Issue 7, 2013

Understanding traditional Chinese medicine anti-inflammatory herbal formulae by simulating their regulatory functions in the human arachidonic acid metabolic network

Abstract

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.

Graphical abstract: Understanding traditional Chinese medicine anti-inflammatory herbal formulae by simulating their regulatory functions in the human arachidonic acid metabolic network

Supplementary files

Article information

Article type
Paper
Submitted
30 Dec 2012
Accepted
14 Mar 2013
First published
15 Mar 2013

Mol. BioSyst., 2013,9, 1931-1938

Understanding traditional Chinese medicine anti-inflammatory herbal formulae by simulating their regulatory functions in the human arachidonic acid metabolic network

S. Gu, N. Yin, J. Pei and L. Lai, Mol. BioSyst., 2013, 9, 1931 DOI: 10.1039/C3MB25605G

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