The State Key Laboratory of Bioactive Substance and Function of Natural Medicines, China; Key Laboratory of Drug Target Research and Drug Screen, Institute of Materia Medica, Chinese Academy of Medical Science and Peking Union Medical College, Beijing, 100050, China.
Key Laboratory of Drug Target Research and Drug Screen, Institute of Materia Medica, Chinese Academy of Medical Science and Peking Union Medical College, Beijing, 100050, China.
J Ethnopharmacol. 2019 Oct 5;242:112044. doi: 10.1016/j.jep.2019.112044. Epub 2019 Jun 27.
Stroke is one of the most frequent causes of death and disability. So far there are no effective preventives or treatments. The therapeutic system of traditional Chinese medicines (TCMs) has been in use for several thousand years and still affords a valuable resource for today's clinicians in preserving health.
We had collected the Chinese medicinal formulae and then commonly used single herbs or drug combinations were analyzed through data mining. The ingredients from the top 30 frequently used herbs which have good druggability and blood-brain barrier permeability were collected as a natural product library. Targets of the related ingredients were predicted using various databases and analyzed by GO and KEGG pathway mapping. The potential stroke targets were validated in the market or from clinical trials, and used to establish molecular docking, HipHop and SBP models to screen new compounds for multi-target activity. Lastly, in vitro experiments with models for oxygen and glucose deprivation and reperfusion (OGDR) were conducted to test the activities of compounds identified by screening.
A total of 1679 Chinese medicinal formulas were selected and their prescription rules were analyzed. 4277 compounds were from the top 30 herbs and 3560 molecules were filtered to build the natural product library. The ingredient-target network, target-disease network and target-target interaction network were established to explain the characteristics and mechanisms of the TCMs. Thirty-one molecules were selected to have multi-target activity on targets of stroke via virtual screening. Five of these had already been reported to have therapeutic effects on stroke. Three of the eight compounds which have been examined showed protective effects on OGDR model.
This paper details a novel strategy for exploring the characteristics and mechanisms of herbal medicines from a systematic standpoint in an attempt to identify those affecting specific target pathways related to stroke. Using this methodology on our natural products library, we found a number of lead candidates with multi-target activity.
中风是最常见的死亡和残疾原因之一。到目前为止，还没有有效的预防或治疗方法。传统中药（TCM）的治疗系统已经使用了几千年，并且仍然为当今的临床医生提供了一种宝贵的资源，以保持健康。
我们已经收集了中药配方，然后通过数据挖掘分析了常用的单味药或药物组合。从具有良好成药性和血脑屏障通透性的前 30 种常用草药中收集了成分，作为天然产物库。使用各种数据库预测相关成分的靶点，并通过 GO 和 KEGG 途径映射进行分析。在市场上或临床试验中验证潜在的中风靶点，并用于建立分子对接、HipHop 和 SBP 模型，以筛选具有多靶点活性的新化合物。最后，通过氧葡萄糖剥夺和再灌注（OGDR）模型进行体外实验，测试筛选出的化合物的活性。
共选择了 1679 种中药方剂，并对其处方规则进行了分析。从前 30 种草药中提取了 4277 种化合物，筛选出 3560 种分子，构建了天然产物库。建立了成分-靶点网络、靶点-疾病网络和靶点-靶点相互作用网络，以解释 TCM 的特点和机制。通过虚拟筛选，从 31 种分子中选择了对中风靶点具有多靶点活性的分子。其中 5 种已经被报道对中风有治疗作用。在已检查的 8 种化合物中，有 3 种对 OGDR 模型有保护作用。
本文从系统的角度详细阐述了一种探索草药特性和机制的新策略，试图确定那些影响与中风相关的特定靶途径的药物。使用这种方法对我们的天然产物库进行研究，我们发现了一些具有多靶点活性的先导候选物。
