目的 探索桔梗汤止咳祛痰功效的潜在活性成分群和分子作用机制。方法 在文献挖掘、多个数据库联用检索与痰多咳嗽相关靶蛋白基础上，利用分子计算结合网络特征分析获得桔梗汤的主要活性成分和潜在的靶点蛋白，并构建分子-蛋白调控网络。结果 基于痰多咳嗽相关病变机制，初步筛选出38个靶蛋白和472个小分子；分子对接结果中发现桔梗汤中78个分子（结构特征分析均符合“类药五原则”）与靶蛋白相互作用的对接得分较高（Score≥7），其中5个成分来自桔梗，73个成分来自甘草。依据分子对接结果，选取对接得分较高（Score≥7）的128条分子-靶蛋白数据对，通过插件Network analyzer分析网络特征，识别出桔梗汤26个主要活性成分（皂苷和黄酮类化合物等）和13个靶蛋白。结论 桔梗汤主要通过其所含的皂苷、黄酮类化合物与TLR4、MMP9、IKK2等多个靶蛋白的作用，起到调控呼吸道过度炎症反应、改善肺功能、抑制黏蛋白过表达、降低咳嗽中枢对刺激反应等作用，最终实现止咳祛痰功效。

Objective To investigate the molecular mechanism and potential active components of Jiegeng Decotion (JD) with the antitussive and expectorant effects. Methods Target proteins related with phlegm and cough were selected through mining literature and retrieving in DrugBank and TTD database, and the main active components and potential target proteins from JD were computed and analyzed by DOVIS 2.0 and Cytoscape 3.0 to build a molecular-protein regulatory network. Results A total of 38 target proteins and 472 small molecules were initially screened based on the pathological mechanism which is related with phlegm and cough. Molecular docking results showed that 78 molecules (five from Platycodi Radix and 73 from Glycyrrhizae Radix et Rhizoma, and their structural characteristics analysis were in accordance with the "rules of generic drugs") were found in JD with higher docking score (Score ≥ 7) of target protein. According to the results of molecular docking, 128 molecular-target protein data pairs with high docking scores (Score ≥ 7) were selected, and then 26 major active components of JD (saponins and flavonoids, etc.) and 13 target proteins were identified by using Network analyzer. Conclusion The active components of JD could regulate over-inflammatory response on the respiratory tract, improve the lung function, inhibit the over-expression of mucin, and reduce the reaction of the stimulation on cough center through acting on the main target proteins (TLR4, MMP9, IKK2, etc), thereby achieving the antitussive and expectorant effects.

国家自然科学基金资助项目（81774156，81001499）；江苏省“333工程”科研资助项目（BRA2016427）；江苏省“六大人才高峰”高层次人才选拔培养资助项目（YY-022）