基于群体协同计算的痰瘀同治方抗心肌缺血再灌注损伤的处方优化研究

It is completely necessary for the development of new Chinese medicines to conduct a prescription optimization study on clinical effective prescriptions that have undergone a lot of basic researches. In the early stage of the project, with the support of three projects of national natural science foundation of China, it was confirmed that the efficacy of simultaneous formula of phlegm and stasis on myocardial ischemia and reperfusion injury（MI/RI）was definite, and its mechanism of action was explained in terms of inflammation, apoptosis, and autophagy. However, due to the fact that the formula has numerous herbal medicines and the composition is complex, it is difficult to further deepen research and convert it into new medicines. Based on the target and network data of the original compound, combined with the compatibility theory of traditional Chinese medicine formulas, the network computing methods can select the optimal medicine combination targeting the core target and pathways of diseases, so as to achieve the optimization of traditional Chinese medicine compound. Therefore, this study takes simultaneous formula of phlegm and stasis as a model, and introduces the theory of “JunChenZuoShi” into the network model, and takes the group cooperative computing as the core to identify the network module, and predict the synergy between medicines, so as to select the optimal medicine combination and provide a new method for optimizing the herbal number of the traditional Chinese medicine compound; and further develop the combination proportion optimization study of the compound formula to form a new prescription, and use the MI/RI rat models to compare the efficacy and mechanism with the original prescription to provide new ideas for the medicine research of anti-MI/RI in traditional Chinese medicine.

对于临床有效且已经过大量基础研究的验方进行处方优化研究，对于中药新药开发十分必要。课题组前期在3个国家自然科学基金项目的支持下，证实了痰瘀同治方对心肌缺血再灌注损伤（MI/RI）疗效确切，并从炎症、凋亡、自噬等角度阐释其作用机制。但由于该方药味较多、成分复杂，难以进一步深化研究并向新药转化。基于原复方的作用靶点和网络数据，结合中药方剂配伍理论，运用网络计算的方法能够筛选出针对疾病核心靶点及通路的最佳药物组合，从而实现对中药复方的优化。因此，本研究以痰瘀同治方为示范，将君臣佐使方剂配伍理论引入到网络模型构建中，以群体协同计算为核心进行网络模块的识别预测药物间的协同作用，从而筛选出药物最佳组合，为中药复方药味优化提供新的方法；进一步开展痰瘀同治方新药物组合的剂量配比研究形成新的处方，并运用MI/RI大鼠模型进行与原方的疗效对比观察及机制研究，为中医药抗MI/RI药物的研究提供新的思路。

临床验方是中药新药研发的主要来源之一，然而基于医生经验形成的验方往往药味繁多、成分复杂，向新药转化困难重重。因此，有必要对经过大量基础研究且已证实有一定疗效的验方进行复方优化研究。本课题在前期研究的基础上，对治疗MI/RI疗效确切的痰瘀同治方开展了复方优化研究。结合群体协同算法和君臣佐使配伍加权理论，本课题提出一种以中药复方靶点网络计算为核心的复方优化新方法，将原本13味药的大处方精简到6味药，且基因富集分析和动物实验结果表明优化后的处方与原方疗效相当，证实了该方法的有效性和可行性。在处方优化的基础上，采用均匀设计对优化方进行剂量优化研究，结合回归分析和多目标优化确定优化方的最佳剂量，且与原方相比疗效更佳。最终，从药物组成和剂量配比两方面实现痰瘀同治方的优化，形成新的痰瘀同治方，为中药复方优化提供一种新思路和新方法。