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中草药中草药化合物的预测方法。

Prediction Methods of Herbal Compounds in Chinese Medicinal Herbs.

机构信息

School of Computer and Information Engineering, Harbin University of Commerce, Harbin 150028, China.

Life Sciences and Environmental Sciences Development Center, Harbin University of Commerce, Harbin 150010, China.

出版信息

Molecules. 2018 Sep 10;23(9):2303. doi: 10.3390/molecules23092303.

Abstract

Chinese herbal medicine has recently gained worldwide attention. The curative mechanism of Chinese herbal medicine is compared with that of western medicine at the molecular level. The treatment mechanism of most Chinese herbal medicines is still not clear. How do we integrate Chinese herbal medicine compounds with modern medicine? Chinese herbal medicine drug-like prediction method is particularly important. A growing number of Chinese herbal source compounds are now widely used as drug-like compound candidates. An important way for pharmaceutical companies to develop drugs is to discover potentially active compounds from related herbs in Chinese herbs. The methods for predicting the drug-like properties of Chinese herbal compounds include the virtual screening method, pharmacophore model method and machine learning method. In this paper, we focus on the prediction methods for the medicinal properties of Chinese herbal medicines. We analyze the advantages and disadvantages of the above three methods, and then introduce the specific steps of the virtual screening method. Finally, we present the prospect of the joint application of various methods.

摘要

中草药最近引起了全世界的关注。中草药的治疗机制在分子水平上与西药进行了比较。大多数中草药的治疗机制仍不清楚。我们如何将中草药化合物与现代医学相结合?中草药类药物预测方法尤为重要。现在越来越多的中草药源化合物被广泛用作类药性化合物候选物。制药公司开发药物的一个重要途径是从中药中的相关草药中发现潜在的活性化合物。预测中草药化合物类药性的方法包括虚拟筛选方法、药效基团模型方法和机器学习方法。本文重点介绍中草药药效预测方法,分析上述三种方法的优缺点,然后介绍虚拟筛选方法的具体步骤。最后,介绍了各种方法联合应用的前景。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8f43/6225236/ab6abd7b1462/molecules-23-02303-g001.jpg

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