Prediction of multi-target of Aconiti Lateralis Radix Praeparata and its network pharmacology / 中国中药杂志

<p><b>OBJECTIVE</b>To predict multi-targets by multi-compounds found in Aconiti Lateralis Radix Praeparata and construct the corresponding multi-compound-multi-target network.</p><p><b>METHOD</b>Based on drug-target relationships of FDA approved drugs, a model for predicting targets was established by random forest algorithm. This model was then applied to predict the targets of Aconiti Lateralis Radix Praeparata and construct the multi-compound-multi-target network.</p><p><b>RESULT</b>The predicted targets of 22 compounds of Aconiti Lateralis Radix Praeparata are validated by literature. Each compound in the established network was correlated with 16. 3 targets on average, while each target was correlated with 4. 77 compounds on average, which reflects the "multi-compound and multi-target" characteristic of Chinese medicine.</p><p><b>CONCLUSION</b>The proposed approach can be used to find potential targets of Chinese medicine.</p>

Network pharmacology study on major active compounds of Fufang Danshen formula / 中国中药杂志

<p><b>OBJECTIVE</b>To investigate the correlations between multi-compounds of Fufang Danshen formula and their multi targets and multi diseases.</p><p><b>METHOD</b>Literature knowledge of nine major active compounds from Fufang Danshen formula, including tanshinone II(A), salvianolic acid B, protocatechuic aldehyde, danshensu, cryptotanshinone, notoginsenoside R1, ginsenoside Rg1, ginsenoside Rb1 and borneol were collected from PubMed. Combined with cardiovascular related diseases and genes from OMIM database, the corresponding multi-compound-multi- target-multi-disease network was constructed and visualized by Cytoscape software.</p><p><b>RESULT</b>AND CONCLUSION: Network analysis showed that the 9 compounds could modulate 42 cardiovascular associated genes (e. g. PPARG, ACE, KCNJ11, KCNQ1, ABCC8, et al), which related to 30 cardiovascular associated diseases including non-insulin-dependent diabetes mellitus, hyperinsulinemic hypoglycemia, hypertension, and coronary heart disease. These results suggested new potential indications of Fufang Danshen formula.</p>

Symptom-based traditional Chinese medicine slices relationship network and its network pharmacology study / 中国中药杂志

<p><b>OBJECTIVE</b>To discover and interpret the correlations between traditional Chinese medicine (TCM) slices and their properties such as function, symptom and channel tropism by constructing the relationship network using network pharmacology approaches.</p><p><b>METHOD</b>TCM slices related information was extracted from Chinese Pharmacopeia (2010 edition, volume I) by text mining, and was used to construct the TCM slices-symptom relationship network. The corresponding network analysis was also performed.</p><p><b>RESULT</b>Three thousands and sixteen pair of TCM slice-symptom correlation associated with 646 TCM slices was discovered, and the constructed network unfolded the complex relationships between TCM slices. Further network analysis results indicated that the un-annotated function and channel tropism of TCM slice can be revealed by proposed symptom-based network.</p><p><b>CONCLUSION</b>Network pharmacology approaches can be applied in TCM research to discover and interpret the relationships between TCM slices and their properties.</p>

Tools for network pharmacology study: network visualization and network analysis / 中国中药杂志

Network pharmacology has been one of the academic frontiers of traditional Chinese medicine research. In this paper, we generally showed the work flow of network pharmacology research, and introduced concepts of network visualization and network analysis, as well the commonly-used tools, such as Cytoscape.