A Traditional Chinese Medicine (TCM) formula is a collection of several herbs. TCM formulae have been used to treat various diseases for several thousand years. However, wide usage of TCM formulae has results in rapid decline of some rare herbs. So it is urgent to find common available replacements for those rare herbs with the similar effects. In addition, a formula can be simplified by reducing herbs with unchanged effects. Based on this consideration, we propose a method, called “formula pair,” to replace the rare herbs and simplify TCM formulae. We show its reasonableness from a perspective of pathway enrichment analysis. Both the replacements of rare herbs and simplifications of formulae provide new approaches for a new formula discovery. We demonstrate our approach by replacing a rare herb “
Traditional Chinese Medicine is an ancient system used in disease treatments for several thousand years already [
An herb normally has five attributes: they have nature, taste, channel tropism, functions, and indications [
A formula usually contains many active compounds. These compounds target many molecules in the cell and work together to increase therapeutic efficacy and reduce adverse effects [
The availability of some herbs has a rapid decline with their wide usage [
Herb switches and simplification in a formula have been tested. For example, “Liu-wei-di-huang” (LWDH) [
We collected 4,343 formulae and 6,171 herbs from SIRC/TCM database (
Combinational degree refers to the similarity between two formulae. The CD was calculated to evaluate combinational degree between two formulae based on the herbs they share and the weights of shared herbs. Assuming there are two formulae
The CD of
An example is shown in Table
Weight of each herb in
Formula | herb 1 | herb 2 | herb 3 | herb 4 | herb 5 | herb 6 | herb 7 |
---|---|---|---|---|---|---|---|
|
1 | 0.8 | 0.6 | 0.4 | 0.2 | ||
|
1 | 0.75 | 0.5 | 0.25 |
We calculated all formula pairs of 4,343 formulae. The generated values for those CDs are from 0 to 7.5; we then normalized them to
DOSim [
For a pair of formulae with a
To evaluate whether the attributes of two herbs are similar or not, a sore system was constructed for the purpose. For the five attributes in a formula, we define each one with a weight of 1. Based on a previous study, the detailed algorithms are as follows.
(1) The four natures of an herb are represented as
An example is shown in Table
Values of natures for herb
Cold | Cool | Warm | Hot | |
---|---|---|---|---|
Herb |
0.25 | 0.25 | 0.25 | 0.25 |
Herb |
0.8 | 0 | 0 | 0 |
(2) The five tastes are represented as
(3) The twelve channel tropisms are represented as
(4) The numbers of functions for herbs
An example is shown in Table
Functions and
Herb |
Function 1 | Function 2 | Function 3 | Function 4 | Function 5 |
---|---|---|---|---|---|
Herb |
Function 2 | Function 4 | Function 6 | Function 7 |
(5) The numbers of indications for herbs
So, attribute similarity (AS) of herb
If herbs
It has been a long history to use herbs to treat diseases. Herbs usually are any part of plants or certain animals with their medicinal effects. Since rare herbs decline rapidly with their wide usage, they face great threat of extinction. To protect those invaluable plants or animals, it is urgent to find the replacement for the formulae with rare herbs. Meanwhile, formulae are not changeless and can be simplified for the cost efficiency and availability. However, the prerequisites for replacements of rare herbs and simplifications of existed formulae are that the new formulae should not change the medical effects compared to original ones. According to this concept, we designed related strategy and used it to computationally detect the possibility of the replacement for all of the formulae we collected.
Combinational degree refers to the similarity of two formulae; the smaller the degree, the less similarity between two formulae. Accordingly, the formula pairs with
The replacement of herb
Herbs in SSJY, SKT, and SJZBY.
Formula | Herbs | |||
---|---|---|---|---|
SJYJJS | Mulberry leaf | Chrysanthemum |
|
Reed rhizome |
Common hogfennel root | Bitter apricot kernel | Platycodon root | Liquorice | |
SKT | Mulberry leaf | Fermented soybean | Thunberg fritillary bulb | Radix adenophorae |
White mulberry root-bark | Cape jasmine fruit | Bitter apricot kernel | Liquorice | |
SJZBY | Mulberry leaf | Chrysanthemum | Thunberg fritillary bulb | Reed rhizome |
Common hogfennel root | Bitter apricot kernel | Platycodon root | Liquorice |
SSJY and SKT, meet the requirements in the replacement model based on the following results: in SSJY,
So, we replaced “
To simplify a formula, we also built a model. For a formula pair with
Assuming formulae if if if if if if
Workflow of simplification.
For example, both formulae “the fifth of Du Huo Ji Sheng Tang plus/minus herbs” (FDHJST) and “Fang Feng Tang” (FFT) can treat rheumatoid arthritis (RA). FDHJST includes 15 herbs (Table
Herbs in FDHJST, FFT, and FFDHT.
Formula | Herbs | ||
---|---|---|---|
DHJSTJJF | Root of doubleteeth pubescent angelica | Mistletoe | Radix gentianae macrophyllae |
Radix saposhnikoviae | Manchurian wildginger | Chinese angelica | |
Szechwan lovage rhizome | Chinese herbaceous peony | Drying rehmannia root | |
Bark of eucommia | Radix achyranthis bidentatae | Ginseng root | |
Tuckahoe | Cassia bark | Liquorice | |
FFT | Radix saposhnikoviae | Chinese angelica | Radix gentianae macrophyllae |
Cassia twig | Notopterygium root | Bitter apricot kernel | |
Tuckahoe | Liquorice | ||
FFDHT | Radix saposhnikoviae | Chinese angelica | Radix gentianae macrophyllae |
Tuckahoe | Root of doubleteeth pubescent angelica | Liquorice |
To further verify that our formula replacement is relevant from biomedical view, we carried out pathway enrichment analysis with those target proteins for each formula. Protein targets of herbs in each formula were obtained from TCMID [
Top 20 pathways enriched by shared targets of SSJY and SKT with
Number | Pathway name |
|
---|---|---|
1 | Leishmaniasis |
|
2 | Pathways in cancer |
|
3 | Pertussis |
|
4 | HTLV-I infection |
|
5 | Chagas disease (American trypanosomiasis) |
|
6 | T-cell receptor signaling pathway |
|
7 | Cytokines and inflammatory response |
|
8 | Measles |
|
9 | Legionellosis |
|
10 | Amoebiasis |
|
11 | Free radical-induced apoptosis |
|
12 | Cytokine network |
|
13 | African trypanosomiasis |
|
14 | IL-5 signaling pathway |
|
15 | Colorectal cancer |
|
16 | Influence of Ras and Rho proteins on G1 to S transition |
|
17 | NF- |
|
18 | Rheumatoid arthritis |
|
19 | Toll-like receptor signaling pathway |
|
20 | Signal transduction through IL1R |
|
Among the top 20 pathways enriched by those 78 shared targets, we found that the pathway of cytokines and inflammatory response ranked 7th and the pathway of free radical-induced apoptosis ranked 11th. Both the two pathways were closely related to chronic bronchitis.
The results showed that there were six targets enriched in the pathway of cytokines and inflammatory response. They are granulocyte-macrophage colony-stimulating factor (GM-CSF), tumor necrosis factor (TNF), interleukin-2 (IL-2), interleukin-4 (IL-4), interleukin-6 (IL-6), and interleukin-10 (IL-10).
Inflammation has been proved to be a central factor to the development and progression of chronic bronchitis [
Another pathway closely connected with chronic bronchitis is free radical-induced apoptosis. It has been reported that apoptosis of structural cells in the lung may contribute to the pathogenesis of chronic bronchitis [
The new formula, SJZBY, also includes the same 78 targeted proteins. Therefore, it is reasonable to say that SJZBY should have the similar effect on the treatment of chronic bronchitis. Pathway enrichment analysis for shared targets of those formulae shows the reasonableness of this replacement.
Pathway enrichment analysis was also applied to explore the potential mechanism for formula simplification. We collected the potential targets for formulae—FDHJST, FFT, and FFDHTl; they are 182, 133, and 95 proteins, respectively. The results show that targets of FDHJST, FFT, and FFDHT are enriched in 73, 64, and 53 pathways with
Top 20 pathways enriched by targets of FDHJST with
Number | Pathway name |
|
---|---|---|
1 | Pathways in cancer |
|
2 | Cytokines and inflammatory response |
|
3 | Colorectal cancer |
|
4 | Cytokine network |
|
5 | Malaria |
|
6 | Chagas disease (American trypanosomiasis) |
|
7 | Pancreatic cancer |
|
8 | Amoebiasis |
|
9 | Bladder cancer |
|
10 | Leishmaniasis |
|
11 | Pertussis |
|
12 | Tuberculosis |
|
13 | Legionellosis |
|
14 | Rheumatoid arthritis |
|
15 | Small cell lung cancer |
|
16 | Chronic myeloid leukemia |
|
17 | Prostate cancer |
|
18 | HTLV-I infection |
|
19 | Influenza A |
|
20 | African trypanosomiasis |
|
Top 20 pathways enriched by targets of FFT with
Number | Pathway name |
|
---|---|---|
1 | Pathways in cancer |
|
2 | Colorectal cancer |
|
3 | Cytokines and inflammatory response |
|
4 | Cytokine network |
|
5 | Prostate cancer |
|
6 | Amoebiasis |
|
7 | Pancreatic cancer |
|
8 | Chagas disease (American trypanosomiasis) |
|
9 | Chronic myeloid leukemia |
|
10 | Pertussis |
|
11 | Leishmaniasis |
|
12 | Apoptotic signaling in response to DNA damage |
|
13 | Tuberculosis |
|
14 | Small cell lung cancer |
|
15 | Influence of Ras and Rho proteins on G1 to S Transition |
|
16 | p53 signaling pathway |
|
17 | Toxoplasmosis |
|
18 | Measles |
|
19 | Malaria |
|
20 | HTLV-I infection |
|
Pathways enriched by targets of FFDHT with
Number | Pathway name |
|
---|---|---|
1 | Pathways in cancer |
|
2 | Colorectal cancer |
|
3 | Prostate cancer |
|
4 | p53 signaling pathway |
|
5 | Pertussis |
|
6 | Small cell lung cancer |
|
7 | Influence of Ras and Rho proteins on G1 to S transition |
|
8 | Endometrial cancer |
|
9 | Pancreatic cancer |
|
10 | Amyotrophic lateral sclerosis (ALS) |
|
11 | Cytokines and inflammatory response |
|
12 | Bladder cancer |
|
13 | Tuberculosis |
|
14 | Amoebiasis |
|
15 | Apoptosis |
|
16 | HTLV-I infection |
|
17 | Cytokine network |
|
18 | RB tumor suppressor/checkpoint signaling in response to DNA damage |
|
19 | Apoptotic signaling in response to DNA damage |
|
20 | Chronic myeloid leukemia |
|
In those top 20 pathways enriched by targets of FDHJST, we found that the pathway of cytokines and inflammatory response were closely connected with RA. The result showed that the
A previous report has confirmed that antagonism of GM-CSF represents a novel therapeutic approach for a variety of autoimmune-mediated inflammatory diseases, including RA [
For those interleukins, IL-6 and IL-8 can be found in RA pathway in KEGG pathway annotation [
Among those top 20 enriched pathways by targets of FFT, the pathway of cytokines and inflammatory response was closely connected with RA. The result showed that this pathway ranked third among the top 20 pathways according the
After simplification, the resulting new formula, FFDHT, was also enriched in the pathway of cytokines and inflammatory response with the
Many herbs used in Traditional Chinese Medicine are endangered, such as tiger bone used to treat rheumatism. Its widely usage results in the rapid decline of tigers with the poaching and illegal trade, which push tigers to extinction [
Moreover, we also proposed a method to simplify formulae based on the similar rationale. A new formula can be formulated with “less herbs but same effect” concept to the original one. Pathway enrichment analysis also shows the reasonableness of the simplification. Our approaches provide an alternative way to reformulate those traditional prescriptions.
Although herbs have been widely used for thousands of years, most of their targets are still unclear and the mechanisms underling their effects remain unknown. And that has strongly prevented the modernization of traditional Chinese Medicine. For example, in the method of score system of attributes’ similarities for herb pairs, we found that “rhinoceros horn” and “Buffalo Horn” have high attributes’ similarity (
In this work, both replacement of rare herbs and simplification of formulae were computationally tested; our approaches provide an alternative way for new TCM formulation and mechanism inference. To fully verify our method and test the effects of those new formulae, more preclinical experiments need to be conducted. By the combination of
The authors are grateful to Ms. Bingxing Lu for her help in paper preparation. This work was supported by the National 973 Key Basic Research Program (Grant no. 2010CB945401 and 2012CB910400), the National Natural Science Foundation of China (Grant no. 31171264, 31071162, 31000590, and 81171272), and the Science and Technology Commission of Shanghai Municipality (11DZ2260300).