Cardiovascular Disease Chemogenomics Knowledgebase-guided Target Identification and Drug Synergy Mechanism Study of an Herbal Formula.

Hai Zhang,Yifeng Chai,Dongyao Wang,Chengjian Li,Guoqing Zhang,Junping Zhang,Xiang-Qun Xie,Aijun Liu,Lirong Wang,Zhiwei Feng,Shifan Ma,Xiaofei Chen,Zhenyu Zhu,Yan Cao

doi:10.1038/srep33963

Abstract

Combination therapy is a popular treatment for various diseases in the clinic. Among the successful cases, Traditional Chinese Medicinal (TCM) formulae can achieve synergistic effects in therapeutics and antagonistic effects in toxicity. However, characterizing the underlying molecular synergisms for the combination of drugs remains a challenging task due to high experimental expenses and complication of multicomponent herbal medicines. To understand the rationale of combination therapy, we investigated Sini Decoction, a well-known TCM consisting of three herbs, as a model. We applied our established diseases-specific chemogenomics databases and our systems pharmacology approach TargetHunter to explore synergistic mechanisms of Sini Decoction in the treatment of cardiovascular diseases. (1) We constructed a cardiovascular diseases-specific chemogenomics database, including drugs, target proteins, chemicals, and associated pathways. (2) Using our implemented chemoinformatics tools, we mapped out the interaction networks between active ingredients of Sini Decoction and their targets. (3) We also in silico predicted and experimentally confirmed that the side effects can be alleviated by the combination of the components. Overall, our results demonstrated that our cardiovascular disease-specific database was successfully applied for systems pharmacology analysis of a complicated herbal formula in predicting molecular synergetic mechanisms, and led to better understanding of a combinational therapy.

Highlights

Combination therapy is a popular treatment for various diseases in the clinic
CVDPlatform was constructed from 984 achieved target proteins related to cardiovascular diseases, 924 CVD drugs that have been either FDAapproved or are in clinical trials, 2080 active chemical compounds associated with therapeutic targets of CVDs, 276 cardiovascular-related pathways, and 350,765 references
In order to obtain a better understanding of the underlying principle of Traditional Chinese Medicinal (TCM), we applied the in silico systems pharmacology approach to analyze the interaction networks between active constituents and targets

Summary

Introduction

Combination therapy is a popular treatment for various diseases in the clinic. Among the successful cases, Traditional Chinese Medicinal (TCM) formulae can achieve synergistic effects in therapeutics and antagonistic effects in toxicity. These platforms were integrated with our established algorithms and programs: GPU-accelerated machine learning algorithms for ligand specificity and function predictions[23,24,25,26,27], molecular fingerprint-based TargetHunter© program for drug target identification[28], and receptor homology modeling and virtual screening approaches for ligand screening of cannabinoid receptor[29,30] All of these techniques have been demonstrated to be effective and efficient, laying the foundation for virtual screening, target identification, and network systems pharmacology studies[18,22,31]

Methods

Results

Conclusion