Traditional Chinese medicine Network Pharmacology

Traditional Chinese medicine Network Pharmacology (TCMNP) is the study of herbal drug actions. Its main objective is to elucidate multiple-target activity of Chinese herbal drugs. As an interdisciplinary field, techniques like data mining, machine learning as well as pharmacological experiments are frequently used.
Overview
Multiple-target
In classic pharmacology study, a drug presents its therapeutic effect by binding to a specific target, which is called the lock and key theory.
In recent years, studies suggest that a drug would act on multiple targets instead of one. Drug targets form scale-free networks and show various network properties.
TCM and network pharmacology
In China, Traditional Chinese medicine (TCM) has been used in clinical practice for over 2500 years. It is regarded as a part of complementary and alternative medical systems and a potential source for drug discovery. In practice, TCM treats diseases primarily with herbal formulae (“Fu Fang”, in Chinese), which consist of several herbs and other natural products. Recent studies show that bioactive ingredients in herbs act moderately on multiple cellular targets in human body. In a case study of Liu-Wei-Di-Huang pill, a compound-target-disease network is built and reveals that a group of molecular targets are related to LWDH therapeutic effects. Another research shows that TCM therapies modulate NEI molecular network.
Methods
Computational modeling
Databases
Researches in TCMNP use databases like GeneBank, HPRD, OMIM and so on. Some unique databases related to TCM research are also used like TCM_ID and TcmSP. Through these databases, computer languages like C++, perl, phython, etc are used to retrieve information of drugs and proteins in order to build a network.
Build networks
Specific computer algorithms are developed to build links. In S. Li's research, a regression model called drugCIPHER was built to link herbal drug ingredients and target proteins by combining the drug chemical similarity and protein-protein interaction information. It bases on the principle that drugs with similar chemical structures or therapeutic effects tend to bind to functionally related target proteins in the molecular network. Input data includes herbal drug compounds, FDA-approved drug structures, drug-target interactions and human protein interactions.
Network analysis tools
Common network analysis tools include Cytoscape, NetworkX, Gephi, Pajek, Complex networks package for Matlab, etc.
Experimental verification
Experimental approaches including high-throughput “omics” technologies and pharmacological experiments. They are conducted to validate dry lab analysis. In a research of Ge-Gen-Qin-Lian formula, rat insulin enzyme immunoassay (EIA) was used to determine insulin stimulatory activity of an herbal ingredient selected by computational models.
Applications
There are mainly four expecting applications: <ref name="Yang" />
1. Discover new potential drug targets and treatments.
2. Discover new potential synergistic herb/ingredient pairs.
3. Understand herb combinational rules
4. Understand the principle of TCM syndromes.

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