Gu Shuo, Yin Ning, Pei Jianfeng, Lai Luhua
Center for Quantitative Biology, AAIS, Peking University, Beijing 100871, China.
Mol Biosyst. 2013 Jul;9(7):1931-8. doi: 10.1039/c3mb25605g. Epub 2013 Apr 23.
Through history, traditional Chinese medicine (TCM) has adopted oriental philosophical practices of drug combination and interaction to address human diseases. To investigate this from a systems biology point of view, we analysed 28 TCM herbs for their anti-inflammatory function, using molecular docking and arachidonic acid (AA) metabolic network simulation. The inhibition potential of each herb toward five essential enzymes as well as their possible side effects were examined. Three commonly prescribed anti-inflammatory formulae were simulated to discover the combinatorial properties of each contained herb in regulating the whole metabolic network. We discovered that different ingredients of a formula tend to inhibit different targets, which almost covered all the targets in the whole network. We also found that herbal combinations could achieve the same therapeutic effect at lower doses compared with individual usage. New herbal combinations were also predicted based on the inhibition potentials and two types of synergistic drug combinations of TCM theory were discussed from the perspective of systems biology. Using this combined approach of molecular docking and network simulation, we were able to computationally elucidate the combinatorial effects of TCM to intervene disease networks. We expect novel TCM formulae or modern drug combinations to be developed based on this research.
纵观历史,中医采用东方哲学中药物配伍和相互作用的方法来治疗人类疾病。为了从系统生物学的角度对此进行研究,我们运用分子对接和花生四烯酸(AA)代谢网络模拟,分析了28种中药的抗炎功能。检测了每种草药对五种关键酶的抑制潜力及其可能的副作用。模拟了三种常用的抗炎方剂,以发现每种所含草药在调节整个代谢网络中的组合特性。我们发现,方剂中的不同成分倾向于抑制不同的靶点,几乎涵盖了整个网络中的所有靶点。我们还发现,与单独使用相比,草药组合可以在较低剂量下达到相同的治疗效果。基于抑制潜力还预测了新的草药组合,并从系统生物学的角度讨论了中医理论中的两种协同药物组合类型。通过分子对接和网络模拟相结合的方法,我们能够通过计算阐明中药干预疾病网络的组合效应。我们期望基于这项研究开发出新的中药方剂或现代药物组合。