research article herb network analysis for a famous tcm...

Research ArticleHerb Network Analysis for a Famous TCM DoctorrsquosPrescriptions on Treatment of Rheumatoid Arthritis

Yan Li1 Rui Li2 Zibo Ouyang2 and Shao Li2

1Yijishan Hospital Wannan Medical College Wuhu 241001 China2MOE Key Lab of Bioinformatics Bioinformatics Division TNLIST Department of AutomationTsinghua University Beijing 100084 China

Correspondence should be addressed to Shao Li shaolimailtsinghuaeducn

Received 28 October 2014 Revised 20 January 2015 Accepted 20 January 2015

Academic Editor Jairo K Bastos

Copyright copy 2015 Yan Li et al This is an open access article distributed under the Creative Commons Attribution License whichpermits unrestricted use distribution and reproduction in any medium provided the original work is properly cited

Traditional Chinese Medicine (TCM) doctors always prescribe various herbal formulae tailored to individual patients Howeverthere is still a lack of appropriate methods to study the rule and potential biological basis underlying the numerous prescriptionsHerewe developed anHerb-Compound-Target-Disease coherent network approach to analyze 871 herbal prescriptions fromaTCMmasterMr Ji-Ren Li in his clinical practice on treatment of rheumatoid arthritis (RA)The core herb networks were extracted fromMr Lirsquos prescriptions Then we predicted target profiles of compounds in core herb networks and calculated potential synergisticactivities among them We further found that the target sets of core herbs overlapped significantly with the RA related biologicalprocesses and pathways Moreover we detected a possible connection between the prescribed herbs with different properties suchas Cold andHot and theWestern drugs with different actions such as immunomodulatory and hormone regulation on treatment ofRA In summary we explored a new application of TCMnetwork pharmacology on the analysis of TCMprescriptions and detectedthe networked core herbs their potential synergistic and biological activities and possible connections with drugsThis work offersa novel way to understand TCM prescriptions in clinical practice

1 Background

Traditional ChineseMedicine (TCM) is one of the most trea-sured cultural heritages in China and is also an inseparablepart of current medical systems Herbal formula (Fang-Ji inMandarin) that consists of two ormoremedicinal herbs is themajor form in TCM clinical practice Nowadays TCM herbalformula has been well known to be effective for the controlof many complex diseases for example rheumatoid arthritis(RA) a common autoimmune disease that leads to a chronicand systemic inflammatory disorder [1 2] Rheumatoidarthritis is manifested by synovial inflammation morningstiffness and pain and may affect many tissues and organs inhuman body especially causing joint deformity Rheumatoidarthritis is a complex disease with limited treatment optionsWithout regular treatment many patients tend to suffer fromhigh probability of disability TCM has been regarded as animportant strategy to inhibit RA development and improve

the life quality of RA patients [3] Actually the treatmentof RA in TCM can be traced up to more than 3000 yearsago RA falls in the scope of the TCM therapeutic conceptldquoBi ZHENGrdquo The etiologies syndrome classification andtreatment of Bi ZHENG had been recorded in the YellowEmperorrsquos Internal Classic one of the earliest treatises inTCM Subsequently TCM practitioners have accumulatedrich clinical experience and numbers of herbal formulae fortreating patients with rheumatoid arthritis As one of the first30 ldquoGrandMasters of TCMrdquo selected byChinese governmentMr Ji-Ren Li at Yijishan Hospital Wannan Medical Collegeis a highly regarded Chinese medicine practitioner who isskilled in the treatment of RA [4 5] Mr Li has accumulatednumerous herbal prescriptions to cure RA patients and earlyaction needs to be taken to understand the professionalexperience embedded in such valuable herbal prescriptions

However quite different from the clinical practice of theWestern medicine herbal formulae are always prescribed by

Hindawi Publishing CorporationEvidence-Based Complementary and Alternative MedicineVolume 2015 Article ID 451319 9 pageshttpdxdoiorg1011552015451319

2 Evidence-Based Complementary and Alternative Medicine

TCMpractitioners specifically tailored to individual patientsTCM doctors treat patients mainly based on syndrome dif-ferentiation For different patients various herbs are groupedand different formulae are prescribed This tradition andfeature make TCM a kind of personalized medicine andcause great difficulty in designing standard protocols suchas the randomized controlled trial in TCM studies Thelack of appropriate methods to analyze the rule as well asscientific basis for TCM-doctor-prescribed herbal formulaeis therefore one of the major frustrations to find clinicalevidence of TCM How to study the characteristics andprescription rule of such flexible TCM formulae is still a greatchallenge and requires widely interdisciplinary efforts

Thanks to the rapid progress of bioinformatics especiallycomplex network theory and technologies recently thenetwork approach has become a new avenue and powerfultool to handle intricate problems such as those in TCMWe have been making efforts to build a TCM networkpharmacology approach over ten years and established aset of network-based methods for TCM study [6ndash9] Forexample to reveal the combination rule and the biologicalbasis of herbal formulae we proposed a global networkanalysis framework consisting of herbcompound networkbiological network (gene protein or target network) anddisease network Several methods are also created suchas a distance-based mutual information model (DMIM)that can identify herb relationships from numerous herbalformulae The good performance of the DMIM method touncover the herbal combination rules has been illustrated inboth 3865 collaterals-related herbal formulae and a classicLiu-Wei-Di-Huang formula [6] Furthermore we proposeda novel concept of ldquonetwork targetrdquo [7] which treats adisease-specific molecular network as a therapeutic targetto help design suitable medical treatments Several methodsfor the network target analysis especially the disease geneprediction target prediction for drugs or herbal compounds[8] the network comodule analysis for drug discovery andthe network-based prioritization of synergistic combinations[7] are developed subsequently These methods have beenapplied in finding bioactive compounds and revealing themechanism of action for herbal formulae including Liu-Wei-Di-Huang pill [9] Now the network-based method inthe context of TCM network pharmacology has become aburgeoning field in the modern studies of TCM [10ndash12] Webelieve the network-based strategy and approaches can alsoprovide good solutions for the herbal prescription analysis

In this work 871 herbal prescriptions from Mr Ji-Ren Lirsquos clinical treatment on patients with rheumatoidarthritis were analyzed from a network point of view TCMnetwork pharmacology methods were employed to detectthe common rules and potential biological basis of theseherbal prescriptions This work is promising as the resultsnicely show the rationality and validity of Mr Lirsquos herbalprescriptions Moreover this work provides a new route tointerpret the professional experience embedded in numerousand precious TCM herbal prescriptions

Herbal prescriptions

Herbnetwork

Compound network

Herb name normalization

Herb relationship byDMIM scoring

Herb compoundcollection

Target prediction by drugCIPHER

Connect compound by target interaction

Disease gene network

Evaluation of synergistic activity by NIMS

Figure 1 The Herb-Compound-Target-Disease coherent networkanalysis framework for studying herbal prescriptions on the treat-ment of certain diseases

2 Methods

21 Herbal Formulae and Herbal Compounds A total of 871herbal prescriptions from Mr Ji-Ren Li in the individuallyclinical treatment of RA patients from 2005 to 2013 were usedin this work The 871 herbal prescriptions were normalizedby substituting the polysemes synonyms and acronyms ofthe herbs in the dataset and resulted in a standardized HerbName list Each formula contains 15 to 29 herbs and the aver-age number is 18 Compounds of herbs were gathered fromthe HerbBioMap database (China Copyright of ComputerSoftware 2011SR076502)TheHerbBioMapdatabase contains10806 compounds for 539 herbs up to now

22 Multilayer Coherent Network Analysis for Herbal Pre-scriptions As shown in Figure 1 we proposed an Herb-Compound-Target-Disease coherent network analysis frame-work to study the prescription rules and potential biologicalbasis for herbal prescriptionsThe principle steps are summa-rized as follows

Herb Network Construction We created a matrix of 871dimensions to represent all collected herbal formulae andthen calculated the frequency of every 343 herbs in allformulae and gave a normalized frequency (NF) NF =AFsum119873

119899=1AF1 where AF is accumulated frequency and 119873

denotes 343-herb species number Next most frequent herbsin 871 herbal prescriptions were selected and subjected tothe DMIM (distance-basedmutual informationmodel) anal-ysis an algorithm for identifying herb relationships amongdifferent formulae and uncovering the combinational rulesof herbs in a network manner [6] The DMIM model isan integrated scoring system combining the mutual infor-mation (MI) entropy characteristics and the ldquobetween-herbdistancerdquo (119889) between herbs by calculating score(119909 119910) =MI(119909 119910)119889(119909 119910) which describes the tendency of herb 119909 and

Evidence-Based Complementary and Alternative Medicine 3

herb 119910 to form an herb pair More importantly the DMIMmodel extracts information from the organization of Jun-Chen-Zuo-Shi (Master-Adviser-Soldier-Guide) herbs in anherbal formula based on which a new parameter ldquobetween-herb distancerdquowas created thatmeans the further the distancebetween two herbs in a formula is the less likely they are tobe relevant to one anotherThus DMIM is suitable to retrieveherb combinational rules achieving a good balance amongthe herbrsquos frequency independence and distance in herbalformulae [6]

Target Prediction for Herbal Compounds and Herbs In thepresent study drugCIPHER a method we developed previ-ously [8] is used to predict the target profile for all availablecompounds collected from each herb in the core herbnetworks drugCIPHER is a regressionmodel that can predictthe links between drugs and target proteins in a genome-wide scale by correlating the drug chemical informationand protein-protein interaction (PPI) from a heterogeneousnetwork By integrating and making full use of all currentFDA-approved drug structures drug-target interactions andhuman protein-protein interactions drugCIPHER can out-put a target profile for any given compound with knownstructure that is calculated from the correlation between thequery ingredientrsquos structure similarity vector in the drugspace and the target-related genersquos closeness vector in thetarget space As the top 100 targets predicted by drugCIPHERcan reach the high prediction accuracy (773) [8] here thetop 100 target profiles predicted for each compound wereselected and the target profiles of all collected compoundswithin a herb were combined to form integrative targetprofiles of this herb The target prediction procedure wasconducted for herbs present in the core herb networks orinvolved in the following studies

Evaluation of Synergistic Actions forHerbNetwork To identifythe potential synergistic effects of herb combinations in thecore herb network at the molecular level and in a highthroughput way we used the network-based identificationof multicomponent synergy (NIMS) method [7] a novelapproach to access the synergistic strength of any combina-tion of herbal compounds by determining their target inter-actions in the protein-protein network The NIMS algorithmconsists of two components topology score and agent scoreThe topology score is generated from the topological featuresof the background network related to disease condition anddrug actions while the agent score is based on the similarityof agent phenotypes Two graph-based measures between-ness and closeness were used to capture the associationsamong targets and the other measure PageRank to verifythe node importance [7] The resulted synergy score is usedto prioritize the synergistic effect of combinations of agentsincluding herbs or herbal compounds

Gene Ontology (GO) and Pathway Analysis for Herb Targetsand RAGenesThe targets of each compound in the top herbswere predicted using drugCIPHER For each compound ofthe top herbs the top 100 proteins were treated as targetsfor the given compound The targets hit by more than five

compounds within an herb were considered herb targets Top15 frequent herbsrsquo targets were subjected to the gene ontology[13] and pathway enrichment analysis One the other handthe 129 RA-related genes with a direct mechanism relation-ship to rheumatoid arthritis were collected from the CTDdatabase [14] For functional analysis we used the ldquoSet Ana-lyzerrdquo tool at the CTD site (httpctdbaseorgtoolsanalyzergo) to analyze the enriched GO terms as well as KEGGpathways for herb targets and RA genes respectively withcorrected 119875 value less than 005 We also mapped the RAgenes and herb targets in the enriched KEGG pathwaynetwork

Compound Network Analysis for Anti-RA Herbs and DrugsFor comparison of the herbal prescriptions and the Westernanti-RA drugs we collected the commonly used anti-RAdrugs and their targets from the DrugBank database [15]Nine immunomodulatory drugs and 7 hormones were selec-ted The immunomodulatory drugs include methotrexateleflunomide ciclosporin thalidomide cyclophosphamideazathioprine mycophenolate mofetil tacrolimus and cyclo-sporine Hormones include dexamethasone hydrocortisonecortisone triamcinolone prednisolone prednisone andmethylprednisolone Based on the targets of each compoundcontained by the top 50 frequent herbs the closeness ofherb compoundrsquos targets and targets of immunomodulatorydrugs and hormones on the RA-related gene network thatconnected by PPI interactions (HPRD Release 7) [16] weremeasuredThe compoundnetworks are then formed inwhichtwo compounds (or drugs) will be linked if their targetsare overlapped or directly connected in the network Herewe paid more attention on the relationship between herbalcompounds with ColdHot property and two types of RAdrugs

3 Results and Discussion

31 Core Herb Networks from Herbal Prescriptions 343 herbswere uniquely identified from all 871 prescriptions ByDMIMscoring [6] we obtained frequently used herbs as well as theircombinations from all available prescriptions with Ji XueTeng as the most frequently used herb The top 15 herbs inMr Lirsquos anti-RA herbal prescription are shown in Table 1 Wecan see that although the prescriptions are written out indi-vidually to patients the commonly used herbs with differentproperties are considered to be the most representative ofthe available herbal prescriptions Therefore to capture thecommon rule of herbal prescriptions here we focused onthe most frequent herbs for the subsequent network analysisThenwe conducted the herb network analysis for these herbalprescriptions A node in herb network refers to an herb andan edge connecting two nodes refers to the two significantcooccurrent herbs in herbal prescriptions By using DMIMscore to evaluate the significance of the edge we constructedtwo types of the core herb networks namely the high-frequency herb network and the intersection herb networkfor Mr Lirsquos 871 prescriptions

For the high-frequency network only the top frequentherbs were treated as nodes and the cooccurrence herbs


Table 1 Top 15 herbs in Mr Ji-Ren Lirsquos antirheumatoid arthritis herbal prescriptions

Chinese name Latin name Property Frequency Normalized frequencyJi Xue Teng Millettia reticulata Benth Warm 503 510Huo Xue Teng Sargentodoxa cuneata Neutral 499 506Huang Qi Astragalus membranaceus (Fisch) Bunge Warm 481 487Dang Gui Radix Angelicae sinensis Warm 430 436Quan Xie Scorpio Neutral 399 404Qing Feng Teng Caulis Sinomenii Neutral 396 401Ku Shen Radix Sophorae flavescentis Cold 323 327Wu Tou Aconitum carmichaeli Debx Hot 306 310Wu Gong Scolopendra Warm 287 291Huang Bai Cortex Phellodendri Cold 283 287Bi Xie Rhizoma Dioscoreae Hypoglaucae Neutral 280 284Ren Dong Teng Caulis Lonicerae Cool 257 260Qin Jiao Radix Gentianae macrophyllae Cold 254 257Wu Shao She Zaocys dhumnades Neutral 235 238Pu Gong Ying Taraxacum mongolicumHand-Mazz Cold 227 230

in herbal prescriptions identified by DMIM were treated asedges For example we found that the top 10 frequent herbswith 45 edges are closely interrelatedwith each other formingalmost all connected graphs Among them Ji Xue Teng andHuang Qi (DMIM score = 18627) Huo Xue Teng and Ji XueTeng (DMIM score = 16517) have the highest DMIM scoresThis result suggests that the top 10 herbs are always prescribedin pairs in Mr Lirsquos practice for RA treatment

For the intersection herb network we built every subnet-work by DMIM for each of the top frequent herbs and thenintersected the subnetworks to construct a core networkFor example Figure 2(a) shows the subnetwork around thetop 2 herb Huo Xue Teng (Sargentodoxa cuneata) The topten frequent herb subnetworks contained 21 to 35 nodes and100 to 200 edges and the resulted core intersection networkhas 14 nodes and 29 edges (Figure 2(b)) Interestingly acomplete formula of Mr Li Qing-Luo-Yin [17] is present inthis network

Herbs and herb combinations present in these two typesof herb networks may play a central role in Mr Lirsquos herbalprescriptions for the treatment of RA

32 Potential Synergistic Activities Underlying Core Herb Net-works Taking the core herb networks as examples we fur-ther performed the network target analysis to computation-ally determine whether the DMIM extracted herb networksdisplayed synergistic effects In this step we collected avail-able compounds for the core herb networks identified fromMr Lirsquos prescriptions The target profile of each compoundwas predicted by the drugCIPHER method [8] Then weselected top 100 targets of compounds assembled in eachherb to analyze the synergistic activity by evaluating the tar-get interactions in the protein-protein interaction networkWhen drugCIPHER [8] and NIMS [7] (see Section 2) areapplied to the herb networks we can obviously detect themodular property in themolecular level that denotes the syn-ergistic relationship in the core herb networks (Figure 3(a))From the outputs of the NIMS score we found that in

an herb network not all herbs interact strongly Instead onlycertain herbs or even certain herbal compounds produceclear synergistic effects For example in the high-frequencyherb network Ji Xue Teng and Huo Xue Teng (average NIMSscore = 084) Ku Shen and Qing Feng Teng (average NIMSscore = 057) Ku Shen and Ji Xue Teng (average NIMS score= 04) and Huo Xue Teng and Qing Feng Teng (averageNIMS score = 031) each of the two herbs has a relativelyhigh NIMS score and tends to produce synergistic activity indifferent levels In the intersection herb network the mainconstituent of TCM herbal formulae Qing-Luo-Yin (QLY)also has a good NIMS score A part of the synergistic modulefromQing Feng Teng and Ku Shen was shown in Figure 3(b)This figure further illustrated that different compounds inan herb pair obtained diverse synergistic scores Amongthem the combination of compounds such as Sinomenineand Matrine achieves a relatively high score which agreeswith the previously experimental results on the synergisticeffects in QLY [17] Thus we demonstrate here that thesynergistic effects of herb components may be contributed tothe modular property of the herb network as well as herbalprescriptions

33 Biological Associations between Herb Targets and RAGenes Since the targets of each compound of herbs areavailable by drugCIPHER we further verify the effectivenessof the top 15 frequent herbs in Mr Lirsquos prescriptions (Table 1)by evaluating the herbal compoundsrsquo targets and theirrelationship with RA genes in terms of the GO biologicalprocesses and pathways As shown in Table 2 there are RA-related GO terms resulting from targets of the top 15 herbswhich were also enriched with 129 RA-related genes formthe CTD database For example the overlapped GO termswhich resulted from both herb targets and RA genes includeangiogenesis [18] cytokine production [19] inflammatoryresponse [20] lymphocyte activation [21] and NF-120581B tran-scription factor activity [22] The overlapped GO terms alsoinclude ldquodefense response to bacteriumrdquo which is worthy


Lian Qiao

Hu Zhang Dai MaoRou Gui

Ku Shen

Bi Xie

Wu Shao She

Qin Jiao

Man Jing Zi

Han Lian Cao

Chai Hu

Wu Wei Zi

Bai Mao Gen

Wei Ling Xian

Qing Feng Teng

Zhi Mu

Wu Tou

Huo Xue Teng

Lei Gong Teng

Huang Bai

Ji XueTengHuang Qi

Pu Gong Ying

Ren Dong Teng

(a)

Man Jing Zi

Wu Tou

Bi Xie

Ji Xue Teng

Zhi Mu

Qin JiaoWu Shao She

Ku ShenHuo Xue Teng

Qing Feng Teng

Pu Gong Ying

Lei Gong Teng

Huang Bai

Ren Dong Teng

(b)

Figure 2 The core intersection herb networks constructed fromMr Ji-Ren Lirsquos anti-RA herbal prescriptions (a) The herb subnet-works around each top frequent herb for example Huo Xue Teng(Sargentodoxa cuneata the top 2 herb) (b) The intersection herbnetwork created from the intersection herb networks of the top tenfrequent herbs Four herbs circled by the green line are a completeformula of Qing-Luo-Yin

of further study Note that other nonoverlapping GO termsassociated with herbs such as the steroid hormone receptorsignaling pathway also contributed a lot to the progressof RA [23] Moreover by pathway enrichment analysis wefurther found that both the RA genes and herb targetsare significantly enriched in the pathway of ldquorheumatoidarthritisrdquo (KEGG05323) (corrected 119875 = 155119890 minus 15 for RAgenes and 119875 = 283119890 minus 12 for herb targets resp) Figure 4shows the details of the network associations of RA genesandherb targets in theKEGGldquorheumatoid arthritisrdquo pathwayproviding additional evidence for the anti-RA effects of MrLirsquos herbal prescriptions These results suggest that the top15 frequent herbs have a potential to treat RA patients byintervening in the critical biological processes and pathway

Qing Feng Teng

Ku Shen

(a)

1

09

08

07

06

05

04

03

02

01

SinomenineDisinomenine

SinacutineAcutumineTuduranine

MagnoflorineIsosinomenine

MichelalbineBianfugenineStepharanine

Mat

rine

NIM

S sc

ore

Kura

rinon

eKu

rara

min

eBa

ptifo

line

Lehm

anin

eBe

ta-s

itoste

rol

Kush

enol

lCa

mph

orKo

sam

ol a

Gua

ijave

rin

Qin

g Fe

ng T

eng

Ku Shen

(b)

Figure 3 Calculation of synergistic activity among compoundscollected from the core herb networks (a) A part of the synergisticmodule from compounds of Qing Feng Teng (Caulis Sinomenii)and Ku Shen (Radix Sophorae flavescentis) (b) The horizontal andvertical axes show the compounds of herbs and the intervals ofaxis represent herbs The dark areas illustrate a modular featureand indicate strong synergistic interactions of herbs with highsynergistic scores calculated by the NIMS method

of RA which in turn gives evidence for the rationality of thecommonly prescribed herbs in Mr Lirsquos clinical practice

34 Network Connections of Anti-RA Herbs and Drugs InTCM RA patients can be categorized to different syndromes(ZHENG in Mandarin) for example Cold Syndrome andHot Syndrome Accordingly as shown in Table 1 Cold HotWarm Cool and Neutral are the basic properties of herbsreflecting the traditional characteristic of TCM TypicallyTCM doctors always use Cool or Cold herbs to treat patientswith Hot Syndrome whereas they use Warm or Hot herbsto treat patients with Cold Syndrome Cold-tendency andHot-tendency herbs may be combined to treat RA patientswith mixed Hot and Cold Syndromes On the other handin modern medicine immunomodulatory drugs such as


Th17 cellTGF120573

Synovial macrophage

T cell receptor

Antigen

DC

Rheumatoid arthritis

CD8086

MHCII

IgGSDF1

VEGF

CCL2 CXCL1CXCL5CCL3

CCL20 Ang1IL8Tie2Flt1

AP1TLR24LPSPeptidoglycan

signaling pathwayToll-like receptor

Autoantibody production

B cell

APRIL

RANKL

CD28CTLA4

TCR

LFA1

ICAM1

IL15

IL6

Synovium

Bone

IL23

MCSF

RANKL

RANKL RANK

CTSKTRAP

CTSLMMP13 Joint destruction

Inflammation

Angiogenesis

Leukocyte migration

Blood vessel

VEGF signaling pathway

Inflammatory

Synovial pannus

Bone resorption

V-ATPase

Osteoblast

Osteoclast

Osteoclast

differentiation

Synovial fibroblast

PTHVitamin D3

IL11

IL17

IL1IL6

IL6

CCL5IL1120573

GMCSF

IL18

BLYS

Self-reactiveTh1 cell

signaling pathwayLT120573

IFN120574

TNF120572

PGE2

H+

cell infiltration

formation

Herb targetRA gene

Figure 4 Network association of RA genes and top 15 frequent herbsrsquo targets in the enriched KEGG ldquorheumatoid arthritisrdquo pathway (KEGG05323)

methotrexate and leflunomide [24 25] and hormones such asglucocorticoids (dexamethasone) [26 27] are two categoriesof medicines for the treatment of patients with rheumatoidarthritis [28] Both categories of medicines can improve thequality of life and delay the disease progression of RA patientsvia independent but interactivemechanism of actions By cal-culating compound networks from the top 50 frequent herbsin Mr Lirsquos prescriptions we obtained the herbs that containingredients similar to RA immunomodulatory drugs andhormones respectively As shown in Figure 5 many herbscontain compounds with targets connected to the selectedanti-RA drugs in the network and may exert similar actionson RA For example 9 out of top 10 herbs with differentproperties such as Cold and Hot (Table 1) have compoundsthat are closely clustered with RA immune and hormonedrugs in the network These results are meaningful sincerecent studies indicated that the metabolism and immuneimbalance are closely associated with patients suffering fromCold Syndrome and Hot Syndrome [29 30] in many diseasesincluding rheumatoid arthritis [31 32] Interestingly it isnoticed that the Cold herbs tend to be enriched in theimmune-herb cluster Hot herbs tend to be enriched inhormone-herb cluster and Warm herbs are enriched in bothclusters Moreover compared with the hormone-herb cluster(Figure 5(b)) the immune-herb cluster is less diverse andonly contains Cold and Warm herbs suggesting these herbstend to exert immunosuppressive or immunoenhancementactions (Figure 5(a)) Although the results are preliminary

the potential connection as well as combinational effectsbetween herbs and drugs is of great importance and deservesfurther investigation in larger samples and clinical or experi-mental studies

4 Conclusions

In summary we developed a TCM network pharmacologystrategy and an Herb-Compound-Target-Disease coherentnetwork analysis framework to study herbal prescriptionsthe main form of TCM clinical practice We extracted twotypes of core herb networks from871 anti-RAherbal formulaeprescribed by a famous TCM doctor From the core herb net-works our network-based strategy identified cooccurrenceherbs and herb pairs with potential synergistic activities Wealso predicted the biological basis of the core herb networkby calculating the compoundrsquos targets from most frequentherbs We detected that targets of the commonly prescribedherbs are enriched together with RA genes in critical bio-logical processes and pathway of RA We also indicated thatherbs with different properties in prescriptions may have apotential connection with RA immunomodulatory drugs orhormones in the compound networks Taken together theseresults could help uncover the prescription rules underlyingherbal formulae in the clinical practice of TCM practitionersMoreover such network-based analyses not only can developa holistic understanding of herbal remedies but also mayfacilitate the following pharmacological evaluation of herbal


Ethylsalicylate

Hinesol

Campesterol

Taraxerone

AtractylenolideI

Leflunomide

Chen PiAngelicideBai

Shao

PaeonilactoneC

QiangHuo

Bai Zhu Albiflorin R1Sheng

DiHuang

ChiShao

Mai Ya

ManJing Zi Fang

Feng

KuShen

QingFengTeng

DangGui

Benzothiazole

Adrenocorticotropichormone

Folic acid

Chromone

Methotrexate

Lupenone

Dipterocarpol

Perrimustine

GuaiolIsofucosterol

120573-cryptoxanthin

Herb

Compound or drug

TengJi Xue

JiangHuang

DanShen

WuGong

HuangQi

ChuanXiong

3-Hydroxymugineicacid

Thiolproteaseinhibitor

Listomin S

Pseudocarpaine

Ciclosporin

Goitrin

Dihydro-2-methyl-3(2H)-furanone

Acetamide

Acetoin

Bornylacetate

Sophoranol

Tacrolimus

SandaracopimaricacidViridiflorol

Stigmasterin

Cholesterol

Ro 09-0680Phenylacetaldehyde

DAU 6215 hydrochloride

AC1L7QUY

Levamisolehydrochloride

Thalidomide

Mugineicacid

Benzoyl-dl-leucine

Ethanamine

Permanentorange

acid

Metarene

Laccase

AC1L7VXU

4-Hydroxymephenytoin

NSC673109

Procurcumenol Dehydrocurdione

Zeaxanthin

C09772

Olean-18-en-3-one

45-epoxide

100347-96-4

trans-Sabinenehydrate

CampheneVitamin D3

3-Oxo-1113(18)-oleanadien-28-oicacid

acid

6-Methylcholest-4-en-3-oneAspartylglucosamine

7-Dehydrostigmasterol

Cyclosporine

(4S5S)-(+)-germacrone

(5|A8|A9|A10|A16|A)-16-hydroxykauran-18-oic

(ZZ998400)-diligustilide

120575-terpineol

120573-sitosterol

51205729120572-dihydroxymatrine

2998400-Deoxymugineic

acetate

(a)

Apioglycyrrhizin

UralsaponinB

InflasaponinIV

InflasaponinI

Glycamil

Glycyrrhizicacid

ammoniumsalt

Glyuranolide

Glycyrrhizinicacid

AraboglycyrrhizinLiquoric acid

SophoraflavosideIV

GibberellinA1

CinncassiolA

Napellonine

CinncassiolC3

SophoraflavosideIII

Shanzhisidemethyl ester

Dexamethasone

Palbinone

Triamcinolone

LeiGongTeng

Ge Gen

WeiLingXian

QuanXie

RenDongTeng

Wu Tou

Fu Zi

Sang Ji Sheng

RuXiang

120572-boswellicacid

Rehmannicacid

Loganin

Tutin

acid

Loganic acid

NSC302037

Glycyrrhetinicacid

Prednisone

24-Hydroxyglycyrrheticacid

Corianin

3-Glc-soyasapogenolE

Glabric acidPaeonilactone

B

Cinncassiol E

Ecdysterone

Uralenolide

Asiatic acid

120573-glycyrrhetinicacid

Oleanolicacid

Geigerinin

CinncassiolC2

Tigogenin

Neotigogenin

GlycyrrhetolKatonic acid

Kihadanin A

Cortisone

Triptonide

Bufotoxin

Helixin

Inokosterone

Methylprednisolone

PrednisoloneTriptolideGibberellic

acidCaryoptoside

Triptolideanalog

Hydrocortisone

Gui Zhi

GanCao

XuDuan

Cold

Warm

Hormone drug

Immunomodulatory drug

Hot

Cool

Tu Fu LingHuang

Bai

Neutral

Niu Xi

Du Huo

Zhi Mu

Mu Gua

ShanZha

Pinnatifidin

(25S)-5120573-spirostan-3120573-ol

11-Keto-120573-boswellicacid

Acetyloleanolicacid

Corosolicacid

Boswellicacid

(5xi13|A14|A20s23r24s)-2324-dihydroxy-25-methoxylanost-7-en-3-one

(3|A20|A)-3-hydroxy-11-oxo-olean-12-en-29-oic

Herb

Compound or drug

(b)

Figure 5 Possible connection between RA herbs and drugs in the networks consisting of herbs herbal compounds immunomodulatorydrugs (a) and hormones (b)


Table 2 Overlapped RA-related GO terms between top 15 herbtargets and RA genes

Category Enriched GO terms Corrected119875-value

Herbtargets

Response to wounding 238119890 minus 127

Angiogenesis 121119890 minus 26

Inflammatory response 860119890 minus 71

Regulation of cytokine production 612119890 minus 26

Immune response 261119890 minus 88

Leukocyte activation 341119890 minus 38

Regulation of lymphocyte activation 452119890 minus 23

Defense response to bacterium 356119890 minus 10

Positive regulation of NF-120581Btranscription factor activity 604119890 minus 12

RA genes










treatments Clearly this study is only the first step to learnthe common rule of herbal prescriptions We will continueto conduct in-depth analysis for understanding the scientificbasis of herbal prescriptions in our future work Althoughmore powerful methods more data on TCM prescriptionsand clinical or experimental evaluations are still requiredwe believe that this TCM network pharmacology strategy issuitable to study herbal formulae both in the herb level andin the molecular level and thus can serve as a novel approachto further understand the professional experience embeddedin TCM prescriptions

Abbreviations

DMIM Distance-based mutual information modeldrugCIPHER Drug-target prediction by correlating

protein interaction network andphenotype network

GO Gene ontologyMI Mutual informationNIMS Network-based identification of

multicomponent synergyRA Rheumatoid arthritisPPI Protein-protein interactionQLY Qing-Luo-YinTCM Traditional Chinese Medicine

Conflict of Interests

The authors declare that they have no competing interests

Authorsrsquo Contribution

Shao Li conceived the study Yan Li collected the data Shao LiYan Li Rui Li and Zibo Ouyang analyzed the data and wrotethe paper All authors read and approved the final paper

Acknowledgments

Thanks to Kai Zhang for his help in herbal prescription col-lection This work is supported by NSFC project (81225025)the SATCM key discipline of ldquoTCM Bi-Bingrdquo in YijishanHospital of WannanMedical College the SATCM laboratoryof TCM master Ji-Ren Li the CATCM project and AnhuirsquosKey Technologies RampD project (11010402173)

References

[1] G G Zhang W Lee B Bausell L Lao B Handwerger andB Berman ldquoVariability in the traditional Chinese medicine(TCM) diagnoses and herbal prescriptions provided by threeTCM practitioners for 40 patients with rheumatoid arthritisrdquoJournal of Alternative and Complementary Medicine vol 11 no3 pp 415ndash421 2005

[2] G G Zhang B Singh W Lee B Handwerger L Lao and BBerman ldquoImprovement of agreement in TCMdiagnosis amongTCM practitioners for persons with the conventional diagnosisof rheumatoid arthritis effect of trainingrdquo Journal of Alternativeand Complementary Medicine vol 14 no 4 pp 381ndash386 2008

[3] P Zhang J Li Y Han X W Yu and L Qin ldquoTraditionalChinese medicine in the treatment of rheumatoid arthritis ageneral reviewrdquo Rheumatology International vol 30 no 6 pp713ndash718 2010

[4] Y Li 100 TCM Practitioners in Latest 100 Years Li Ji-ren ampZhang Shun-hua China Press of Traditional Chinese MedicineBeijing China 2004

[5] C Shu Z Li and Y Li ldquoGrand Master of TCM Ji-Ren Lirsquosexperience on the treatment of Bi Zhengrdquo Forum on TraditionalChinese Medicine vol 27 pp 10ndash12 2012

[6] S Li B Zhang D Jiang Y Wei and N Zhang ldquoHerbnetwork construction and co-module analysis for uncoveringthe combination rule of traditional Chinese herbal formulaerdquoBMC Bioinformatics vol 11 supplement 11 article S6 2010

[7] S Li B Zhang and N Zhang ldquoNetwork target for screeningsynergistic drug combinations with application to traditionalChinese medicinerdquo BMC Systems Biology vol 5 supplement 1p S10 2011

[8] S Zhao and S Li ldquoNetwork-based relating pharmacological andgenomic spaces for drug target identificationrdquo PLoS ONE vol5 no 7 Article ID e11764 2010

[9] X Liang H Li and S Li ldquoA novel network pharmacologyapproach to analyse traditional herbal formulae the Liu-Wei-Di-Huang pill as a case studyrdquoMolecular BioSystems vol 10 no5 pp 1014ndash1022 2014

[10] E L Leung Z-W Cao Z-H Jiang H Zhou and L LiuldquoNetwork-based drug discovery by integrating systems biologyand computational technologiesrdquo Briefings in Bioinformaticsvol 14 no 4 pp 491ndash505 2013

[11] V Sharma and I N Sarkar ldquoBioinformatics opportunitiesfor identification and study of medicinal plantsrdquo Briefings inBioinformatics vol 14 no 2 pp 238ndash250 2013


[12] S Li and B Zhang ldquoTraditional Chinese medicine networkpharmacology theory methodology and applicationrdquo ChineseJournal of Natural Medicines vol 11 no 2 pp 110ndash120 2013

[13] M Ashburner C A Ball J A Blake et al ldquoGene ontology toolfor the unification of biologyrdquoNature Genetics vol 25 no 1 pp25ndash29 2000

[14] A P Davis B L King S Mockus et al ldquoThe comparativetoxicogenomics database update 2011rdquo Nucleic Acids Researchvol 39 no 1 pp D1067ndashD1072 2011

[15] D S Wishart C Knox A C Guo et al ldquoDrugBank a knowl-edgebase for drugs drug actions and drug targetsrdquoNucleic AcidsResearch vol 36 no 1 pp D901ndashD906 2008

[16] T S Keshava Prasad RGoel K Kandasamy et al ldquoHumanpro-tein reference databasemdash2009 updaterdquo Nucleic Acids Researchvol 37 no 1 pp D767ndashD772 2009

[17] B Zhang X Wang and S Li ldquoAn integrative platform of TCMnetwork pharmacology and its application on a herbal formulaQing-Luo-Yinrdquo Evidence-Based Complementary and AlternativeMedicine vol 2013 Article ID 456747 12 pages 2013

[18] A E Koch ldquoAngiogenesis implications for rheumatoid arthri-tisrdquo Arthritis amp Rheumatism vol 41 no 6 pp 951ndash962 1998

[19] M Feldmann F M Brennan and R N Maini ldquoRole ofcytokines in rheumatoid arthritisrdquo Annual Review of Immunol-ogy vol 14 pp 397ndash440 1996

[20] E H S Choy and G S Panayi ldquoCytokine pathways andjoint inflammation in rheumatoid arthritisrdquo The New EnglandJournal of Medicine vol 344 no 12 pp 907ndash916 2001

[21] G Janossy G Panayi O Duke M Bofill L W Poulterand G Goldstein ldquoRheumatoid arthritis a disease of T-lymphocytemacrophage immunoregulationrdquo The Lancet vol2 no 8251 pp 839ndash842 1981

[22] S S Makarov ldquoNF-120581B in rheumatoid arthritis a pivotal reg-ulator of inflammation hyperplasia and tissue destructionrdquoArthritis Research vol 3 no 4 pp 200ndash206 2001

[23] M Cutolo A Sulli B Villaggio B Seriolo and S AccardoldquoRelations between steroid hormones and cytokines in rheuma-toid arthritis and systemic lupus erythematosusrdquo Annals of theRheumatic Diseases vol 57 no 10 pp 573ndash577 1998

[24] P E Lipsky D M van der Heijde E W St Clair et al ldquoAnti-TumorNecrosis Factor Trial in RheumatoidArthritis with Con-comitant Therapy Study Group Infliximab and methotrexatein the treatment of rheumatoid arthritis Anti-Tumor NecrosisFactor Trial in Rheumatoid Arthritis with Concomitant Ther-apy Study Grouprdquo The New England Journal of Medicine vol343 no 22 pp 1594ndash1602 2000

[25] V Strand S Cohen M Schiff et al ldquoTreatment of activerheumatoid arthritis with leflunomide compared with placeboand methotrexate Leflunomide Rheumatoid Arthritis Investi-gators Grouprdquo Archives of Internal Medicine vol 159 no 21 pp2542ndash2550 1999

[26] J R Kirwan ldquoThe effect of glucocorticoids on joint destructionin rheumatoid arthritisrdquoThe New England Journal of Medicinevol 333 no 3 pp 142ndash146 1995

[27] S R de Antonio H M Blotta R L Mamoni et al ldquoEffects ofdexamethasone on lymphocyte proliferation and cytokine pro-duction in rheumatoid arthritisrdquoThe Journal of Rheumatologyvol 29 no 1 pp 46ndash51 2002

[28] J R OrsquoDell ldquoTherapeutic strategies for rheumatoid arthritisrdquoTheNew England Journal of Medicine vol 350 no 25 pp 2591ndash2602 2004

[29] S Li Z Q Zhang L JWu X G Zhang Y D Li andY YWangldquoUnderstanding ZHENG in traditional Chinese medicine inthe context of neuro-endocrine-immune networkrdquo IET SystemsBiology vol 1 no 1 pp 51ndash60 2007

[30] R Li T Ma J Gu X Liang and S Li ldquoImbalanced networkbiomarkers for traditional Chinese medicine Syndrome ingastritis patientsrdquo Scientific Reports vol 3 article 1543 2013

[31] G Chen C Lu Q Zha et al ldquoA network-based analysis oftraditional Chinese medicine cold and hot patterns in rheuma-toid arthritisrdquo Complementary Therapies in Medicine vol 20no 1-2 pp 23ndash30 2012

[32] H A van Wietmarschen W Dai A J van der Kooij et alldquoCharacterization of rheumatoid arthritis subtypes using symp-tom profiles clinical chemistry and metabolomics measure-mentsrdquo PLoS ONE vol 7 no 9 Article ID e44331 2012

Submit your manuscripts athttpwwwhindawicom

Stem CellsInternational

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014


MEDIATORSINFLAMMATION

of


Behavioural Neurology

EndocrinologyInternational Journal of



Disease Markers


BioMed Research International

OncologyJournal of



Oxidative Medicine and Cellular Longevity


PPAR Research

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Immunology ResearchHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Journal of

ObesityJournal of



Computational and Mathematical Methods in Medicine

OphthalmologyJournal of


Diabetes ResearchJournal of



Research and TreatmentAIDS


Gastroenterology Research and Practice


Parkinsonrsquos Disease

Evidence-Based Complementary and Alternative Medicine

Volume 2014Hindawi Publishing Corporationhttpwwwhindawicom


TCMpractitioners specifically tailored to individual patientsTCM doctors treat patients mainly based on syndrome dif-ferentiation For different patients various herbs are groupedand different formulae are prescribed This tradition andfeature make TCM a kind of personalized medicine andcause great difficulty in designing standard protocols suchas the randomized controlled trial in TCM studies Thelack of appropriate methods to analyze the rule as well asscientific basis for TCM-doctor-prescribed herbal formulaeis therefore one of the major frustrations to find clinicalevidence of TCM How to study the characteristics andprescription rule of such flexible TCM formulae is still a greatchallenge and requires widely interdisciplinary efforts

Thanks to the rapid progress of bioinformatics especiallycomplex network theory and technologies recently thenetwork approach has become a new avenue and powerfultool to handle intricate problems such as those in TCMWe have been making efforts to build a TCM networkpharmacology approach over ten years and established aset of network-based methods for TCM study [6ndash9] Forexample to reveal the combination rule and the biologicalbasis of herbal formulae we proposed a global networkanalysis framework consisting of herbcompound networkbiological network (gene protein or target network) anddisease network Several methods are also created suchas a distance-based mutual information model (DMIM)that can identify herb relationships from numerous herbalformulae The good performance of the DMIM method touncover the herbal combination rules has been illustrated inboth 3865 collaterals-related herbal formulae and a classicLiu-Wei-Di-Huang formula [6] Furthermore we proposeda novel concept of ldquonetwork targetrdquo [7] which treats adisease-specific molecular network as a therapeutic targetto help design suitable medical treatments Several methodsfor the network target analysis especially the disease geneprediction target prediction for drugs or herbal compounds[8] the network comodule analysis for drug discovery andthe network-based prioritization of synergistic combinations[7] are developed subsequently These methods have beenapplied in finding bioactive compounds and revealing themechanism of action for herbal formulae including Liu-Wei-Di-Huang pill [9] Now the network-based method inthe context of TCM network pharmacology has become aburgeoning field in the modern studies of TCM [10ndash12] Webelieve the network-based strategy and approaches can alsoprovide good solutions for the herbal prescription analysis

In this work 871 herbal prescriptions from Mr Ji-Ren Lirsquos clinical treatment on patients with rheumatoidarthritis were analyzed from a network point of view TCMnetwork pharmacology methods were employed to detectthe common rules and potential biological basis of theseherbal prescriptions This work is promising as the resultsnicely show the rationality and validity of Mr Lirsquos herbalprescriptions Moreover this work provides a new route tointerpret the professional experience embedded in numerousand precious TCM herbal prescriptions

Herbal prescriptions

Herbnetwork

Compound network

Herb name normalization

Herb relationship byDMIM scoring

Herb compoundcollection

Target prediction by drugCIPHER

Connect compound by target interaction

Disease gene network

Evaluation of synergistic activity by NIMS

Figure 1 The Herb-Compound-Target-Disease coherent networkanalysis framework for studying herbal prescriptions on the treat-ment of certain diseases

2 Methods

21 Herbal Formulae and Herbal Compounds A total of 871herbal prescriptions from Mr Ji-Ren Li in the individuallyclinical treatment of RA patients from 2005 to 2013 were usedin this work The 871 herbal prescriptions were normalizedby substituting the polysemes synonyms and acronyms ofthe herbs in the dataset and resulted in a standardized HerbName list Each formula contains 15 to 29 herbs and the aver-age number is 18 Compounds of herbs were gathered fromthe HerbBioMap database (China Copyright of ComputerSoftware 2011SR076502)TheHerbBioMapdatabase contains10806 compounds for 539 herbs up to now

22 Multilayer Coherent Network Analysis for Herbal Pre-scriptions As shown in Figure 1 we proposed an Herb-Compound-Target-Disease coherent network analysis frame-work to study the prescription rules and potential biologicalbasis for herbal prescriptionsThe principle steps are summa-rized as follows

Herb Network Construction We created a matrix of 871dimensions to represent all collected herbal formulae andthen calculated the frequency of every 343 herbs in allformulae and gave a normalized frequency (NF) NF =AFsum119873

119899=1AF1 where AF is accumulated frequency and 119873

denotes 343-herb species number Next most frequent herbsin 871 herbal prescriptions were selected and subjected tothe DMIM (distance-basedmutual informationmodel) anal-ysis an algorithm for identifying herb relationships amongdifferent formulae and uncovering the combinational rulesof herbs in a network manner [6] The DMIM model isan integrated scoring system combining the mutual infor-mation (MI) entropy characteristics and the ldquobetween-herbdistancerdquo (119889) between herbs by calculating score(119909 119910) =MI(119909 119910)119889(119909 119910) which describes the tendency of herb 119909 and





















Lian Qiao


Ku Shen

Bi Xie

Wu Shao She

Qin Jiao

Man Jing Zi

Han Lian Cao

Chai Hu

Wu Wei Zi

Bai Mao Gen

Wei Ling Xian

Qing Feng Teng

Zhi Mu

Wu Tou

Huo Xue Teng

Lei Gong Teng

Huang Bai

Ji XueTengHuang Qi

Pu Gong Ying

Ren Dong Teng

(a)

Man Jing Zi

Wu Tou

Bi Xie

Ji Xue Teng

Zhi Mu

Qin JiaoWu Shao She

Ku ShenHuo Xue Teng

Qing Feng Teng

Pu Gong Ying

Lei Gong Teng

Huang Bai

Ren Dong Teng

(b)



Qing Feng Teng

Ku Shen

(a)

1

09

08

07

06

05

04

03

02

01





Mat

rine

NIM

S sc

ore

Kura

rinon

eKu

rara

min

eBa

ptifo

line

Lehm

anin

eBe

ta-s

itoste

rol

Kush

enol

lCa

mph

orKo

sam

ol a

Gua

ijave

rin

Qin

g Fe

ng T

eng

Ku Shen

(b)





Th17 cellTGF120573

Synovial macrophage

T cell receptor

Antigen

DC


CD8086

MHCII

IgGSDF1

VEGF

CCL2 CXCL1CXCL5CCL3





B cell

APRIL

RANKL

CD28CTLA4

TCR

LFA1

ICAM1

IL15

IL6

Synovium

Bone

IL23

MCSF

RANKL

RANKL RANK

CTSKTRAP


Inflammation

Angiogenesis

Leukocyte migration

Blood vessel


Inflammatory

Synovial pannus

Bone resorption

V-ATPase

Osteoblast

Osteoclast

Osteoclast

differentiation

Synovial fibroblast

PTHVitamin D3

IL11

IL17

IL1IL6

IL6

CCL5IL1120573

GMCSF

IL18

BLYS



IFN120574

TNF120572

PGE2

H+

cell infiltration

formation

Herb targetRA gene




4 Conclusions



Ethylsalicylate

Hinesol

Campesterol

Taraxerone

AtractylenolideI

Leflunomide


Shao

PaeonilactoneC

QiangHuo


DiHuang

ChiShao

Mai Ya

ManJing Zi Fang

Feng

KuShen

QingFengTeng

DangGui

Benzothiazole


Folic acid

Chromone

Methotrexate

Lupenone

Dipterocarpol

Perrimustine

GuaiolIsofucosterol


Herb

Compound or drug

TengJi Xue

JiangHuang

DanShen

WuGong

HuangQi

ChuanXiong



Listomin S

Pseudocarpaine

Ciclosporin

Goitrin


Acetamide

Acetoin

Bornylacetate

Sophoranol

Tacrolimus


Stigmasterin

Cholesterol



AC1L7QUY


Thalidomide

Mugineicacid

Benzoyl-dl-leucine

Ethanamine

Permanentorange

acid

Metarene

Laccase

AC1L7VXU


NSC673109


Zeaxanthin

C09772

Olean-18-en-3-one

45-epoxide

100347-96-4


CampheneVitamin D3


acid



Cyclosporine




120575-terpineol

120573-sitosterol



acetate

(a)

Apioglycyrrhizin

UralsaponinB

InflasaponinIV

InflasaponinI

Glycamil

Glycyrrhizicacid

ammoniumsalt

Glyuranolide

Glycyrrhizinicacid


SophoraflavosideIV

GibberellinA1

CinncassiolA

Napellonine

CinncassiolC3

SophoraflavosideIII


Dexamethasone

Palbinone

Triamcinolone

LeiGongTeng

Ge Gen

WeiLingXian

QuanXie

RenDongTeng

Wu Tou

Fu Zi

Sang Ji Sheng

RuXiang


Rehmannicacid

Loganin

Tutin

acid

Loganic acid

NSC302037

Glycyrrhetinicacid

Prednisone


Corianin



B

Cinncassiol E

Ecdysterone

Uralenolide

Asiatic acid


Oleanolicacid

Geigerinin

CinncassiolC2

Tigogenin

Neotigogenin


Kihadanin A

Cortisone

Triptonide

Bufotoxin

Helixin

Inokosterone

Methylprednisolone


acidCaryoptoside

Triptolideanalog

Hydrocortisone

Gui Zhi

GanCao

XuDuan

Cold

Warm

Hormone drug


Hot

Cool

Tu Fu LingHuang

Bai

Neutral

Niu Xi

Du Huo

Zhi Mu

Mu Gua

ShanZha

Pinnatifidin

(25S)-5120573-spirostan-3120573-ol


Acetyloleanolicacid

Corosolicacid

Boswellicacid



Herb

Compound or drug

(b)





Herbtargets










RA genes











Abbreviations









Acknowledgments


References







































of






Disease Markers



OncologyJournal of





PPAR Research



Journal of

ObesityJournal of




































Lian Qiao


Ku Shen

Bi Xie

Wu Shao She

Qin Jiao

Man Jing Zi

Han Lian Cao

Chai Hu

Wu Wei Zi

Bai Mao Gen

Wei Ling Xian

Qing Feng Teng

Zhi Mu

Wu Tou

Huo Xue Teng

Lei Gong Teng

Huang Bai

Ji XueTengHuang Qi

Pu Gong Ying

Ren Dong Teng

(a)

Man Jing Zi

Wu Tou

Bi Xie

Ji Xue Teng

Zhi Mu

Qin JiaoWu Shao She

Ku ShenHuo Xue Teng

Qing Feng Teng

Pu Gong Ying

Lei Gong Teng

Huang Bai

Ren Dong Teng

(b)



Qing Feng Teng

Ku Shen

(a)

1

09

08

07

06

05

04

03

02

01





Mat

rine

NIM

S sc

ore

Kura

rinon

eKu

rara

min

eBa

ptifo

line

Lehm

anin

eBe

ta-s

itoste

rol

Kush

enol

lCa

mph

orKo

sam

ol a

Gua

ijave

rin

Qin

g Fe

ng T

eng

Ku Shen

(b)





Th17 cellTGF120573

Synovial macrophage

T cell receptor

Antigen

DC


CD8086

MHCII

IgGSDF1

VEGF

CCL2 CXCL1CXCL5CCL3





B cell

APRIL

RANKL

CD28CTLA4

TCR

LFA1

ICAM1

IL15

IL6

Synovium

Bone

IL23

MCSF

RANKL

RANKL RANK

CTSKTRAP


Inflammation

Angiogenesis

Leukocyte migration

Blood vessel


Inflammatory

Synovial pannus

Bone resorption

V-ATPase

Osteoblast

Osteoclast

Osteoclast

differentiation

Synovial fibroblast

PTHVitamin D3

IL11

IL17

IL1IL6

IL6

CCL5IL1120573

GMCSF

IL18

BLYS



IFN120574

TNF120572

PGE2

H+

cell infiltration

formation

Herb targetRA gene




4 Conclusions



Ethylsalicylate

Hinesol

Campesterol

Taraxerone

AtractylenolideI

Leflunomide


Shao

PaeonilactoneC

QiangHuo


DiHuang

ChiShao

Mai Ya

ManJing Zi Fang

Feng

KuShen

QingFengTeng

DangGui

Benzothiazole


Folic acid

Chromone

Methotrexate

Lupenone

Dipterocarpol

Perrimustine

GuaiolIsofucosterol


Herb

Compound or drug

TengJi Xue

JiangHuang

DanShen

WuGong

HuangQi

ChuanXiong



Listomin S

Pseudocarpaine

Ciclosporin

Goitrin


Acetamide

Acetoin

Bornylacetate

Sophoranol

Tacrolimus


Stigmasterin

Cholesterol



AC1L7QUY


Thalidomide

Mugineicacid

Benzoyl-dl-leucine

Ethanamine

Permanentorange

acid

Metarene

Laccase

AC1L7VXU


NSC673109


Zeaxanthin

C09772

Olean-18-en-3-one

45-epoxide

100347-96-4


CampheneVitamin D3


acid



Cyclosporine




120575-terpineol

120573-sitosterol



acetate

(a)

Apioglycyrrhizin

UralsaponinB

InflasaponinIV

InflasaponinI

Glycamil

Glycyrrhizicacid

ammoniumsalt

Glyuranolide

Glycyrrhizinicacid


SophoraflavosideIV

GibberellinA1

CinncassiolA

Napellonine

CinncassiolC3

SophoraflavosideIII


Dexamethasone

Palbinone

Triamcinolone

LeiGongTeng

Ge Gen

WeiLingXian

QuanXie

RenDongTeng

Wu Tou

Fu Zi

Sang Ji Sheng

RuXiang


Rehmannicacid

Loganin

Tutin

acid

Loganic acid

NSC302037

Glycyrrhetinicacid

Prednisone


Corianin



B

Cinncassiol E

Ecdysterone

Uralenolide

Asiatic acid


Oleanolicacid

Geigerinin

CinncassiolC2

Tigogenin

Neotigogenin


Kihadanin A

Cortisone

Triptonide

Bufotoxin

Helixin

Inokosterone

Methylprednisolone


acidCaryoptoside

Triptolideanalog

Hydrocortisone

Gui Zhi

GanCao

XuDuan

Cold

Warm

Hormone drug


Hot

Cool

Tu Fu LingHuang

Bai

Neutral

Niu Xi

Du Huo

Zhi Mu

Mu Gua

ShanZha

Pinnatifidin

(25S)-5120573-spirostan-3120573-ol


Acetyloleanolicacid

Corosolicacid

Boswellicacid



Herb

Compound or drug

(b)





Herbtargets










RA genes











Abbreviations









Acknowledgments


References







































of






Disease Markers



OncologyJournal of





PPAR Research



Journal of

ObesityJournal of

















Th17 cellTGF120573

Synovial macrophage

T cell receptor

Antigen

DC


CD8086

MHCII

IgGSDF1

VEGF

CCL2 CXCL1CXCL5CCL3





B cell

APRIL

RANKL

CD28CTLA4

TCR

LFA1

ICAM1

IL15

IL6

Synovium

Bone

IL23

MCSF

RANKL

RANKL RANK

CTSKTRAP


Inflammation

Angiogenesis

Leukocyte migration

Blood vessel


Inflammatory

Synovial pannus

Bone resorption

V-ATPase

Osteoblast

Osteoclast

Osteoclast

differentiation

Synovial fibroblast

PTHVitamin D3

IL11

IL17

IL1IL6

IL6

CCL5IL1120573

GMCSF

IL18

BLYS



IFN120574

TNF120572

PGE2

H+

cell infiltration

formation

Herb targetRA gene




4 Conclusions



Ethylsalicylate

Hinesol

Campesterol

Taraxerone

AtractylenolideI

Leflunomide


Shao

PaeonilactoneC

QiangHuo


DiHuang

ChiShao

Mai Ya

ManJing Zi Fang

Feng

KuShen

QingFengTeng

DangGui

Benzothiazole


Folic acid

Chromone

Methotrexate

Lupenone

Dipterocarpol

Perrimustine

GuaiolIsofucosterol


Herb

Compound or drug

TengJi Xue

JiangHuang

DanShen

WuGong

HuangQi

ChuanXiong



Listomin S

Pseudocarpaine

Ciclosporin

Goitrin


Acetamide

Acetoin

Bornylacetate

Sophoranol

Tacrolimus


Stigmasterin

Cholesterol



AC1L7QUY


Thalidomide

Mugineicacid

Benzoyl-dl-leucine

Ethanamine

Permanentorange

acid

Metarene

Laccase

AC1L7VXU


NSC673109


Zeaxanthin

C09772

Olean-18-en-3-one

45-epoxide

100347-96-4


CampheneVitamin D3


acid



Cyclosporine




120575-terpineol

120573-sitosterol



acetate

(a)

Apioglycyrrhizin

UralsaponinB

InflasaponinIV

InflasaponinI

Glycamil

Glycyrrhizicacid

ammoniumsalt

Glyuranolide

Glycyrrhizinicacid


SophoraflavosideIV

GibberellinA1

CinncassiolA

Napellonine

CinncassiolC3

SophoraflavosideIII


Dexamethasone

Palbinone

Triamcinolone

LeiGongTeng

Ge Gen

WeiLingXian

QuanXie

RenDongTeng

Wu Tou

Fu Zi

Sang Ji Sheng

RuXiang


Rehmannicacid

Loganin

Tutin

acid

Loganic acid

NSC302037

Glycyrrhetinicacid

Prednisone


Corianin



B

Cinncassiol E

Ecdysterone

Uralenolide

Asiatic acid


Oleanolicacid

Geigerinin

CinncassiolC2

Tigogenin

Neotigogenin


Kihadanin A

Cortisone

Triptonide

Bufotoxin

Helixin

Inokosterone

Methylprednisolone


acidCaryoptoside

Triptolideanalog

Hydrocortisone

Gui Zhi

GanCao

XuDuan

Cold

Warm

Hormone drug


Hot

Cool

Tu Fu LingHuang

Bai

Neutral

Niu Xi

Du Huo

Zhi Mu

Mu Gua

ShanZha

Pinnatifidin

(25S)-5120573-spirostan-3120573-ol


Acetyloleanolicacid

Corosolicacid

Boswellicacid



Herb

Compound or drug

(b)





Herbtargets










RA genes











Abbreviations









Acknowledgments


References







































of






Disease Markers



OncologyJournal of





PPAR Research



Journal of

ObesityJournal of

















Ethylsalicylate

Hinesol

Campesterol

Taraxerone

AtractylenolideI

Leflunomide


Shao

PaeonilactoneC

QiangHuo


DiHuang

ChiShao

Mai Ya

ManJing Zi Fang

Feng

KuShen

QingFengTeng

DangGui

Benzothiazole


Folic acid

Chromone

Methotrexate

Lupenone

Dipterocarpol

Perrimustine

GuaiolIsofucosterol


Herb

Compound or drug

TengJi Xue

JiangHuang

DanShen

WuGong

HuangQi

ChuanXiong



Listomin S

Pseudocarpaine

Ciclosporin

Goitrin


Acetamide

Acetoin

Bornylacetate

Sophoranol

Tacrolimus


Stigmasterin

Cholesterol



AC1L7QUY


Thalidomide

Mugineicacid

Benzoyl-dl-leucine

Ethanamine

Permanentorange

acid

Metarene

Laccase

AC1L7VXU


NSC673109


Zeaxanthin

C09772

Olean-18-en-3-one

45-epoxide

100347-96-4


CampheneVitamin D3


acid



Cyclosporine




120575-terpineol

120573-sitosterol



acetate

(a)

Apioglycyrrhizin

UralsaponinB

InflasaponinIV

InflasaponinI

Glycamil

Glycyrrhizicacid

ammoniumsalt

Glyuranolide

Glycyrrhizinicacid


SophoraflavosideIV

GibberellinA1

CinncassiolA

Napellonine

CinncassiolC3

SophoraflavosideIII


Dexamethasone

Palbinone

Triamcinolone

LeiGongTeng

Ge Gen

WeiLingXian

QuanXie

RenDongTeng

Wu Tou

Fu Zi

Sang Ji Sheng

RuXiang


Rehmannicacid

Loganin

Tutin

acid

Loganic acid

NSC302037

Glycyrrhetinicacid

Prednisone


Corianin



B

Cinncassiol E

Ecdysterone

Uralenolide

Asiatic acid


Oleanolicacid

Geigerinin

CinncassiolC2

Tigogenin

Neotigogenin


Kihadanin A

Cortisone

Triptonide

Bufotoxin

Helixin

Inokosterone

Methylprednisolone


acidCaryoptoside

Triptolideanalog

Hydrocortisone

Gui Zhi

GanCao

XuDuan

Cold

Warm

Hormone drug


Hot

Cool

Tu Fu LingHuang

Bai

Neutral

Niu Xi

Du Huo

Zhi Mu

Mu Gua

ShanZha

Pinnatifidin

(25S)-5120573-spirostan-3120573-ol


Acetyloleanolicacid

Corosolicacid

Boswellicacid



Herb

Compound or drug

(b)





Herbtargets










RA genes











Abbreviations









Acknowledgments


References







































of






Disease Markers



OncologyJournal of





PPAR Research



Journal of

ObesityJournal of



















Herbtargets










RA genes











Abbreviations









Acknowledgments


References







































of






Disease Markers



OncologyJournal of





PPAR Research



Journal of

ObesityJournal of











































of






Disease Markers



OncologyJournal of





PPAR Research



Journal of

ObesityJournal of
















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