Traditional Chinese Medicine-Based Network Pharmacology Could Lead to New Multicompound Drug Discovery

Miao Jiang,Li Li,Na Lin,Aiping Lu,Cheng Lu,Jian Li,Xuyan Niu,Hongtao Guo,Zhaoxiang Bian

doi:10.1155/2012/149762

Abstract

Current strategies for drug discovery have reached a bottleneck where the paradigm is generally “one gene, one drug, one disease.” However, using holistic and systemic views, network pharmacology may be the next paradigm in drug discovery. Based on network pharmacology, a combinational drug with two or more compounds could offer beneficial synergistic effects for complex diseases. Interestingly, traditional chinese medicine (TCM) has been practicing holistic views for over 3,000 years, and its distinguished feature is using herbal formulas to treat diseases based on the unique pattern classification. Though TCM herbal formulas are acknowledged as a great source for drug discovery, no drug discovery strategies compatible with the multidimensional complexities of TCM herbal formulas have been developed. In this paper, we highlighted some novel paradigms in TCM-based network pharmacology and new drug discovery. A multiple compound drug can be discovered by merging herbal formula-based pharmacological networks with TCM pattern-based disease molecular networks. Herbal formulas would be a source for multiple compound drug candidates, and the TCM pattern in the disease would be an indication for a new drug.

Highlights

Completed in 2003, the human genome project plunged the world into the postgenomic era aimed at understanding the global function of the genome through systems biology, mathematics, and computational techniques [1]
Li et al established a method called distancebased mutual information model (DMIM), and through which they demonstrated that six herbs in Liu-wei-di-huang (LWDH) formula connected closely with common responsive genes enriched in cancer pathways and neuroendocrineimmune pathways, and LWDH formula-treated diseases shared an overlapped molecular basis associated with the angiogenic processes as well as the imbalance of the human body [32]
We have chosen protein targets of the compounds in the herbal formula consisting of Radix Aconiti Praeparata (Fuzi), Herba Asari (Xixin), and Ramulus Cinnamomi (Guizhi) which were found good for the treatment of rheumatoid arthritis (RA) with cold pattern by text mining, pharmacological networks for the multiple compound new drug candidates were built up by ingenuity pathway analysis (IPA) and protein-protein interaction analysis after collecting their target proteins from PubChem

Summary

Introduction

Completed in 2003, the human genome project plunged the world into the postgenomic era aimed at understanding the global function of the genome through systems biology, mathematics, and computational techniques [1]. Organic life is a nonlinear system involving all kinds of interactions between networks of biomacromolecules, cells, drugs, and each other [3], and the “one drug for one gene for one disease” model failed to work because one drug often has many targets, and many protein targets are targeted by more than one drug [4, 5] These insights triggered a major change in the strategies adopted in the new drug discovery: the shift from single compound drugs to multiple compound drugs. The major hurdles in the multiple compound new drug discoveries are how to identify the TCM pattern in a disease and build up the pharmacological network of herbal formula. By integrating the TCM pattern molecular network and the pharmacological network of herbal formulas, which we would like to call as TCM-based network pharmacology, could be a novel way to lead to multiple compound drug discoveries

TCM Pattern-Based Disease Molecular Networks

Herbal Formula-Based Pharmacological Networks

TCM-Based Network Pharmacology in Multiple Compound New Drug Discovery

Perspectives and Conclusions