基于生物网络的桂枝茯苓胶囊作用机理研究  

Action mechanism studies of GuizhiFuling Capsule:based on a bio-network analysis

作　　者：萧伟[1,2] 曹亮[1,2] 范麒如[1,2] 丁岗[1,2] 毕宇安[1,2] 丁为现[1,2] 王振中[1,2] 

机构地区：[1]江苏康缘药业股份有限公司,江苏连云港222001 [2]中药制药过程新技术国家重点实验室,江苏连云港222001

出　　处：《计算机与应用化学》2012年第12期1455-1459,共5页Computers and Applied Chemistry

基　　金：国家重大新药创制项目(2009ZX09504-004)

摘　　要：利用计算药理学研究桂枝茯苓胶囊中的460个化合物的化学空间分布,并利用分子对接及生物网络分析方法研究了这些化合物与1053个FDA批准药物靶点的作用情况。化学空间分布研究结果表明桂枝茯苓胶囊中的大部分化合物具有较好的类药性,生物网络分析结果初步阐释了桂枝茯苓胶囊治疗妇科血瘀证可能的作用机理及潜在活性成分。GuizhiFuling Capsule （GFC） is a traditional Chinese medical （TCM） with good effect for treating gynecological blood stasis. Previous pharmacology methods to explain the mechanism of GFC drug action have mainly focused on the interactions between single molecule and single disease target. When comprehensively explain the action mechanism of complicated system, those methods showed powerless and time-cousuming. Here, we present a bio-network method to analysis the drug action and predict the active compound, which can handle complicated associations of multiple compounds from TCM and multiple targets involved in a disease. Firstly, we used computational pharmacological methods to study the chemical space distribution of 460 compounds from 5 kinds of Chinese herbs of GFC. The result indicated that those compounds have good drug-like properties, as mean rule of 5 violations lower than 1.5. The principal component analysis shows that the chemical space distribution of 460 compounds completely covered 150 drugs, approved by Food and Drug Administration of United States （FDA）, which have treatment similarity with GFC. After that, the molecule docking method was used to study the interactions between those compounds and 1053 drug targets approved by FDA. Then, a ＂drug-target＂ bio-network was structured by combining the filtered docking data. The bio-network analysis shows that the most of compounds in GFC have a good target binding potential. 397 compounds can interacted with 998 targets and ct-amylin, as the best one, has interactive actions with 692 targets. Finally, 33 targets were filtered out using disease-associated about gynecological blood stasis. We found that 305 compounds have potential binding actives with them. This work may contribute to rapid detection useful targets in disease and large-scale prediction active compounds from TCM.

关 键 词：化学空间 分子对接 生物网络 妇科血瘀证 桂枝茯苓胶囊 

分 类 号：R914.2[医药卫生—药物化学] R963[医药卫生—药学]