Bioinformatics Center, College of Life Sciences, Northwest A&F University, Yangling, Shaanxi, China.
PLoS One. 2012;7(9):e43918. doi: 10.1371/journal.pone.0043918. Epub 2012 Sep 4.
Compound Danshen Formula (CDF) is a widely used Traditional Chinese Medicine (TCM) which has been extensively applied in clinical treatment of cardiovascular diseases (CVDs). However, the underlying mechanism of clinical administrating CDF on CVDs is not clear. In this study, the pharmacological effect of CDF on CVDs was analyzed at a systemic point of view. A systems-pharmacological model based on chemical, chemogenomics and pharmacological data is developed via network reconstruction approach. By using this model, we performed a high-throughput in silico screen and obtained a group of compounds from CDF which possess desirable pharmacodynamical and pharmacological characteristics. These compounds and the corresponding protein targets are further used to search against biological databases, such as the compound-target associations, compound-pathway connections and disease-target interactions for reconstructing the biologically meaningful networks for a TCM formula. This study not only made a contribution to a better understanding of the mechanisms of CDF, but also proposed a strategy to develop novel TCM candidates at a network pharmacology level.
复方丹参方(CDF)是一种广泛应用于心血管疾病(CVDs)临床治疗的中药。然而,CDF 治疗 CVDs 的临床作用机制尚不清楚。在这项研究中,从系统的角度分析了 CDF 对 CVDs 的药理作用。通过网络重建方法,开发了一个基于化学、化学生物基因组学和药理学数据的系统药理学模型。利用该模型,我们进行了高通量的计算筛选,从 CDF 中获得了一组具有理想药效学和药理学特性的化合物。这些化合物和相应的蛋白质靶标进一步用于搜索生物数据库,如化合物-靶标关联、化合物途径连接和疾病-靶标相互作用,以构建有意义的中药配方生物网络。这项研究不仅有助于更好地理解 CDF 的作用机制,还提出了一种在网络药理学水平上开发新型中药候选药物的策略。