Perspective
Acta Pharmacologica Sinica advance online publication, 13 Apr 2015; doi: 10.1038/aps.2015.8
Efficacy-oriented compatibility for component-based Chinese medicine
- 1Tianjin State Key Laboratory of Modern Chinese Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin 300193, China
- 2Pharmaceutical Informatics Institute, Zhejiang University, Hangzhou 310058, China
- 3Chinese Academy of Chinese Medical Science, Beijing 100700, China
Correspondence: Bo-li Zhang, E-mail zhangbolipr@163.com
Received 12 November 2014; Accepted 3 March 2015
Advance online publication 13 April 2015
Advance online publication 13 April 2015
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Abstract
Single-target
drugs have not achieved satisfactory therapeutic effects for complex
diseases involving multiple factors. Instead, innovations in recent drug
research and development have revealed the emergence of compound drugs,
such as cocktail therapies and “polypills”, as the frontier in new drug
development. A traditional Chinese medicine (TCM) prescription that is
usually composed of several medicinal herbs can serve a typical
representative of compound medicines. Although the traditional
compatibility theory of TCM cannot be well expressed using modern
scientific language nowadays, the fundamental purpose of TCM
compatibility can be understood as promoting efficacy and reducing
toxicity. This paper introduces the theory and methods of
efficacy-oriented compatibility for developing component-based Chinese
medicines.
Keywords:
efficacy-oriented compatibility; component-based Chinese medicine; traditional Chinese medicine; multi-target drug
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Introduction
Human
disease patterns have changed drastically in recent decades. At
present, chronic complex diseases such as coronary heart disease,
stroke, diabetes, cancer and chronic obstructive pulmonary disease are
common and drain large amounts of healthcare resources. As a
consequence, medical purposes and models have been transformed. Recent
advances in health sciences have revealed accumulating evidence of the
limitations of the current one-drug-one-target lock-and-key model1.
As a result, combination therapies, such as multi-component drugs for
multiple targets, are gaining increasing attention and are considered as
the next paradigm in drug discovery1,2.
For example, Caduet, a combination of amlodipine and atorvastatin
calcium, was approved by the US Food and Drug Administration (FDA) in
2004 for the treatment of hypertension and hypercholesterolemia.
Traditional
Chinese medicine (TCM) prescriptions, which are usually composed of
several medicinal herbs, are typical representative of compound
medicines. After thousands of years of clinical practice, a large number
of TCM treatments have been demonstrated to be of significant efficacy
and proven safety. In contrast to the simple addition of several
compounds to form a superpill, a TCM prescription follows the principle
of compatibility (peiwu) instead of simple stack of herbs. The
compatibility principles of TCM prescriptions include considerations of
herbal property (hot, cold, warm and cool), herbal taste (acidic, sweet,
bitter, pungent and salty), and trend of drug action (meridian entry,
up and down, floatation and sinking, and open and close). Although TCM
theories are difficult to be expressed in modern scientific language,
the fundamental purpose of TCM compatibility is clear and is the same as
that of modern medicine: to increase efficacy and reduce toxicity.
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Component-based Chinese medicine
The
basic and most important questions closely related to understanding and
guiding the clinical practice of TCM are the effective composition and
the mechanism of action of a TCM prescription. However, neither question
has been well elucidated due to their complexity. Moreover, it remains
an insurmountable challenge to clarify the active materials and
mechanisms of herbal decoctions or preparations made from Chinese
medicinal materials. Furthermore, the quality standards of TCM
preparations are not well established, especially regarding the
stability and homogeneity among batches. To understand how TCM treats
disease and to improve the quality control level, the model and approach
for research and development (R&D) of new TCM drugs should be
innovated.
TCM preparations, which are made from raw
herbal slices according to the compatibility theory of TCM, display
certain clinical effects. However, their effective materials and their
mechanisms of action and safety are not well established; the quality
control level is low; and dosages are based on experience and ancient
literature. By contrast, natural drugs are mostly made from extractions
of single herbs with a fixed ratio of compounds. Research data regarding
the effective materials, mechanisms of action, dosages, efficacy and
safety of natural drugs are rich and available. Based on solid research
foundation, the quality control of natural drugs is well conducted (Table 1).
However, by neglecting the compatibility theory of TCM in clinical
experience, natural drugs lose the advantage of compound medicines for
complex diseases.
A
new approach to develop modern Chinese medicine should combine the
strong points of both TCM and natural drugs. Under the support of the
National Key Basic Research Project on key scientific problems of TCM
prescriptions, we previously proposed the concept of component-based
Chinese medicine (CCM)3.
CCM
is a type of modern Chinese medicine made from standard components
following the compatibility theory and principles of TCM. The standard
components are extractions of medicinal herbs or TCM prescriptions with
fixed ingredients and ratios. Standard components, not clearly
identified compounds, are a group of active materials made using
standardized extraction, separation, and purification methods and
technologies.
CCMs have the advantages of both TCM and natural drugs (Table 1);
they are guided by the theory and principle of compatibility in TCM yet
contain relatively stabile effective substances and active mechanisms.
In addition, CCMs are characterized by standardized quality control and
stability and validated efficacy, safety and dosage. The active mode of
CCMs is multi-component for multiple targets/pathways involved in
complex disease pathology. Developing modern Chinese medicine by the
compatibility of standard components is innovative in that it maintains
the core advantages of TCM and integrates the technology of modern drug
design. The model of CCM is suitable for developing new drug of small
prescription and for the secondary development of Chinese patent
medicines.
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Paradigm of efficacy-oriented compatibility for component-based Chinese medicine (CCM).
Full figure and legend (46K)Download Power Point slide (244 KB)
Efficacy-oriented compatibility
There
are many processes and techniques for developing CCMs. Composing an
ideal prescription is the key step, and efficacy-oriented compatibility
is a practical approach. The principles and methods for
efficacy-oriented compatibility are summarized below.
Principles
The
principles of efficacy-oriented compatibility are the following:
highlighting the primary effect, considering secondary effects and
reducing adverse effects. On the basis of clinical experience, the
preparation of standard components, analysis of composition-activity
relationships, and prescription optimization should follow these
principles. In addition, efficacy-oriented compatibility is ideal for
developing small prescriptions composed of no more than ten components.
Methods
Generally,
efficacy-oriented compatibility should integrate traditional experience
with modern techniques. The paradigm and related methods of
efficacy-oriented compatibility for CCM are described in Figure 1.
The target disease and its pathological stage are firstly defined.
Then, data mining methods are used to explore the targets and key nodes
related to the disease and to analyze potential effective prescriptions
and components. Using methods of network pharmacology and
high-throughput screening, the candidate prescription is primarily
revised and further evaluated by experimental studies. The candidate
prescription will then be optimized according to the principles stated
above, which is the key link of efficacy-oriented compatibility.
Finally, the optimized prescription should be assessed by clinical
trials (Figure 1). Some of the available techniques are summarized below.
Figure 1.
Full figure and legend (46K)Download Power Point slide (244 KB)
Data mining
Along
with the rapid development of science and technology, significant
progress has been made in the understanding of life at the cellular and
molecular levels. Targets associated with certain diseases have been
gradually discovered, and the currently identified targets for disease
treatment are countable4.
Potential targets associated with disease are mostly reported in the
scientific literature and biological databases. For example, the most
popular biomedical literature database, MEDLINE/PubMed, currently
contains more than 18 million literature abstracts, and more than 60 000
new abstracts are added monthly. Similarly, chemical, genomic,
proteomic and metabolic data are collected in the MEDLINE database.
Developing in pace with the growth of biological databases, the
flourishing of bioinformatics, especially data mining approaches, has
changed the methods of target discovery5.
Currently, text mining of literature databases and microarray data
mining are the two prevailing approaches to target discovery6. Text mining has been broadly applied to identify disease-associated genes/proteins and to understand their roles in diseases7,8.
The systematic approach is a strategy that selects targets through the
study of diseases in whole organisms using information derived from
clinical trials and in vivo animal studies. Researchers can identify disease-associated networks and predict key nodes automatically by data mining9,10.
Although data mining is very useful for deriving biological entities
and insights from a large number of research articles, it is a
preliminary strategy that requires validation by experimental studies.
Database of standard herbal components
For
drug discovery, historical experience is always significant. Indeed,
many TCM prescriptions have been used for thousands of years. Thus, CCM
should adequately utilize ancient records and clinical experience. With
innovations in analytic technology and equipment, it becomes possible
and easier to determine the constituents of single herbs or
prescriptions. The ingredients of approximately 400 herbs that are
commonly used in TCM have been gradually identified. We have established
a component materials warehouse and database for herbal components,
which is a resource for developing new prescriptions for multiple
targets. Specifically, more than 20 000 standard herbal components have
been extracted from commonly used medicinal herbs and prescriptions.
In
cooperation with the TCM research team at Zhejiang University, we
developed an in silico approach to predict potential targets of herbal
ingredients based on known relationships between FDA-approved drugs and
their targets. The performance of predictive models was evaluated by
cross-validation and external datasets, which achieved good predictive
accuracy. The models were then applied to 10 339 TCM ingredients,
resulting in 6670 predicted ingredient-target relationships with high
confidence. The TCM potential target database (TCM-PTD) is now freely
accessible online (http://tcm.zju.edu.cn/ptd).
Network pharmacology
Network
analyses of biological pathways and interactions have revealed that
much of the robustness of biological systems is derived from the
structure of the network11,12.
Drugs with multiple ingredients aimed at multiple targets may show
better effects on the complex equilibrium of whole cellular networks
than drugs that act on a single target. Additionally, systematic
drug-design strategies should be more efficient than simple combinations
of several compounds13.
Integrating network biology and polypharmacology holds the promise of
expanding the number of druggable targets. Advances in these areas are
creating the foundation of network pharmacology for drug discovery14.
Network analysis does not preclude the identification of individual
targets, yet the key challenge facing the development of network
pharmacology is identifying a node or combination of nodes in a
biological network whose perturbation results in a desired therapeutic
outcome15,16.
Biological databases, data mining and databases of herbal components
provide the basic conditions for network pharmacology research.
High-throughput screening (HTS)
Network
pharmacological research can develop a candidate prescription based on
herbal components. The next step is to optimize the components and
proportions of the candidate prescription. HTS is a well-established
process in discovery for pharmaceutical and biotechnology companies and
is increasingly applied to research in academia and medical
institutions. HTS has evolved into a mature discipline of modern drug
discovery. Tens of thousands to millions of samples are tested in HTS
campaigns for their ability to modulate biochemical targets in cell-free
assays and/or phenotypic or targeted cell-based assays17.
However, the application of HTS for the identification of biologically
active natural products, such as TCM libraries, remains a relatively
uncommon activity.
The targets and cellular phenomena
amenable to HTS include nuclear receptors, G protein-coupled receptors
(GPCRs), ion channels, protein kinases, proteases, signaling pathways,
cell death mechanisms and others. For each category of targets commonly
subjected to HTS, natural product modulators have been identified18.
A strategy for the production of high-quality fractionated libraries of
Chinese herbal formulas for HTS was first introduced by Liu et al19.
A team of US and Chinese co-investigators with expertise in TCM,
botany, chemistry and drug discovery has jointly established a prototype
library consisting of 202 authenticated medicinal plant and fungal
species that collectively represent the therapeutic content of the
majority of commonly prescribed TCM herbal prescriptions. Initial
screening targets have been applied to preliminary evaluations of 3709
TCM fractions from 82 authenticated TCM species20.
Developments
in techniques for component characterizing, biological evaluation and
other screening methods under the perspective of their applicability in
natural product have been described in an article by Zhu21. In particular, HTS is likely to increase success in modern drug discovery from TCM.
A case
Myocardial
infarction (MI) is a typical polygenic disease. Anti-platelet drugs,
beta-blockers, angiotensin-converting enzyme (ACE) inhibitors, and
statins have been recommended for clinical practice based on the results
of randomized clinical trials and their systematic reviews. However,
most of these conventional drugs are based on specific pathways, mainly a
single drug acting on a single target. This means that a patient might
need to take several drugs concurrently, which leads to new problems,
such as low adherence, high cost, and more adverse effects22.
Thus, a new strategy for the management of patients following MI is
needed. The concept of “polypill” was developed approximately 12 years
ago, with a compound pill including several conventional drugs23.
The Indian Polycap Study showed that a polypill composed of
hydrochlorothiazide, atenolol, ramipril, simvastatin and aspirin had the
desired effects and was as safe as the individual pills24. The polypill is a new concept in Western medicine, but it is not new in TCM.
The Qi-Shen-Yi-Qi (QSYQ) pill, a type of polypill for treating MI, is a CCM25. QSYQ is composed of extracts from 4 herbs: Radix Astragalus membranaceus (Huangqi), Radix Salvia miltiorrhiza (Danshen), Panax notoginseng (Sanqi) and Lignum Dalbergiae Odoriferae (Jiangxiang). These herbs constitute the QSYQ pill based on efficacy-oriented compatibility principles.
Over the past several years, in vivo and in vitro
studies have revealed the integrated effects of QSYQ for MI, including
protection of cardiac muscle cells, prevention of cardiac
ischemia-reperfusion injury via energy modulation, antagonized
ventricular remodeling, inhibition of the inflammatory reaction and the
progression of atherosclerosis, and stabilization of atherosclerotic
plaques through changes in histological constitution26,27,28,29,30,31,32.
Recently, a network pharmacology study further revealed the underlying
multi-compound, multi-target and multi-pathway mode of action (MOA) of
QSYQ31.
This study evidentially confirmed the roles of the QSYQ component herbs
in the primary effect of treating MI: Huangqi serves as the sovereign,
Danshen as the minister, Sanqi as the assistant and Jiangxiang as the
courier32.
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Perspective
Single-target
drugs have showed only limited success for multi-factor diseases, which
is why the success rate of new drugs is low despite careful and
considerable efforts. The fundamental problem may not be technological,
but philosophical: the wrong approach to drug discovery has been
followed. In the field of new drug R&D, ideas and methods are
undergoing innovation, and compound drug development is becoming the
cutting edge in new drug development. In contrast to chemical drug
development, which proceeds from the laboratory bench to the clinical
bedside, TCM preparations are generated from clinical practice. The
development of modern or scientific Chinese drugs should begin with
clinical experience and classic prescriptions. The development of modern
science and technology provides powerful support for developing new TCM
drugs. One key point is that R&D of new TCM drugs is inseparable
from the theory of TCM, especially the theory of prescription
compatibility. Efficacy-oriented compatibility is a practical mode for
developing CCM, which also needs further development in practice.
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References
- Medina-Franco JL, Giulianotti MA, Welmaker GS, Houghten RA. Shifting from the single to the multitarget paradigm in drug discovery. Drug Discov Today 2013; 18: 495–501. | Article | PubMed | ISI | OpenURL |
- Sams-Dodd F. Target-based drug discovery: is something wrong? Drug Discov Today 2005; 10: 139–47. | Article | PubMed | ISI | OpenURL | CAS |
- Zhang Bl, Wang Yy. Theories and Methods Used in the Research of Modern Chinese Medicine by Drug Combination Chin J Nat Med 2005; 3: 258–61.
- Szuromi P, Vinson V, Marshall E. Rethinking drug discovery Science 2004; 303: 1795. | Article | ISI | OpenURL |
- Yang Y, Adelstein SJ, Kassis AI. Target discovery from data mining approaches Drug Discov Today 2012; 17: S16–23. | Article | PubMed | ISI | OpenURL |
- Sakharkar MK, Sakharkar KR. Targetability of human disease genes. Curr Drug Discov Technol 2007; 4: 48–58. | Article | PubMed | OpenURL |
- Pospisil P, Iyer LK, Adelstein SJ, Kassis AI. A combined approach to data mining of textual and structured data to identify cancer-related targets. BMC Bioinformatics 2006; 7: 354. | Article | PubMed | OpenURL | CAS |
- Ozgür A, Vu T, Erkan G, Radev DR. Identifying gene-disease associations using centrality on a literature mined gene-interaction network. Bioinformatics 2008; 24: i277–85. | Article | PubMed | ISI | OpenURL | CAS |
- Krauthammer M, Kaufmann CA, Gilliam TC, Rzhetsky A. Molecular triangulation: bridging linkage and molecular-network information for identifying candidate genes in Alzheimer's disease. Proc Natl Acad Sci U S A 2004; 101: 15148–53. | Article | PubMed | ISI | OpenURL |
- Cheng D, Knox C, Young N, Stothard P, Damaraju S, Wishart DS. PolySearch: a web-based text mining system for extracting relationships between human diseases, genes, mutations, drugs and metabolites. Nucleic Acids Res 2008; 36: W399–405. | Article | PubMed | ISI | OpenURL | CAS |
- Albert R, Jeong H, Barabasi AL. Error and attack tolerance of complex networks. Nature 2000; 406: 378–82. | Article | PubMed | ISI | OpenURL | CAS |
- Barabási AL, Oltvai ZN. Network biology: understanding the cell's functional organization. Nat Rev Genet 2004; 5: 101–13. | Article | PubMed | ISI | OpenURL | CAS |
- Csermely P, Agoston V, Pongor S. The efficiency of multi-target drugs: the network approach might help drug design. Trends Pharmacol Sci 2005; 26: 178–82. | Article | PubMed | ISI | OpenURL | CAS |
- Hopkins AL. Network pharmacology: the next paradigm in drug discovery. Nat Chem Biol 2008; 4: 682–90. | Article | PubMed | ISI | OpenURL | CAS |
- Mayer LD, Janoff AS. Optimizing combination chemotherapy by controlling drug ratios. Mol Interv 2007; 7: 216–23. | Article | PubMed | ISI | OpenURL | CAS |
- Ramaswamy S. Rational design of cancer-drug combinations. N Engl J Med 2007; 357: 299–300. | Article | PubMed | ISI | OpenURL | CAS |
- Mayr LM, Fuerst P. The future of high-throughput screening. J Biomol Screen 2008; 13: 443–8. | Article | PubMed | ISI | OpenURL | CAS |
- Curtis J. Henrichand John A. Beutler. Matching the power of high throughput screening to the chemical diversity of natural products. Nat Prod Rep 2013; 30: 1284–98. | Article | PubMed | OpenURL | CAS |
- Liu L, Li YF, Cheng YY. A method for the production and characterization of fractionated libraries from Chinese herbal formulas. J Chromatogr B Analyt Technol Biomed Life Sci 2008; 862: 196–204. | Article | PubMed | OpenURL |
- Eisenberg DM, Harris ES, Littlefield BA, Cao S, Craycroft JA, Scholten R, et al. Developing a library of authenticated Traditional Chinese Medicinal (TCM) plants for systematic biological evaluation-rationale, methods and preliminary results from a Sino-American collaboration. Fitoterapia 2011; 82: 17–33. | Article | PubMed | ISI | OpenURL |
- Zhu Y, Zhang Z, Zhang M, Mais DE, Wang MW, et al. High-throughput screening for bioactive components from traditional Chinese medicine. Comb Chem High Throughput Screen 2010; 13: 837–48. | Article | PubMed | ISI | OpenURL |
- Xing DM, Zhang JH, Li L, Zhu MJ, Shang HC, et al. Intervention effects and safety of cardiovascular Polypill for the relevant risk factors of coronary heart disease: a systematic review. Chin J Evid-based Med 2013; 13: 446–51.
- Wald NJ, Law MR. A strategy to reduce cardiovascular disease by more than 80%. BMJ 2003; 326: 1419. | Article | PubMed | ISI | OpenURL | CAS |
- Indian Polycap Study (TIPS), Yusuf S, Pais P, Afzal R, Xavier D, Teo K, et al. Effects of a polypill (Polycap) on risk factors in middle-aged individuals without cardiovascular disease (TIPS): a phase II, double-blind, randomised trial. Lancet 2009; 373: 1341–51. | Article | PubMed | ISI | OpenURL | CAS |
- Shang H, Zhang J, Yao C, Liu B, Gao X, Ren M, et al. Qi-shen-yi-qi dripping pills for the secondary prevention of myocardial infarction: a randomised clinical trial. Evid Based Complement Alternat Med 2013; 2013: 738391.
- Yan FF, Liu Y, Liu YF, Zhao YX. Effect of Qishenyiqi dripping pills on histology of experimental atherosclerotic plaque. J Nanjing Univ Traditi Chin Med 2007; 23: 295–7.
- Yan FF, Liu Y, Liu YF, Zhao YX. Effects of Qishenyiqi Dripping pills on high sensitivity C reactive protein in experimental atherosclerosis rabbits. Shanghai J Traditi Chin Med 2007; 41: 59–60.
- Du WX, Zhu MD, Feng LM, Song QG, Wei Y, Ma P, et al. Intervention effect of Qishenyiqi dripping pills on early ventricular remodeling after acute myocardial infarction. Chin J Evid Based Cardiovasc Med 2008; 28: 41–3.
- Hong C, Wang Y, Lou J, Liu Q, Qu H, Cheng Y. Analysis of myocardial proteomic alteration after Qishenyiqi formula treatment in acute infarcted rat hearts. Zhongguo Zhong Yao Za Zhi 2009; 34: 1018–21. | PubMed |
- Zhang L, Wang Y, Yu L, Liu L, Qu H, Wang Y, et al. QI-SHEN-YI-QI accelerates angiogenesis after myocardial infarction in rats. Int J Cardiol 2010; 143: 105–9. | Article | PubMed | ISI | OpenURL |
- Li X, Wu L, Liu W, Jin Y, Chen Q, Wang L, et al. A network pharmacology study of Chinese medicine QiShenYiQi to reveal its underlying multi-compound, multi-target, multi-pathway mode of action. PLoS One 2014; 9: e95004. | Article | PubMed | OpenURL |
- Wu L, Wang Y, Li Z, Zhang B, Cheng Y, Fan X. Identifying roles of “Jun-Chen-Zuo-Shi” component herbs of QiShenYiQi formula in treating acute myocardial ischemia by network pharmacology. Chin Med 2014; 9: 24. | Article | PubMed | OpenURL |
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Acknowledgements
This
work was supported by the National Key Basic Research Program of China
(2012CB518404); the Ministry of Education of China-Program for
Innovative Research Team (IRT1276); and the New Century Excellent Talent
of Ministry of Education of China (NCET-13-0936).