Abstract
Traditional Chinese medicine (TCM) is typically prescribed as formula to treat certain symptoms. A TCM formula contains hundreds of chemical components, which makes it complicated to elucidate the molecular mechanisms of TCM. Here, we proposed a computational systems pharmacology approach consisting of network link prediction, statistical analysis, and bioinformatics tools to investigate the molecular mechanisms of TCM formulae. Taking formula Tian-Ma-Gou-Teng-Yin as an example, which shows pharmacological effects on Alzheimer’s disease (AD) and its mechanism is unclear, we first identified 494 formula components together with corresponding 178 known targets, and then predicted 364 potential targets for these components with our balanced substructure-drug–target network-based inference method. With Fisher’s exact test and statistical analysis we identified 12 compounds to be most significantly related to AD. The target genes of these compounds were further enriched onto pathways involved in AD, such as neuroactive ligand–receptor interaction, serotonergic synapse, inflammatory mediator regulation of transient receptor potential channel and calcium signaling pathway. By regulating key target genes, such as ACHE, HTR2A, NOS2, and TRPA1, the formula could have neuroprotective and anti-neuroinflammatory effects against the progression of AD. Our approach provided a holistic perspective to study the relevance between TCM formulae and diseases, and implied possible pharmacological effects of TCM components.
Highlights
With more than 5,000-year history, the traditional Chinese medicine (TCM) still plays key roles in the treatment of many diseases and disorders worldwide
We proposed a computational systems pharmacology approach (Figure 1) combining our balanced substructure-drug–target network-based inference (bSDTNBI) method and statistical analysis to find out the molecular mechanisms of Traditional Chinese medicine (TCM) formulae, taking formula Tian-Ma-GouTeng-Yin (TMGTY) as an example
In order to evaluate the pharmacokinetic properties of this oral administrated formula, human intestinal absorption (HIA) and blood brain barrier (BBB) penetrations were predicted using our in silico system admetSAR
Summary
With more than 5,000-year history, the traditional Chinese medicine (TCM) still plays key roles in the treatment of many diseases and disorders worldwide. Computational Systems Pharmacology of TCM hundreds of chemical components, which makes it complicated and difficult to elucidate the molecular mechanisms of treatment. Network pharmacology is especially advantageous in analyzing ‘multicompound, multi-target, and multi-effect’ scenario to reveal the molecular relationships among compounds and complex diseases from multiple scales (Zhao et al, 2010; Li et al, 2012). It is very helpful for illustrating molecular mechanisms of TCM formulae and finding active constituents from herbs (Hao and Xiao, 2014). There are many studies published to date, such as Radix Curcumae formula against cardiovascular diseases (Tao et al, 2013), Qing-Luo-Yin against Rheumatoid arthritis (Zhang B. et al, 2013) and Ge-GenQin-Lian decoction against type 2 diabetes (Li J. et al, 2014)
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