Abstract
Background and objective: Traditional Chinese Medicine (TCM) has been practiced over thousands of years in China and other Asian countries for treating various symptoms and diseases. However, the underlying molecular mechanisms of TCM are poorly understood, partly due to the “multi-component, multi-target” nature of TCM. To uncover the molecular mechanisms of TCM, we perform comprehensive gene expression analysis using connectivity map. Methods: We interrogated gene expression signatures obtained 102 TCM components using the next generation Connectivity Map (CMap) resource. We performed systematic data mining and analysis on the mechanism of action (MoA) of these TCM components based on the CMap results. Results: We clustered the 102 TCM components into four groups based on their MoAs using next generation CMap resource. We performed gene set enrichment analysis on these components to provide additional supports for explaining these molecular mechanisms. We also provided literature evidence to validate the MoAs identified through this bioinformatics analysis. Finally, we developed the Traditional Chinese Medicine Drug Repurposing Hub (TCM Hub) – a connectivity map resource to facilitate the elucidation of TCM MoA for drug repurposing research. TCMHub is freely available in http://tanlab.ucdenver.edu/TCMHub. Conclusions: Molecular mechanisms of TCM could be uncovered by using gene expression signatures and connectivity map. Through this analysis, we identified many of the TCM components possess diverse MoAs, this may explain the applications of TCM in treating various symptoms and diseases.
| Original language | English |
|---|---|
| Journal | Computer Methods and Programs in Biomedicine |
| DOIs | |
| Publication status | Accepted/In press - 2018 Jan 1 |
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Keywords
- Bioinformatics
- Connectivity map
- Gene expression signatures
- Mechanisms of action
- Traditional Chinese Medicine
ASJC Scopus subject areas
- Software
- Computer Science Applications
- Health Informatics
Cite this
Exploring the molecular mechanisms of Traditional Chinese Medicine components using gene expression signatures and connectivity map. / Yoo, Minjae; Shin, Jimin; Kim, Hyunmin; Kim, Jihye; Kang, Jaewoo; Tan, Aik-Choon.
In: Computer Methods and Programs in Biomedicine, 01.01.2018.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Exploring the molecular mechanisms of Traditional Chinese Medicine components using gene expression signatures and connectivity map
AU - Yoo, Minjae
AU - Shin, Jimin
AU - Kim, Hyunmin
AU - Kim, Jihye
AU - Kang, Jaewoo
AU - Tan, Aik-Choon
PY - 2018/1/1
Y1 - 2018/1/1
N2 - Background and objective: Traditional Chinese Medicine (TCM) has been practiced over thousands of years in China and other Asian countries for treating various symptoms and diseases. However, the underlying molecular mechanisms of TCM are poorly understood, partly due to the “multi-component, multi-target” nature of TCM. To uncover the molecular mechanisms of TCM, we perform comprehensive gene expression analysis using connectivity map. Methods: We interrogated gene expression signatures obtained 102 TCM components using the next generation Connectivity Map (CMap) resource. We performed systematic data mining and analysis on the mechanism of action (MoA) of these TCM components based on the CMap results. Results: We clustered the 102 TCM components into four groups based on their MoAs using next generation CMap resource. We performed gene set enrichment analysis on these components to provide additional supports for explaining these molecular mechanisms. We also provided literature evidence to validate the MoAs identified through this bioinformatics analysis. Finally, we developed the Traditional Chinese Medicine Drug Repurposing Hub (TCM Hub) – a connectivity map resource to facilitate the elucidation of TCM MoA for drug repurposing research. TCMHub is freely available in http://tanlab.ucdenver.edu/TCMHub. Conclusions: Molecular mechanisms of TCM could be uncovered by using gene expression signatures and connectivity map. Through this analysis, we identified many of the TCM components possess diverse MoAs, this may explain the applications of TCM in treating various symptoms and diseases.
AB - Background and objective: Traditional Chinese Medicine (TCM) has been practiced over thousands of years in China and other Asian countries for treating various symptoms and diseases. However, the underlying molecular mechanisms of TCM are poorly understood, partly due to the “multi-component, multi-target” nature of TCM. To uncover the molecular mechanisms of TCM, we perform comprehensive gene expression analysis using connectivity map. Methods: We interrogated gene expression signatures obtained 102 TCM components using the next generation Connectivity Map (CMap) resource. We performed systematic data mining and analysis on the mechanism of action (MoA) of these TCM components based on the CMap results. Results: We clustered the 102 TCM components into four groups based on their MoAs using next generation CMap resource. We performed gene set enrichment analysis on these components to provide additional supports for explaining these molecular mechanisms. We also provided literature evidence to validate the MoAs identified through this bioinformatics analysis. Finally, we developed the Traditional Chinese Medicine Drug Repurposing Hub (TCM Hub) – a connectivity map resource to facilitate the elucidation of TCM MoA for drug repurposing research. TCMHub is freely available in http://tanlab.ucdenver.edu/TCMHub. Conclusions: Molecular mechanisms of TCM could be uncovered by using gene expression signatures and connectivity map. Through this analysis, we identified many of the TCM components possess diverse MoAs, this may explain the applications of TCM in treating various symptoms and diseases.
KW - Bioinformatics
KW - Connectivity map
KW - Gene expression signatures
KW - Mechanisms of action
KW - Traditional Chinese Medicine
UR - http://www.scopus.com/inward/record.url?scp=85045080802&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85045080802&partnerID=8YFLogxK
U2 - 10.1016/j.cmpb.2018.04.002
DO - 10.1016/j.cmpb.2018.04.002
M3 - Article
C2 - 29650251
AN - SCOPUS:85045080802
JO - Computer Methods and Programs in Biomedicine
JF - Computer Methods and Programs in Biomedicine
SN - 0169-2607
ER -