Predicting and understanding synergistic pairwise compound combinations of Shexian Baoxin Pill (SBP) using network biology

Q2 Medicine
Siti Zuraidah Mohamad Zobir , Ran Joo Choi , Dezso Modos , Tai-Ping Fan , Andreas Bender
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引用次数: 1

Abstract

The Traditional Chinese Medicine (TCM) formulation Shexiang Baoxin Pill (SBP) is commonly used in the treatment of coronary heart disease (CHD) in East Asia and regarded to promote the regulation of angiogenesis and to improve endothelial function. SBP comprises of seven TCM materials; however, the interactions of their effects in a biological system are unknown. In this work we developed an algorithm to predict the synergy of pairwise combinations of 22 compounds present in SBP. The algorithm is based on the targets of the compounds network properties in an angiogenesis- and CHD-specific network. We evaluated our synergy score prospectively by testing the 20 highest-ranked and the 20 lowest-ranked compound combinations for their synergistic potential to promote cell proliferation of human umbilical vascular endothelial cells. Results showed that 70 % of the 20 highest-ranked combinations increased cell proliferation synergistically, while only 30 % of the 20 lowest-ranked combinations had a synergistic effect. Based on the target and pathway predictions for the combinations, we hypothesized that two complementary pathways are responsible for the synergistic effect, apoptosis through caspase-3 and caspase-8 and cell growth through the proto-oncogene c-Fos and fibroblast growth factor 1. Hence, in this work we introduce an algorithm which was able to increase the probability of identifying compound pairs from SBP exhibiting synergy, which was experimentally validated in a disease-relevant model. Furthermore, we were able, based on this model, to provide a hypothesis for interactions causing synergy to promote endothelial cell growth.

Abstract Image

利用网络生物学预测和理解蛇仙保心丸(SBP)的协同配对组合
蛇香保心丸(SBP)是东亚地区治疗冠心病(CHD)常用的中药制剂,被认为具有促进血管生成和改善内皮功能的作用。SBP由七种中药组成;然而,它们在生物系统中的相互作用是未知的。在这项工作中,我们开发了一种算法来预测存在于SBP中的22种化合物的成对组合的协同作用。该算法基于血管生成和冠心病特异性网络中化合物网络特性的目标。我们通过测试20个排名最高和20个排名最低的化合物组合来评估我们的协同作用评分,以促进人类脐带血管内皮细胞的细胞增殖。结果显示,在20个排名最高的组合中,70%的组合具有协同作用,而在20个排名最低的组合中,只有30%的组合具有协同作用。基于对这些组合的靶点和通路的预测,我们假设两个互补的通路负责协同作用,通过caspase-3和caspase-8进行细胞凋亡,通过原癌基因c-Fos和成纤维细胞生长因子1进行细胞生长。因此,在这项工作中,我们引入了一种算法,该算法能够增加从SBP中识别出具有协同作用的化合物对的概率,这在疾病相关模型中得到了实验验证。此外,基于该模型,我们能够提供一个相互作用导致协同作用促进内皮细胞生长的假设。
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Synergy
Synergy Medicine-Medicine (miscellaneous)
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