi: 10.1039/b303745b.
Medicinal plants have been explored therapeutically in traditional medicines and are a valuable source for drug discovery. Insufficient knowledge about the molecular mechanism of these medicinal plants limits the scope of their application and hinders the effort to design new drugs using the therapeutic principles of herbal medicines. This problem can be partially alleviated if efficient methods for rapid identification of protein targets of herbal ingredients can be introduced. Efforts have been directed at developing efficient computer methods for facilitating target identification. Various methods being explored or under investigation are reviewed here. So far, one computer method, INVDOCK, has been specifically used for automated drug target identification. Its usefulness in the identification of therapeutic targets of medicinal herbal ingredients as well as synthetic chemicals is reviewed. The majority of INVDOCK identified therapeutic targets of several well-known medicinal herbal ingredients have been found to be confirmed or implicated by experiments, which suggests the potential of in silico methods in facilitating the study of molecular mechanism of medicinal plants.
药用植物在传统医学中已被用于治疗，并且是药物发现的宝贵来源。对这些药用植物分子机制的了解不足限制了它们的应用范围，并阻碍了利用草药治疗原理设计新药的努力。如果能够引入高效的方法来快速鉴定草药成分的蛋白质靶点，这个问题可以得到部分缓解。人们一直在致力于开发高效的计算机方法来促进靶点鉴定。本文综述了正在探索或研究中的各种方法。到目前为止，一种计算机方法INVDOCK已专门用于自动药物靶点鉴定。本文综述了其在鉴定药用草药成分以及合成化学品治疗靶点方面的实用性。INVDOCK鉴定出的几种著名药用草药成分的大多数治疗靶点已被实验证实或涉及，这表明计算机方法在促进药用植物分子机制研究方面的潜力。
