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Systems Pharmacology Dissection of Multi-Scale Mechanisms of Action for Herbal Medicines in Treating Rheumatoid Arthritis Jinghui Wang, Yan Li, Yinfeng Yang, Jian Du, Miaoqing Zhao, Feng Lin, Shuwei Zhang, and Bin Wang Mol. Pharmaceutics, Just Accepted Manuscript • DOI: 10.1021/acs.molpharmaceut.7b00505 • Publication Date (Web): 03 Aug 2017 Downloaded from http://pubs.acs.org on August 6, 2017

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Molecular Pharmaceutics

Systems Pharmacology Dissection of Multi-Scale Mechanisms of Action for Herbal Medicines in Treating Rheumatoid Arthritis Jinghui Wang 1, 2, Yan Li 1, 2,*, Yinfeng Yang 1, Jian Du Feng Lin 1, Shuwei Zhang 1 and Bin Wang 3

1, 2,*

, Miaoqing Zhao1,

1. Key Laboratory of Industrial Ecology and Environmental Engineering (MOE), Department of Materials Sciences and Chemical Engineering, Dalian University of Technology, Dalian, Liaoning, 116024, China; E-Mails: [email protected]; [email protected]; [email protected]; [email protected]; [email protected] 2. Institute of Chemical Process Systems Engineering, Dalian University of Technology, Dalian 116024, Liaoning, China; E-Mail: [email protected] 3. Dalian Ocean University, Dalian, Liaoning, 116023, China; E-Mail: [email protected] * Corresponding authors: [email protected]; [email protected]

Abstract: As a chronic inflammatory and angiogenic disease with increased morbidity and mortality, rheumatoid arthritis (RA) is characterized by the proliferation of synovial tissue and the accumulation of excessive mononuclear infiltration, which always results in the joint deformity, disability, and eventually the destruction of the bone and cartilage. Traditional Chinese Medicine (TCM), with rich history of proper effectiveness in treating the inflammatory joint disease containing RA, has long combated such illness from, actually, an integrative and holistic point of view. However, its “multi-components” and “multi-targets” feature makes it very difficult to decipher the molecular mechanisms of RA from a systematic perspective if employing only routine methods. Presently, an innovative systems-pharmacology approach was introduced, combining the ADME screening model, drug targeting and network pharmacology, to explore the action mechanisms of botanic herbs for the treatment of RA. As a result, we uncover 117 active compounds and 85 key molecular targets from seven RA-related herbs, which are mainly implicated in four signaling pathways, i.e., VEGF, PI3K-Akt, TLR and T-cell-receptor pathways. Additionally, the network relationships among the active components, target proteins and pathways were further built to uncover the pharmacological characters of these herbs. Besides, MD simulations and MM-PBSA calculations were carried out to explore the binding interactions between the compounds and their receptors as well as to investigate the binding affinity of the ligand to their protein targets. In vitro experiments by ligand binding assays validate the reliability of the drug-target interactions as well as the MD results. The high binding affinities and good inhibitions of the active compounds indicate that the potential therapeutic effects of these herbal medicines for treating RA are exerted probably through the modulation of these relevant proteins, which further validates the rationality and reliability of the drug-target interactions as well as our the network-based analytical methods. This work may be of help for not only understanding the action mechanisms of TCM and for discovering new drugs from plants for the treatment of RA, but also providing a novel potential method for modern medicine in treating complex diseases.

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Keywords: Rheumatoid arthritis; TCM; Systems-Pharmacology; MD; MM-PBSA 1 INTRODUCTION Rheumatoid arthritis (RA), a progressive systemic autoimmune disease, has 1% prevalence in the adult human population and affects three times more women than men.1 It is associated with a syndrome of pain, progressive disability, and chronic inflammatory synovitis which gradually leads to articular destruction, functional decline and systemic disease.2 Generally, the primary objectives in RA’s treatment are to reduce the joint damage and disability, control the inflammation and pain, improve or maintain the physical function as well as the life quality.3 The most commonly used drugs for treating RA are disease-modifying anti-rheumatic drugs (DMARDs) and non-steroidal anti-inflammatory drugs (NSAIDs).4 Although these drugs have anti-inflammatory, immunosuppressive and analgesic effects, due to their frequent side effects, their application should be cautious and a long-term treatment by them should be avoided as well.3 Therefore, a task of developing more potent and safer drugs for treating RA is still a matter of urgency. Over the past decade, the use of complementary and alternative medicine (CAM) therapies has become increasingly popular throughout the world. Traditional Chinese Medicine (TCM), one of main items of CAM, is a whole medical system with rich practice experience over thousands of years, and has attracted wide attention in recent decades owing to their moderate treatment effects and fewer adverse reactions.5 Based on the synergistic effects produced by its multi-ingredients, multi-proteins and multi-pathways feature, TCM generates efficacy with a remarkable advantage over a single-drug therapy, especially in conquering chronic complex diseases containing RA. For centuries in China, various TCM herbal medicines have been used for the treatment of RA, with their anti-arthritic and anti-inflammatory activities already confirmed by experimental arthritis animal models and examined by clinical trials with RA patients.6-12 Consequently, TCM has been deemed as a crucial strategy for inhibiting RA development as well as improving the life quality of RA patients. However, herbal medicines always contain huge numbers of constituents, and the diversified bioactive compounds of TCM with their related multiple targets, pathways also complicate their pharmacological research, making it difficult to uncover the mechanisms of their interactions employing only traditional experimental approaches. Alternative to experiments, systems pharmacology, as a novel powerful tool to understand the complicated interactions between the target proteins and small molecules from a biological perspective, resembles the holism concept of channel tropism in TCM.13,14 Recently, a growing body of study has shown that the application of systems pharmacology provides guidance to investigate the scientific connotation of TCM.15,16 Presently, to explore the therapeutic mechanism of TCM in treating RA, a novel systems-pharmacological model we developed was introduced, integrating pharmacokinetics screening, drug targeting and network analysis. The work scheme is depicted in Fig. 1. In brief, using a wide-scale text mining approach, the anti-RA herbal medicines with their corresponding ingredients were firstly extracted. Then, the


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active components with satisfactory pharmacokinetic activity in these botanic herbs were screened out using an in silico ADME (absorption, distribution, metabolism, and excretion) system. Thirdly, after identification of the target proteins of these ingredients, we mapped the obtained targets onto functional ontologies for generating compound–target network and target-pathway integration analysis. Finally, to validate the reliability of drug-target interactions and to further get their accurate binding modes, the inhibitory effects of 8 candidate compounds on their predicted targets were determined in vitro by ligand binding assays with their binding interactions assessed by molecular dynamics (MD) simulation. Using the MM-PBSA (Molecular Mechanics-Poisson-Boltzmann Surface Area) method, the binding affinities of these compounds with their receptors were computed. The high binding affinities and good inhibitions of these compounds indicate that the ligands bind well to their receptors, further validating the rationality and reliability of the drug-target interactions as well as our network-based analytical methods. All these results may not only provide new insights for deeper understanding of the underlying molecular mechanisms of TCM for the treatment of RA, but also promote the development of new therapy from herbal medicine for complex diseases in the near future.

Figure 1. The work scheme of systems pharmacology approach

2 MATERIALS AND METHODS 2.1 Identification of Herbs for Treating RA To obtain the herbs for the treatment of RA, a potent wide-scale text mining with the keywords ‘herbal medicine’ and ‘RA’ was carried out. Due to different herbs with



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different research extents, a statistical index, i.e., P-value was calculated to lessen the possible bias as well as to evaluate the probability co-occurrence between a single herbal medicine and RA17 according to the following formula.

k −1

P =1−

∑ f(i)

k −1

=1 −

i =0

∑ i =0

 K  N − K      i  n − i  N    n 

(1)

Herein, N is the total number of articles published in database PubMed and CNKI, K represents the number of papers related to RA, n is the number of papers about each single herb and k is the number of papers about the effects of corresponding herbs on RA. The herbs are considered to have strong correlations with RA when P-value ≤ 0.01. In addition, more empirically based knowledge and TCM experience are employed for the selection of herbs. As a result, seven herbs (as summarized in Table 1), i.e., Radix Paeoniae Alba, Angelicae Sinensis Radix, Radix Angelicae Biseratae, Aconiti Lateralis Radix Praeparata, Cinnamomi Ramulus, Radix Astragali seu Hedysari, Anemarrhenae Rhizoma, that are significantly correlated with RA were obtained. 2.2 Ingredients Database Construction All ingredients of RA-related herbal medicines were obtained from TCMSP (http://lsp.nwsuaf.edu.cn/tcmsp.php). Due to the deglycosylation of glycosides by colonic bacteria in humans, the corresponding aglycones of the ingredients were also retained for following studies. Finally, a total of 1009 chemicals were obtained for the present analysis. 2.3 ADME Screening Models Generally, an early evaluation of the ADME properties of drugs can predict the pharmacokinetic behavior of chemical compounds and minimize their potential drug-drug interactions. In the present work, two ADME-related models, i.e., PreOB (predict oral bioavailability) and PreDL (predict drug-likeness) were employed to prescreen for the bioactive molecules. In detail, PreOB, a potent in-house previously developed model18 was performed to predict the OB of the constituents of the herbs, integrating the information of cytochrome P450 3A4 and P-glycoprotein. Additionally, in order to obtain drug-like compounds, PreDL,19 a database-dependent model developed by our own laboratory, was also carried out to compute the drug-likeness of each compound by using the Tanimoto coefficient (as displayed in Eq.2) T ( A, B)=

A⋅ B 2

2

A + B − A⋅ B

(2)

where a represents the molecular properties of ingredients in herbs, and b denotes the average drug-likeness index of all compounds in DrugBank database


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(http://www.drugbank.ca/). In the current study, the ingredients meeting the criteria of OB ≥ 30% and DL ≥ 0.18 are chosen as candidate compounds and used for further research. 2.4 Target Fishing and Network Construction To obtain the molecular targets of these active ingredients, an in-house developed model SysDT based on RF and SVM methods20 was proposed, which efficiently integrates large scale information of chemistry, genomics and pharmacology. Additionally, with attempt to characterize the multi-component therapeutic features of the anti-RA herbs and to explore the biological effects of these drugs on the pathway level, three networks including Compound-Target (C-T), Compound-Target-Function (C-T-F), Compound-Target-Disease (C-T-D) and Target-Pathway (T-P) networks were constructed. All of the compounds were extracted from ADME screening and the targets obtained from the target fishing. Then, the obtained target profiles were organized into several pathways by mapping to KEGG. Those pathways not directly related to RA were removed according to pathological and clinical studies. All the bipartite graphs of the networks were generated and visualized by an open source of bioinformatics package, Cytoscape 3.2.1.21 2.5 Docking and MD Simulations analysis Presently, to investigate the mechanism of the interactions between the candidate compounds and targets, five important predicted and approved targets for RA drugs from our C-T network were selected for docking and MD simulations. Using molecular docking program GOLD (version 5.1), docking simulation was performed. The X-ray crystal structures of five targets (F2, MAOB, PIM1, COX-1 and NOS) were extracted from RCSB Protein Data Bank. The binding site was defined as the volume of co-crystalized ligands in the template proteins. Since water molecules are also essential to stabilizing the ligand-receptor complex, we retained all water molecules of the crystal structure for docking study. The radius around the ligand was set 10 Å in the crystal structure as the binding pocket and the 10 top-ranked docking poses were selected for further analysis. In addition, employing AMBER 10.0 software package22 and the general AMBER force field, all-atom MD simulations were performed in a water solvated simulation box. Through the Berendsen thermostat approach, the temperature was set to a constant. The value of the isothermal compressibility was set at 4.5 × 10-5 bar-1, and to keep the pressure at 1 bar, the Parrinello-Rahman scheme was carried out.23 Moreover, to calculate the electrostatic energy, we employed the particle mesh Ewald method.23 Finally, the full system was subjected to energy minimization and then equilibrated by a 500ps MD simulation at 300 K employing the algorithm of the steepest descent for 10000 steps. 2.6 Calculations of Binding Free Energy Using the MM-PBSA method, the energetic contributions of protein-ligand



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binding affinities were explored. For different protein-ligand systems, the free energy of the binding was computed using the following equations: ∆Gbind = ∆EMM + ∆Gsol - T∆S ∆GMM = ∆Einternal + ∆Eelectrostatic + ∆Evdw

(3) (4)

∆Gsol = ∆GPB + ∆GSA (5) where ∆EMM represents the interaction energy between the receptor and the ligand, which is the sum of the electrostatic (∆Eelectrostatic) and van der Waals (∆Evdw) energies. ∆Gsol is the solvation energy, which includes the electrostatic contribution to the solvation free energy (∆GPB) and the non-polar contribution to the free energy of desolvation (∆GSA). T∆S denotes the conformational entropy contribution, which can be neglected due to the expensive computational cost and low prediction accuracy.24,25 2.7 Experimental Validation For validating the reliability of the obtained C-T networks, the in vitro experiments were constructed to quantify the inhibitory effects of compounds on their predicted targets. Following the rules of randomness and availability, the drug-target interactions were selected and the F2, MAOB, PIM1, COX-1 and NOS inhibition assay (BioVision) were performed according to the manufacturer’s instructions. The compounds quercetin, kaempferol, isorhamnetin, eugenol, rutin, chlorogenic acid, catechin and taxifolin (with purities of ≥ 98%) were obtained from YuanYe Technology Ltd. (Shanghai, China). All compounds were freshly prepared and dissolved in DMSO. 3 RESULTS 3.1 Herbal Medicines for Treating RA As displayed in Table 1, a total of 7 herbs were significantly correlated with RA. Among them, Radix Angelicae Biseratae obtains the highest ratio (12.44%; with p ≤ 0.01), indicating that this herb may exert a crucial role for treating RA. Actually, this herb was already widely used in TCM for dispelling pathogenic wind and removing dampness in the treatment of rheumatism and RA.26 The second important one is Anemarrhenae Rhizoma (7.33%; with p ≤ 0.01), followed by Cinnamomi Ramulus (4.56%; with p ≤ 0.01), Paeoniae Radix Alba (3.03%; with p ≤ 0.01) and so forth. Further exploration also shows that all 7 herbs with their chemical components have been used in Chinese and Japanese folk medicine for treating RA. After removing the overlapped chemicals, finally we obtain a total of 1009 ingredients for these herbs from our database TCMSP.


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Table 1. The species and genus of the herbs and the correlations between herbs with RA Number of articles Herb HQ DG BS ZH FZ GZ ZM

Species

Genus

Fabaceae27 Lamiaceae28 Ranunculaceae29 Apiaceae30 Ranunculaceae31 Lauraceae32 Liliaceae33

Astragalus membranaceus Salvia miltiorrhiza Bunge Paeonia lactiflora Pall. Angelica pubescens Aconitu; mcarmichaeli Debx. Cinnamomum cassia Presl Anemarrhena asphodeloides

Total (n)

Relevant to RA (k ratio; p-value)

77618 79217 35258 22251 27803 43025 10564

1071 (1.38%; p ≤ 0.01) 1638 (2.07%; p ≤ 0.01) 1069 (3.03%; p ≤ 0.01) 2769 (12.44%; p ≤ 0.01) 775 (2.78%; p ≤ 0.01) 1962 (4.56%; p ≤ 0.01) 775 (7.33%; p ≤ 0.01)

Anemarrhenae Rhizoma (ZM); Radix Angelicae Biseratae (ZH); Radix Paeoniae Alba (BS); Aconiti Lateralis Radix Praeparata (FZ); Cinnamomi Ramulus (GZ); Angelicae Sinensis Radix (DG); Radix Astragali seu Hedysari (HQ).

3.2 Bioactive Compounds Screened by PreOB and PreDL Due to the multi-component feature of herb medicine, screening the drugs with satisfactory pharmacokinetic properties to overcome different barriers for reaching market is very crucial. Presently, two reliable in silico models, i.e., PreOB and PreDL were applied to filter the satisfactory active pharmaceutical ingredients from these anti-RA herbs. As a result, a total of 117 bioactive ingredients, occupying 117/1009 of the compound dataset, are obtained and summarized in Table 2. Here, for simplicity, three representative herbs, i.e., Radix Paeoniae Alba, Anemarrhenae Rhizoma and Cinnamomi Ramulus are used to explain the screening principles in detail.



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Table 2. Bioactive compounds with their OB and DL values predicted. ID

Compound Name

OB

BS01 BS02 BS03 BS04 BS05 BS06 BS07 BS08 BS09 BS10 BS11 DG01 DG02 DG03 DG04 DG05 DG06 DG07 DG08 DG09 DG10 DG11 DG12

DG14 DG15 DG16 DG17

4-O-galloylalbiflorin_qt Catechin Paeonol Benzoylpaeoniflorin Palbinone 2-Furylmethyl ketone Di-(2-ethylhexyl) phthalate Lactiflorin Albiflorin_qt Paeoniflorin Paeonin_qt 2-(4-methylphenyl)-H-imidazole α-spinasterol Marmesinin_qt z-ligustilide Archangelicin Flazine Columbianedin Angelol B Oxypeucedanin hydrate Heralenol Pabulenol Columbianetin acetate 2''-O-(2'''-methylbutyryl)Isoswertisin_qt Isoimperaterin Imperatorin Berfeldine A Nodakenin_qt

FZ01

DL

Herbs

78.42 44.78 32.10 31.14 40.74 38.75 43.59 36.58 41.25 29.86 41.14 31.57 42.98 82.28 48.44 37.10 109.30 87.14 67.86 36.01 72.63 44.28 52.06

0.80 0.24 0.04 0.54 0.53 0.48 0.35 0.33 0.33 0.40 0.27 0.95 0.76 0.18 0.07 0.65 0.39 0.36 0.35 0.29 0.29 0.26 0.26

Radix Paeoniae Alba Radix Paeoniae Alba Radix Paeoniae Alba Radix Paeoniae Alba Radix Paeoniae Alba Radix Paeoniae Alba Radix Paeoniae Alba Radix Paeoniae Alba Radix Paeoniae Alba Radix Paeoniae Alba Radix Paeoniae Alba Angelicae Sinensis Radix Angelicae Sinensis Radix Angelicae Sinensis Radix Angelicae Sinensis Radix Angelicae Sinensis Radix Angelicae Sinensis Radix Angelicae Sinensis Radix Angelicae Sinensis Radix Angelicae Sinensis Radix Angelicae Sinensis Radix Angelicae Sinensis Radix Angelicae Sinensis Radix

33.78

0.24

Angelicae Sinensis Radix

39.38 31.01 42.11 79.04

0.23 0.22 0.18 0.18

Episesamin

56.55

0.83

FZ02

β-sitosterol

36.91

0.75

FZ03

Daucosterol_qt

36.91

0.75

FZ04

Karacoline

48.94

0.73

Angelicae Sinensis Radix Angelicae Sinensis Radix Angelicae Sinensis Radix Angelicae Sinensis Radix Aconiti Lateralis Radix Praeparata Aconiti Lateralis Radix Praeparata Aconiti Lateralis Radix Praeparata Aconiti Lateralis Radix Praeparata

DG13


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To be continued ID

Compound Name

OB

DL

FZ05

Isotalatizidine

46.71

0.73

FZ06

Columbianine

63.33

0.73

FZ07

Songorine

55.27

0.72

FZ08

12-epi-napelline

36.63

0.72

FZ09

Karakanine

81.00

0.53

GZ01 GZ02 GZ03 GZ04 GZ05 GZ06 GZ07

6-Hydroxystigmast-4-en-3-one Manoyl oxide Styrene 2-Phenylethyl ester benzoic acid Elaidic acid Taxifolin Epicatechin

39.81 38.05 29.34 34.87 34.23 51.81 48.96

0.79 0.24 0.01 0.37 0.29 0.27 0.24

HQ01

Methylnissolin-3-O-glucoside

36.74

0.92

HQ02

Eugenol

56.23

0.28

HQ03

Alexandrin_qt

36.91

0.75

HQ04

Hederagenin

36.91

0.75

HQ05

(+)-Syringaresinol

40.46

0.72

HQ06

Folic acid

68.96

0.71

HQ07

AstragalosideIV_qt

60.85

0.69

HQ08

Bifendate

31.08

0.67

HQ09

Rutin

3.20

0.68

HQ10

3,9-di-O-methylnissolin

77.25

0.48

HQ11

Methylnissolin-3-O-glucoside_qt

55.49

0.42


Herbs Aconiti Lateralis Radix Praeparata Aconiti Lateralis Radix Praeparata Aconiti Lateralis Radix Praeparata Aconiti Lateralis Radix Praeparata Aconiti Lateralis Radix Praeparata Cinnamomi Ramulus Cinnamomi Ramulus Cinnamomi Ramulus Cinnamomi Ramulus Cinnamomi Ramulus Cinnamomi Ramulus Cinnamomi Ramulus Radix Astragali seu Hedysari Radix Astragali seu Hedysari Radix Astragali seu Hedysari Radix Astragali seu Hedysari Radix Astragali seu Hedysari Radix Astragali seu Hedysari Radix Astragali seu Hedysari Radix Astragali seu Hedysari Radix Astragali seu Hedysari Radix Astragali seu Hedysari Radix Astragali seu Hedysari


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To be continued ID

Compound Name

HQ12 HQ13 HQ14 HQ15 HQ16 HQ17 HQ18 HQ19 HQ20 HQ21 HQ22 HQ23 HQ24 HQ25 HQ26 HQ27 HQ28 ZH01 ZH02 ZH03 ZH04

Astrapterocarpan Phyllanthin Odoratin (Dipteryx) Astraisoflavan glucoside_qt Isorhamnetin 7-O-methylisomucronulatol Quercetin Ononin_qt Isoflavanone Hirsutrin Castanin Rhamnocitrin-3-O-glucoside_qt ZINC14758732 Chlorogenic acid Astraisoflavanin_qt 5-O-Methylvisammioside Formononetin Ammijin_qt Sitogluside_qt Zosimin Angelol D

OB

DL

Herbs

40.63 33.31 65.94 173.44 49.60 67.60 46.43 32.42 111.02 47.88 71.82 107.11 69.64 62.77 71.32 73.93 68.33 82. 50 36.91 53.06 35.03

0.42 0.42 0.30 0.30 0.31 0.30 0.28 0.21 0.30 0.28 0.27 0.27 0.27 0.26 0.26 0.25 0.21 0.18 0.75 0.36 0.34

Radix Astragali seu Hedysari Radix Astragali seu Hedysari Radix Astragali seu Hedysari Radix Astragali seu Hedysari Radix Astragali seu Hedysari Radix Astragali seu Hedysari Radix Astragali seu Hedysari Radix Astragali seu Hedysari Radix Astragali seu Hedysari Radix Astragali seu Hedysari Radix Astragali seu Hedysari Radix Astragali seu Hedysari Radix Astragali seu Hedysari Radix Astragali seu Hedysari Radix Astragali seu Hedysari Radix Astragali seu Hedysari Radix Astragali seu Hedysari Radix Angelicae Biseratae Radix Angelicae Biseratae Radix Angelicae Biseratae Radix Angelicae Biseratae


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To be continued ID

Compound Name

ZH05 ZH06 ZH07 ZH08 ZH09 ZH10 ZH11 ZH12 ZM01 ZM02 ZM03 ZM04 ZM05 ZM06 ZM07 ZM08 ZM09 ZM10 ZM11 ZM12 ZM13 ZM14 ZM15 ZM16 ZM17 ZM18 ZM19 ZM20 ZM21 ZM22 ZM23 ZM24 ZM25 ZM26 ZM27 ZM28 ZM29 ZM30 ZM31 ZM32 ZM33

Angelol G ZINC14589867 O-Acetylcolumbianetin Isoimperatorin Ammidin Angelicone Marmesin Marmesine Macrostemonoside F_qt Timosaponin C_qt Anemarsaponin B_qt Timosaponin B_qt Timosaponin B III_qt Timosaponin C2_qt Timosaponin H2_qt Timosaponin B VI_qt Anemarsaponin E_qt Timosaponin BI_qt Timosaponin D2_qt Timosaponin I2_qt Anemarrhenasaponin II_qt Anemarrhenasaponin Ia_qt Timosaponin J_qt Smilagenone Tingenone Anemarsaponin G_qt Stigmasterol Chinoinin Hippeastrine Chrysanthemaxanthin Asperglaucide Anhydroicaritin Squalene Mangiferin_qt Cis-N-Feruloyltyramine Afzelin_qt kaempferol Neomangiferin_qt Chinoinin_qt Coumaroyltyramine Timosaponin A-III_qt

OB

DL

46.35 45.75 56.97 30.89 41.30 119.11 50.20 84.78 35.26 35.26 35.26 35.26 35.26 35.12 35.12 30.67 30.67 30.67 30.67 30.67 31.38 31.38 31.13 37.35 38.23 52.46 43.83 32.30 51.26 38.72 58.02 110.14 33.55 18.79 117.68 42.67 42.06 102.75 100.13 110.71 4.44

0.34 0.34 0.26 0.23 0.22 0.19 0.17 0.18 0.87 0.87 0.87 0.87 0.87 0.86 0.86 0.86 0.86 0.86 0.85 0.86 0.84 0.84 0.84 0.81 0.80 0.79 0.76 0.75 0.62 0.58 0.52 0.44 0.43 0.22 0.26 0.24 0.24 0.22 0.22 0.20 0.81


Herbs Radix Angelicae Biseratae Radix Angelicae Biseratae Radix Angelicae Biseratae Radix Angelicae Biseratae Radix Angelicae Biseratae Radix Angelicae Biseratae Radix Angelicae Biseratae Radix Angelicae Biseratae Anemarrhenae Rhizoma Anemarrhenae Rhizoma Anemarrhenae Rhizoma Anemarrhenae Rhizoma Anemarrhenae Rhizoma Anemarrhenae Rhizoma Anemarrhenae Rhizoma Anemarrhenae Rhizoma Anemarrhenae Rhizoma Anemarrhenae Rhizoma Anemarrhenae Rhizoma Anemarrhenae Rhizoma Anemarrhenae Rhizoma Anemarrhenae Rhizoma Anemarrhenae Rhizoma Anemarrhenae Rhizoma Anemarrhenae Rhizoma Anemarrhenae Rhizoma Anemarrhenae Rhizoma Anemarrhenae Rhizoma Anemarrhenae Rhizoma Anemarrhenae Rhizoma Anemarrhenae Rhizoma Anemarrhenae Rhizoma Anemarrhenae Rhizoma Anemarrhenae Rhizoma Anemarrhenae Rhizoma Anemarrhenae Rhizoma Anemarrhenae Rhizoma Anemarrhenae Rhizoma Anemarrhenae Rhizoma Anemarrhenae Rhizoma Anemarrhenae Rhizoma


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3.2.1 Radix Paeoniae Alba Radix Paeoniae Alba, the root of Paeonia lactiflora Pall, has been commonly used as an herbal medicine in China.34 Due to its antispasmodic, tonic, astringent and analgesic properties, this herb is traditionally used in TCM for the treatment of RA, hemicranias, and constitutional hypotension.35 It has also been reported that Radix Paeoniae Alba exhibits diverse pharmacological actions such as anti-inflammatory, anti-oxidant, anti-allergic, anti-thrombosis, immune-regulating, cognition-enhancing, anti-hyperglycemic effects and kidney protection effect in diabetic rats.36 Furthermore, significant amounts of monoterpenoid glucosides, tannins, phenolic acids, triterpenes, saponins, and other substances extracted from Radix Paeoniae Alba are usually considered to be the main bioactive compounds. In the current work, based on ADME analysis, 11 out of 112 compounds with favorable OB and DL values are obtained from this herb. Among them, three representative monoterpene glycosides, i.e., albiflorin, paeoniflorin and benzoylpaeoniflorin show potent biological activities.37 For example, paeoniflorin (DL = 0.40, OB = 29.86%) and albiflorin (DL = 0.33, OB = 41.25%), as major active monoterpene glycosides of this herbal medicine, have been reported showing anti-inflammatory and analgesic effects, thus are regarded as the candidate compounds for treating RA.38 Previous studies also demonstrated that paeoniflorin potently suppressed the index of joint swelling and polyarthritis, and markedly enhanced the index of immune organ weight and decreased the joint injury, indicating that paeoniflorin is therapeutically effective in treatment of RA.39 3.2.2 Anemarrhenae Rhizoma Anemarrhenae Rhizoma is an important crude drug prepared from the rhizome of Anemarrhena asphodeloides Bge.40 As a kind of TCM recorded in Chinese Pharmacopoeia, it has been employed clinically for centuries to treat various diseases.41 Modern pharmacological studies have demonstrated multiple activities of Anemarrhenae Rhizoma, including anti-inflammatory, anti-pyretic, anti-platelet aggregation and anti-pathogenic microorganism effects as well as hypoglycemic effects.42 There are numerous and diverse chemical ingredients in Rhizoma Anemarrhenae, containing steroidal saponins and anthone C-glycosides with various bioactivities. In this herb, up to date 175 compounds have been identified from the crude Anemarrhenae Rhizoma, out of which 31 molecules possess satisfactory OB and favorable DL properties. Among these ingredients, steroidal saponins with diverse structures are the main active components of Anemarrhenae Rhizoma, which also possess wide biological and pharmacological activities. For example, phytochemical studies proved that the steroid saponin timosaponin BIII was one of the main active compounds from Anemarrhenae Rhizoma.43 Emerging evidence also confirmed the anti-inflammatory, anti-osteoporosis, anti-oxidant and anti-coagulated blood activities of this compound.43 Actually, timosaponin BIII significantly prevented the activation of NF-κB and MAPK, as well as the phosphorylation of IRAK1, TAK1, and IκBα in LPS-stimulated macrophages, which is widely used in the treatment of RA.43 Apart


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from the steroidal saponins, xanthones are also major constituents of Anemarrhenae Rhizoma. For instance, neomangiferin, as main xanthone of Anemarrhenae Rhizoma, acts as an antioxidant agent and presents antitumor activities, etc.44 Also, by inhibiting the NF-κB and MAPK pathway and preventing the release of inflammatory mediators and cytokines, neomangiferin shows anti-inflammatory effects.45 In addition, anemarsaponin B presents anti-inflammation properties as well by inhibiting IL-1 β, IL-6, and TNF-α expression, possibly via the p38 MAP kinase pathway and NF-κB signal pathway.46 All these anti-inflammatory effects are markedly associated with the treatment of RA. Additionally, although some compounds have low OB, these chemicals also exhibit significant biological activities related with RA. For instance, studies in RAW 264.7 macrophages suggested that mangiferin (OB = 7.6%) had anti-inflammation effect since it down-regulated the levels of COX-2, IL-6, iNOS and TNF-α and inhibited the activation of NF-κB pathway.47 Moreover, timosaponin A-III, one of the herb ingredients obtained from Anemarrhenae Rhizoma, alleviated the inflammation and oxidative damages, showing its pharmaceutical potential in the treatment of RA.48 Owing to these profound pharmacological effects, mangiferin and timosaponin A-III are also selected for further research as well. 3.2.3 Cinnamomi Ramulus Belonging to the family of lauraceae, Cinnamomi Ramulus is the young stem of Cinnamomum cassia PRESL.49 As one of the most important TCM, Cinnamomi Ramulus has been commonly used in Asia and Europe to treat maladies involving blood circulation and inflammation.50 Through preventing the expression of various genes related to inflammatory responses like inducible iNOS, COX-2 and inhibiting the production of NO in the central nervous system (CNS) and periphery, components of Cinnamomi Ramulus present anti-inflammatory effects,51 and this herb is therefore considered as a potential for preventing or treating inflammation diseases like RA.51 Moreover, Cinnamomi Ramulus can act as an anti-oxidant, mediating anti-inflammatory effects and repressing cyclooxygenase as well as hydroperoxidase functions.52 Presently, a total of 7 ingredients (Table 2) with favorable pharmacokinetic activities are extracted from this herb and most of them have, actually, been reported as bioactive substances. For example, taxifolin with good OB of 51.81% and a DL value of 0.27 has been reported to exhibit an inhibitory effect on neutrophil adhesion, presenting the possible mechanism of the anti-inflammatory activity of this component.53 Moreover, taxifolin also inhibited the activities of serum aspartate and alanine aminotransferase induced by the inflammatory reaction.54 Through regulating free radicals reactions, taxifolin prevented biomolecules from oxidative damage.54 Moreover, β-sitosterol (OB = 36.91%, DL = 0.75), another bioactive compound of Cinnamomi Ramulus, exerted acknowledged analgesic and anti-inflammatory effects through suppression of the formation of prostaglandins and bradykinins.55 Also, β-sitosterol reduced the levels of NO production and the expression of IL-6, TNF-α and IL-1β in LPS-activated macrophage cells, which are involved in the chronic



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inflammatory process of RA.56 To sum up, a total of 117 candidate compounds (Table 2) are obtained from the prescreening models and used for further study. 3.3 Drug Targeting and Network Construction Considering the fact that most bioactive molecules of herbs act by binding to specific proteins and some TCM might target multiple proteins due to the existence of its multiple active components, drug targeting should be of help in shedding light on TCM’s mechanism of action on RA from the perspective of network pharmacology. In this section, in order to probe the binding of Chinese herbs to their targets in RA, a robust and unbiased drug targeting method20 we previously developed was applied. As a result, 85 predicted targets (Table 3) in total are screened out, which are targeted by 117 candidate components from the seven herbs.


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Table 3. The information of anti-RA-related targets of seven herbs Protein Name

Gene Name

UniProt ID

Muscarinic acetylcholine receptor M4 Muscarinic acetylcholine receptor M5 Alpha-1A adrenergic receptor Alpha-1B adrenergic receptor Calcium-activated potassium channel subunit alpha-1 Mu-type opioid receptor Progesterone receptor Muscarinic acetylcholine receptor M3 Muscarinic acetylcholine receptor M2 Muscarinic acetylcholine receptor M1 Retinoic acid receptor RXR-alpha DNA topoisomerase 2-alpha Carbonic anhydrase 2 Prostaglandin G/H synthase 1 (COX-1) Prostaglandin G/H synthase 2 (COX-2) Androgen receptor Nitric oxide synthase, inducible Nitric oxide synthase, endothelial Estrogen receptor Estrogen receptor beta Serine/threonine-protein kinase Chk1 Serine/threonine-protein kinase pim-1 Alpha-1D adrenergic receptor Alpha-2A adrenergic receptor Alpha-2B adrenergic receptor Alpha-2C adrenergic receptor Delta-type opioid receptor Coagulation factor X Prothrombin Coagulation factor VII Glucocorticoid receptor Vascular endothelial growth factor receptor 2 Sodium-dependent dopamine transporter Sodium-dependent noradrenaline transporter Sodium-dependent serotonin transporter Glycogen synthase kinase-3 beta Mitogen-activated protein kinase 14 Mitogen-activated protein kinase 1 Cell division protein kinase 2

CHRM4 CHRM5 ADRA1A ADRA1B KCNMA1 OPRM1 PGR CHRM3 CHRM2 CHRM1 RXRA TOP2A CA2 PTGS1 PTGS2 AR NOS2 NOS3 ESR1 ESR2 CHEK1 PIM1 ADRA1D ADRA2A ADRA2B ADRA2C OPRD1 F10 F2 F7 NR3C1 KDR SLC6A3 SLC6A2 SLC6A4 GSK3B MAPK14 MAPK1 CDK2

P08173 P08912 P35348 P35368 Q12791 P35372 P06401 P20309 P08172 P11229 P19793 P11388 P00918 P23219 P35354 P10275 P35228 P29474 P03372 Q92731 O14757 P11309 P25100 P08913 P18089 P18825 P41143 P00742 P00734 P08709 P04150 P35968 Q01959 P23975 P31645 P49841 Q16539 Q16539 P24941



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To be continued Protein Name Tyrosine-protein phosphatase non-receptor type 1 Trypsin-1 Dipeptidyl peptidase 4 Alcohol dehydrogenase 1B Peroxisome proliferator-activated receptor gamma Cyclin-A2 Nuclear receptor coactivator 2 Beta-2 adrenergic receptor Calmodulin Sodium channel protein type 5 subunit alpha cAMP-dependent protein kinase catalytic subunit alpha Gamma-aminobutyric-acid receptor subunit alpha-1 Acetylcholinesterase Mineralocorticoid receptor cGMP-inhibited 3',5'-cyclic phosphodiesterase A D(1A) dopamine receptor Leukotriene A-4 hydrolase Neuronal acetylcholine receptor subunit alpha-7 Tumor necrosis factor Nuclear receptor coactivator 1 Amine oxidase [flavin-containing] B Amine oxidase [flavin-containing] A Potassium voltage-gated channel subfamily H member 2 Beta-1 adrenergic receptor cAMP-dependent protein kinase inhibitor alpha 5-hydroxytryptamine 3 receptor 3-hydroxy-3-methylglutaryl-coenzyme A reductase Interleukin-6 Interleukin-4 Interleukin-2 Interleukin-8 Interleukin-5 Interleukin-13 Interleukin-17 Ig gamma-1 chain C region Caspase-3 Apoptosis regulator Bcl-X Tyrosine phenol-lyase Hepatocyte growth factor receptor Gamma-aminobutyric-acid receptor subunit alpha-2

Gene Name

UniProt ID

PTPN1 PRSS1 DPP4 ADH1B PPARG CCNA2 NCOA2 ADRB2 CALM1 SCN5A PRKACA GABRA1 ACHE NR3C2 PDE3A DRD1 LTA4H CHRNA7 TNF-a NCOA1 MAOB MAOA KCNH2 ADRB1 PKIA HTR3A HMGCR IL-6 IL-4 IL-2 IL-8 IL-5 IL-13 IL-17 IGHG1 CASP3 BCL2 TYR MET GABRA2

P18031 P07477 P27487 P00325 P37231 P20248 Q15596 P07550 P62158 Q14524 P17612 P14867 P22303 P08235 Q14432 P21728 P09960 P36544 P01375 Q15788 P27338 P21397 Q12809 P08588 P61925 P46098 P04035 P05231 P05112 P60568 P10145 P05113 P35225 Q16552 P01857 P42574 Q07817 P31013 P08581 P47869


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To be continued Protein Name

Gene Name

UniProt ID

Alcohol dehydrogenase 1C Epidermal growth factor receptor Chymotrypsinogen B Alcohol dehydrogenase 1A Heat shock protein HSP 90-alpha Phosphatidylinositol-4,5-bisphosphate subunit gamma isoform

ADH1C EGFR CTRB1 ADH1A HSP90AA1 PIK3CG

P00326 P00533 P17538 P07327 P07900 P48736

3-kinase

catalytic

3.3.1 C-T Network Analysis To uncover the synergistic effects of multi-components and multi-targets in RA-related herbs as well as to assess their mechanisms of action, a C-T network analysis was performed. After removing 14 compounds with no target proteins, a graph of C-T interactions (Fig. 2) was constructed using 117 candidate compounds with their corresponding targets (The detailed information about C-T network is provided in Table S1 of Supporting Information). For most active compounds, they are hit by more than one targets, among which HQ17 has the highest number of targets (degree = 44), followed by HQ10 (degree = 35), HQ11 (degree = 34), HQ12 (degree = 31), demonstrating crucial roles of these components. The average number of target proteins for every drug is 13, indicating the multi-target properties of ingredients of these herbs. With respect to the candidate targets, the average number of chemicals for every target is 15, revealing the multi-component features of these herbs. Among these targets, ESR1 possesses the largest degree (Degree = 84), followed by PTGS2 (Degree = 60), NOS2 (Degree = 55), CDK2 (Degree = 48), demonstrating their potential therapeutic effects for treating RA.

Figure 2. The C-T network was constructed by linking the candidate compounds (hexagon) with their potential targets (circles). ZM, Anemarrhenae Rhizoma; ZH, Radix Angelicae Biseratae; BS, Radix Paeoniae Alba; FZ, Aconiti Lateralis Radix Praeparata; GZ, Cinnamomi Ramulus; DG,



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Angelicae Sinensis Radix; HQ, Radix Astragali seu Hedysari.

Since a TCM formula often contains multiple interactive herbs who work usually synergistically, it is customary to rank the compositions into four categories, namely, Jun, Chen, Zuo and Shi (monarch, minister, assistant and guide) with proper herbs to strengthen the therapeutic effects and decrease the side-effects when analyzing the roles of herbs in the TCM formula. Presently, 33 active compounds from Anemarrhenae Rhizoma which has the highest number of bioactive components among seven herbs are considered to play leading roles in treating RA. By the analysis of C-T network, it is found that most connected targets of ingredients in Anemarrhenae Rhizoma is involved in the treatment of RA. Additionally, many targets of the active compounds in this herb like kaempferol (ZM29), anhydroicaritin (ZM24), coumaroyltyramine (ZM32), etc., are the main regulators controlling various singling pathways and play central roles (hubs) in the C-T Network. With the largest number of active molecules and powerful pharmacological effects, Anemarrhenae Rhizoma is therefore considered as the monarch herbal medicine, playing a Jun role in the potency of the formula for treating RA. With respect to a Chen herb, assisting the Jun herb is the primary mission in the TCM theory. In the current work, Radix Astragali seu Hedysari includes 29 ingredients, containing the second large number of bioactive compounds, with middle degree in all 7 herbs. The mean number of target proteins for every component is 20, showing that Radix Astragali seu Hedysari could enhance the pharmacological synergism. Therefore, Radix Astragali seu Hedysari is regarded as a Chen herb which helps strengthen the curative effect of the Jun herb Anemarrhenae Rhizoma, or, it is used for the treatment of accompanying symptoms. For other five herbs, due to lower number of active ingredients they contained and fewer target proteins they displayed, they serve as assistant and messenger drugs. For example, Paeoniae Radix Alba has long been used as a component of traditional Chinese prescription to eliminate stasis, reduce fever, relieve pain and activate blood circulation.57 It also shows a synergistic interaction with Glycyrrhizae Radix for the treatment of pain.58 Although containing only fewer active compounds, those five herbs might have broad pharmacological actions with Jun/Chen herbs and are thus employed to improve the pharmacological activity of these monarch and ministerial herbs. Taken together, these seven herbs work together harmoniously through multi-components and multi-targets, which may provide a comprehensive therapeutic efficacy for RA and also clarify the ‘‘Jun-Chen-Zuo-Shi’’ principle of TCM from a system level. Additionally, as we all know, RA is not only a disorder with chronic inflammation but also an angiogenic disease. Tissue damage triggers inflammation, and inflammation stimulates angiogenesis, which in turn causes the repair and growth of tissue. Moreover, in the course of inflammation, the infiltrates of immune cells offer cytokines affecting bone metabolism negatively, which in turn leads to the increased bone resorption.59 Therefore, RA is often denoted as a progressive disease with systemic autoimmunity. Meanwhile, inflammation, angiogenesis and immune systems are the three main fundamental processes implicated in the pathology of RA. Herein,


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we employed network pharmacology to explore the relationship of the active compounds and their targets, which are related to inflammation, angiogenesis and immune systems. As shown in Fig. 3, 52 common targets (accounting for 19.1% of the total targets) are shared by the seven herbs, which are mainly associated with cytokines (inflammation), angiogenesis and immune systems.

Figure 3. C-T-F network was constructed by the ingredients (octagons) and their corresponding protein targets (circles).

Cytokines, the local protein mediators, are implicated in almost all crucial biological processes, which contain inflammation, cell growth and activation, differentiation and immunity.60 Although we do not know what the exact cause of RA is, accumulating evidence has confirmed that the pro-inflammatory cytokines like TNF-α, interleukins-2-6, 8 and 13 play important roles in the pathogenesis of RA.61 Taking TNF-α for an example, with the extensive proinflammatory activities, it is a key mediator of joint inflammation.62 Clinical therapy for RA directed at TNF-α contains the use of specific antibodies and soluble receptor fusion proteins which bind to TNF-α and inhibit its biologic activity,63 showing the importance of TNF-α in RA. Additionally, pathogenesis studies of RA, both in clinical settings and experimental animal models, demonstrate crucial roles of cytokine interleukins in synovial inflammation and the destruction of cartilage and bone tissue.64 For instance, IL-6, a pleiotropic cytokine with multiple effects, is over-expressed in the synovial tissue of RA patients65 and influences the function of monocytes, neutrophils, osteoclasts-cells, B cells and T cells, which are potently triggered in RA. Also, it can induce the hepatic acute-phase response, a crucial characteristic of RA and is associated with the activity of the disease and articular destruction.61 Overall, these observations strongly support the evidence that the cytokines contained in the generated C-T network have important roles in treating RA, further validating the drug targeting approach. For angiogenesis (or new blood vessel growth), as a crucial event in the initiation and persistence of rheumatoid disease, it can be strategically suppressed to decrease



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the inflammation of RA animal models.66 Persistent angiogenesis is essential for maintaining the chronic synovial architecture changes in RA patients and for giving a vital source of cytokines and protease activity.67 Although there are many angiogenic cytokines found in RA joint tissue, vascular endothelial growth factor (VEGF), an endothelial cell-selective angiogenic factor produced by synovial-joint cells, plays an important role in mediating the angiogenic process of RA.69 In addition, COX-1 and COX-2, the mediators of angiogenesis expressed abundantly in RA joints, also promote the angiogenesis process and the development of arthritis.68 Recent studies demonstrated that the genetic deletion of COX-1 significantly inhibited the increased PGE2 levels, which prevented the growth of the mouse mammary tumor and angiogenesis.64 Besides, the proinflammatory activity of COX-2 also increased in the synovial tissue of RA patients and the COX-2-induced angiogenic activity may be a mechanism of action within diseased synovium, providing an additional reason for using COX-2 inhibitors in the treatment of RA.69 Moreover, RA is also a disease with progressive systemic autoimmunity. Several cytokines and sex hormone estrogen generated by immune cells can affect the bone cells, offering a relationship between the immune and bone system of RA.70 Recent studies have suggested that hormone-mediated effects on the programmed cell death 1 (PD-1) signaling pathway are essential to modulate autoimmunity.71 As a matter of fact, animal researches have demonstrated that estrogens present obvious beneficial effects on arthritis, and hormone replacement therapy also shows a positive effect on postmenopausal women with RA.72 Moreover, the presence of estrogen receptors (ERs), ER1 and ER2, is of outstanding importance for treating RA.72 Actually, in the synovial tissue of patients with RA, macrophage-like and fibroblast-like synoviocytes were positive for ER1 and ER2.72 Furthermore, estrogen triggers human monocytes apoptosis, and regulates the release of pro-inflammatory cytokine as well,73 which in turn affects the process of RA. To sum it up, the obtained results suggest that the diverse target proteins of those seven herbs are closely associated with inflammation, angiogenesis and immune systems, demonstrating that the potential therapeutic effect of each drug for combating RA is through the multiple components hitting into multiple relevant target proteins. 3.3.2 C-T-D Network Analysis To investigate the therapeutic potential of these herbs on treating RA, a C-T-D network was built employing the active compounds, target proteins and relevant diseases, which results in 110 target-disease interactions. In this net, about half of the targets are mapped onto multiple diseases associated with RA. As a result, 46 potential targets achieve six types of diseases including the cardiovascular diseases (CVDs), digestive system diseases, lung disease, kidney disease, hyperalgesia and spasmolysis (Table S2 in Supporting Information). The global view of C-T-D network is depicted in Fig. 4, in which hexagon, circle and square nodes represent the active compounds, potential targets and relevant diseases, respectively. As shown in Fig. 4, 8 target proteins like PTGS2, PPARG and NOS2 are


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connected with arthritis, indicating that these targets have direct or indirect effects on the treatment of RA. Actually, the enhanced expression of NOS2 has been observed among peripheral blood mononuclear cells from RA patients, which is correlated with the inflammation of RA. Since most targets contained in the C-T-D network are involved in CVDs, a conclusion is drawn that CVDs may be a potential complication of RA, which is consistent with the proved results that rheumatoid patients have higher incidence of CVDs74 and CVDs are responsible for 35–50% of RA deaths.75 For instance, hypertension is the most common coexisting disease with high blood pressure, and RA patients seem to have high risk of developing hypertension. The target mineralocorticoid receptor (NR3C2) is an influencing factor in blood pressure regulation, and due to the promote action on salt retention in kidney,76 an inhibition of NR3C2 deserves more attention in subsequent anti-RA therapy. Therefore, active management (of target proteins such as NOS2, PTGS2, AR and NR3C1) of hypertension can lead to the reduction of cardiovascular events in the rheumatology clinic of RA patients and may eliminate the excess cardiovascular mortality. Moreover, considerable evidence suggests that RA also has high frequency of heart failure.77 Patients with myocardial infarction have shown increased expression of NOS2 and the activation of NOS2 presents side effects on cardiac structure and function during the myocardial infarction.78 Therefore, the inhibition of NOS2 blocks the cardiac dysfunction both in heart failure and myocardial infarction. Furthermore, emerging evidence indicates that the infection of the urogenital tract generating serious kidney disease and the infection of gastro-intestine system are the frequent causes of RA.79 With respect to lung disease, it is one of the major extra-articular manifestations and may be regarded as a toxic event consequent to the therapy for RA.80 Besides, RA is known to cause continuous pain as recurrent process, and pain is a key component of RA and may increase over time for RA patients.75 Herein, 9 targets such as NOS2, PTGS1 and SCN5A are linked with hyperalgesia and these targets may have effective action on central pain processing, and relieve the pain of RA patients. Overall, the targets shared by diverse diseases should be potentially valuable for the treatment of RA, implying that the synergistic therapeutic effect of a TCM formula is more effective than a single drug.



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Figure 4. C-T-D network. The active compounds are connected with (octagons) their potential target proteins (circles) and relevant diseases (squares). The blue and red circles are the common and specific targets of the diseases, respectively.

3.3.3 T-P Network Analysis Given the fact that the therapeutic effect of drugs is associated with both the protein targets and the signaling pathways related to diseases, presently for understanding the action mechanisms of RA, five major pathways presenting close relationships with RA were extracted from KEGG (www.genome.jp/kegg), which includes VEGF, PI3K-Akt, Toll-like receptor, T cell receptor and Osteoclast differentiation signaling pathways. Subsequently, we mapped all the relevant targets onto these signaling pathways and generated a T-P Network (Fig. 5) to explore the synergistic effects of herbal medicine for the treatment of RA. It is well known that VEGF is a key factor in charge of vascular development and blood vessel invasion in the synovial membrane of patients with RA.81 Aberrant VEGF signaling is a feature of pathologic conditions of RA and in the synovial fluids of RA patients, increased VEGF levels were also observed.81 Additionally, VEGF receptor 1 (VEGFR-1) mediates the immunity of monocytes/macrophages and the proliferation of bone marrow hematopoietic cells. Therefore, it may also promote the chronic inflammation of rheumatoid arthritis,82,83 suggesting that a therapeutic inhibition of VEGFR-1 action might reduce the VEGF signaling, which is beneficial for RA patients. Moreover, phosphoinositide 3-kinases (PI3Ks), the lipid kinases controlling a wide variety of cellular processes, are abundantly expressed in leucocytes where they stimulate the cellular growth, proliferation and migration.84 The various roles of PI3Ks in the immune system suggest that inhibition of this signaling pathway may provide new therapy for autoimmune disease such as RA.84 Actually, pharmaceutical inhibition and genetic inactivation of PI3Ks lead to the impairment of immune


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responses and the decrease of the susceptibility to inflammatory and autoimmune conditions in experimental studies.85 Besides, PI3K-Akt pathway also regulates the cell survival through various target proteins such as KDR, RXRA, NOS3 and GSK3β involved in T-P network. Thus, the administration of PI3K-Akt signaling pathway may be a medicinal potential for treating RA. Additionally, Toll-like receptors (TLRs) signaling pathway is involved in modulating the cell activities on stimulation and plays a fundamental role on the activation of innate immune system.86 Synovia fibroblasts (SFs) from RA joints expressed TLRs pre-dominantly at the sites of attachment and invasion into cartilage and bone. The activation of SFs is a significant feature in the destructive process of RA. Therefore, TLRs signaling pathway, either by initiating or by perpetuating the activation of SFs, may contribute to the RA pathogenesis. Moreover, TNF-α is a therapeutic target for RA as displayed in C-T network and drugs that block TNF-α may decrease the joint inflammation.87 Due to the fact that TLRs not only up-regulate the expression of those agents inducing the inflammation such as TNF-α,88 but also initiate the activation of the adaptive immune responses, the TLRs signaling is possible through mediating these associated targets, thereby exerting the crucial role for the therapeutic effect of RA. With respect to T-cell-receptor (TCR) signaling, it has a central role in functioning of T cells and activation of adaptive immune response.89 T cells from RA patients are hyporesponsive, or anergic to the engagement of antigen receptor.90 Peripheral blood and inflamed synovium persistently stimulate T cells and improve the autologously-mixed lymphocyte reaction when RA synovial dendritic cells activate T cells. The impaired antigen responsiveness of immune suppression is the characteristic for RA patients with severe inflammation. Also, it has been reported that the immune system with ageing may disturb the activation of TCR pathways and contribute to the pathogenesis of RA with genetic variants.91 Actually, the treatment of RA by inhibiting TCR signaling has been proved by experimental results.92 Furthermore, osteoclasts are essential to the restoration of bone. A recent study displayed that in RA patients, abundant osteoclast cells were observed,93 implying that the inhibition of osteoclast differentiation might protect the RA bone. Since RANKL (as receptor activator of nuclear factor κB ligand) is an indicator of osteoclast differentiation, the expression of RANKL in the synovium cells with inflammation may promote the immune or inflammatory processes, which in turn produce osteoclast differentiation factors at sites of bone erosion as much as in osteoclast formation of arthritis.94 Therefore, RANKL inhibitors may provide a novel therapeutic potential to bone loss in RA. Overall, osteoclast differentiation signaling pathway associated with the development of synovitis and bone damage in RA is also a potent perspective for clinical treatment and scientific research of RA. Apart from the five major pathways associated with RA, there are numerous biological cross-talks observed in this net, which refer to one or more target genes of one signaling pathway affecting another one or more pathway(s) at the same time.95 As depicted in Fig. 5, AKT is a cross-talk for PI3K-AKT signaling pathway (orange), osteoclast differentiation (red) and TLRs signaling pathway (blue), while MAPK14 is



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the cross-talk between VEGF (purple), PI3K-AKT (orange), TLRs (blue) and TCR (green) signaling pathways. For the cross-talk Akt, it maintains balance between the apoptotic cell death and proliferation, which are involved in the pathophysiology of RA. Once Akt is activated, it regulates the function of multiple substrates, containing the regulation of cell cycle progression, cell survival, cell permeability angiogenesis and metabolism.96 As a matter of fact, Zhang et al. has found that phosphorylated Akt provides a survival signal in RA synovial fibroblasts through preventing the enhancement of apoptosis.97 Additionally, MAPK14, as another cross-talk involved in the T-P network is found in synovial lining and endothelial cells, exhibiting a crucial effect for inflammatory bone destruction and providing a potential therapeutic target for the treatment of RA.98 Indeed, MAPK14 modulates the production of proinflammatory cytokines involved in the pathogenic process of RA, which are the key regulators of cell differentiation and apoptosis by distinct signaling cascades.99 Numerous studies have indicated that an inhibition of MAPK14 kinase with small-molecule compounds like ZM32, HQ28, GZ06, DG12 and BS02 reduces the bone loss of RA and thus has been successfully applied in the treatment of experimental arthritis. Taken together, all these results suggest that the modulation of active targets in RA-associated pathways is a potent therapeutic therapy for these herbs to cure RA.

Figure 5. Distribution of target proteins on the compressed RA pathways.

3.4 Experimental Confirmation To examine the reliability and reasonability of the above results, the inhibitory effects of the candidate compounds on their predicted targets were determined in vitro by ligand binding assays. The selection of the drug-target interactions follows the principle of random and market readily available. Examination of the binding data indicates that compounds quercetin, kaempferol and isorhamnetin have been identified as potent ligands of COX-1 and NOS (Table 4), which are in good agreements with the results obtained from the SysDT model. These compounds directly bind to COX-1 and NOS, exhibiting a high inhibition ratio at the concentration of 50 µM. For example, when compound quercetin binds to COX-1 and NOS proteins, it generates an inhibition ratio of 59% and 54%, respectively.


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Quercetin is also a potent inhibitor of F2 with an inhibition value of 47% at 50 µM. Actually, quercetin, as one flavonoid of wide biological effects, has been extensively employed in the treatment of inflammation, RA, tumors, etc.100 With the highest inhibitory activity, catechin also binds well to the receptor of COX-1. In addition, compounds eugenol and kaempferol exert inhibitory activities against MAOB with a relatively weak inhibition ratio of 55% and 38% at 100 µM, respectively. Also, kaempferol can inhibit F2 with a ratio of 49% at 50 µM. Besides, isorhamnetin and rutin are examined with the PIM1 inhibition assays and both of them reduce the activity of PIM1 by 55% and 46% at the dose of 100 µM, respectively. The good inhibition of these compounds proves the rationality and reliability of the drug-target interactions, validating the network-based analytical methods. Table 4. Inhibitory rate for selected key C-T interactions. NO.

Target Gene Name

Drug Name

Dosage (µM)

Inhibitory Rate (%)

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F2 F2 MAOB MAOB PIM1 PIM1 COX-1 COX-1 COX-1 COX-1 COX-1 COX-1 NOS NOS NOS NOS

kaempferol quercetin eugenol kaempferol rutin isorhamnetin quercetin catechin kaempferol isorhamnetin rutin chlorogenic acid quercetin kaempferol taxifolin isorhamnetin

50 50 100 100 100 100 50 50 50 50 50 50 50 50 50 50

49 47 55 38 46 55 59 54 52 35 32 31 54 44 33 42

3.5 Molecular Dynamics Simulations In order to test the reliability of the above drug-target interactions and to further explore the accurate binding modes, we selected eight compounds with their corresponding potential target proteins which are approved and possess significant correlations with RA for MD analysis. Presently, 5 ns MD simulations for all the docked complexes were carried out to extract the kinetic conformational changes between the drug and the target, which occurred in aqueous solution. Moreover, the snapshots of the binding conformations of each complex with the key amino acids of the average structure at the last 1 ns of the MD simulations are depicted in Figs. 6, 7 and 8. Obviously, kaempferol and quercetin are located within the binding cavity of F2 (Figs. 6A and B), both of which form two hydrogen bonds and an additional water-mediated hydrogen-bonding interaction, which help the stabilization of these compounds at the binding site. In addition, the MAOB-eugenol and MAOB-kaempferol complexes (Figs. 6C and D) are stabilized by the



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hydrogen-bonding interactions between the ligand and Ala35, Gly58 and Lys96. Water-mediated hydrogen bonding interactions are also observed in the MAOB binding site. Figs. 6E and F demonstrate that rutin and isorhamnetin are directed towards the binding pocket in the entrance cavity of the PIM1, establishing hydrogen bonds interactions with residues Asp131, Asp108, Lys67, Gly47 and Gly89.

Figure 6. Hydrogen-bonding networks within the binding site of the drug-target complexes obtained from MD simulation. (A) F2-kaempferol, (B) F2-quercetin, (C) MAOB-eugenol, (D) MAOB-kaempferol, (E) PIM1-rutin, (F) PIM1-isorhamnetin. The molecules are present as ball and stick models. Dotted black lines in these pictures represent H-bonds with distance unit of Å. Other O and N atoms are colored as red and blue, respectively.

Fig. 7 depicts the binding interactions of compounds quercetin, kaempferol, catechin, isorhamnetin, rutin and chlorogenic acid with COX-1. Clearly, the interaction modes of quercetin and kaempferol with their receptors present common characteristics in terms of the crucial residues and hydrogen-bond interactions in the binding site. In the binding pocket of COX-1, Ala199 and Asn382 solidly form two hydrogen bonds with compounds quercetin and kaempferol (Figs. 7A and B). π-π interactions of the ligands with His386 are also found in these two active pockets (Figs. 7A and B). For compound catechin, it is located at the binding site by hydrogen bond interactions with residues Trp387, Asn382 and Tyr385 and by a π-π interaction with His354 within the receptor COX-1 (Fig. 7C). As to isorhamnetin, there are two H-bonds formed by the H-bond donor of this compound with residues His388, Asn382, and a p-cation interaction existing between residue His386 and the phenyl linker (Fig. 7D) of this compound, which is crucial to its binding affinity with COX-1. With respect to rutin, three H-bonds are observed with Tyr385, Asn382 and Thr212 in the binding pocket of COX-1 (Fig. 7E). Binding of chlorogenic acid to COX-1 shows that three H-bonds are formed by the ligand and the carboxyl group of Glu203, Tyr385 and Thr212 (Fig. 7F). On the basis of these experimental and computational results, it is summarized that these compounds should act as potential COX-1 inhibitors.


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Figure 7. Binding interactions of COX-1 with its ligands. (A) COX-1-quercetin, (B) COX-1-kaempferol, (C) COX-1-catechin, (D) COX-1-isorhamnetin, (E) COX-1-rutin and (F) COX-1-chlorogenic acid. The molecules are present as ball and stick models. Dotted black lines in these pictures represent H-bonds with distance unit of Å. Other O and N atoms are colored as red and blue, respectively.

Additionally, the binding conformations of compounds quercetin, kaempferol, taxifolin, and isorhamnetin with NOS are depicted in Fig. 8. Clearly, it is observed that the binding modes of quercetin, kaempferol and isorhamnetin with NOS present common characteristics in terms of the crucial residues and H-bond interactions in the binding site. The three compounds form one H-bond with residue Asn370 and a water-mediated hydrogen-bonding interaction with Trp372. Besides, two edge-to-face π-π interactions are also found between the taxifolin and isorhamnetin with Trp194 and Phe368. Based on these findings, we can see that hydrogen bonding, water-mediated hydrogen-bonding and edge-to-face interactions play key roles in the protein-ligand recognition and stability, which may be helpful in determining the inhibitor activities.

Figure 8. Binding conformations of four complexes, i.e., NOS-quercetin (A), NOS-kaempferol (B), NOS-taxifolin (C) and NOS-isorhamnetin (D) from the MD simulation. The molecules are



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shown as a ball and stick model. The dotted black lines in these pictures represent H-bonds with the distance unit of Å. O and N atoms are colored as red and blue, respectively.

3.6 Calculation of Binding Free Energy Since binding free energy can reflect the binding affinity of the ligands, presently, to obtain a quantitative evaluation of the difference in affinities for the studied compounds with their target proteins, the binding affinities of the eight compounds were computed employing the MM-PBSA approach. The binding free energy is the sum of various potential energies with their detailed contributions depicted in Table 5. Table 5. Contributions of various energy components to the binding free energy (kcal mol-1) Component

∆Evdwz

∆Eelectrostatic

∆GPB/GB

∆GSA

∆Egas(EMM)

∆Gsol

∆Gbind

F2-kaempferol F2-quercetin MAOB-eugenol MAOB-kaempferol PIM1-rutin PIM1-isorhamnetin COX-1-quercetin COX-1-catechin COX-1-kaempferol COX-1-isorhamnetin COX-1-rutin COX-1-chlorogenic acid NOS-quercetin NOS-kaempferol NOS-taxifolin NOS-isorhamnetin

-46.62 -43.23 -39.58 -40.16 -38.22 -44.14 -51.05 -44.36 -46.24 -36.75 -20.31 -32.47 -51.14 -37.46 -26.70 -35.27

-13.22 -11.76 -9.22 -8.95 0.38 1.77 -10.35 -6.16 -5.33 -15.51 0.86 -12.61 -2.62 -11.24 -5.67 -11.63

44.33 43.35 36.33 39.14 25.33 26.37 36.37 28.15 39.15 40.86 11.72 38.22 34.87 35.19 26.77 37.80

-3.56 -4.11 -3.68 -2.11 -2.26 -3.22 -3.24 -2.95 -3.84 -3.76 -4.75 -1.93 -3.39 -4.34 -3.81 -4.73

-59.84 -54.99 -48.80 -49.11 -37.84 -42.37 -61.4 -50.52 -51.57 -52.26 -19.45 -45.08 -53.76 -48.7 -32.37 -46.9

40.77 39.24 32.65 37.03 23.07 23.15 33.13 23.20 35.31 37.10 6.97 36.29 31.48 30.85 22.96 33.07

-19.07 -15.75 -16.15 -12.08 -14.77 -19.22 -28.27 -25.32 -16.26 -15.16 -12.48 -8.79 -22.28 -17.85 -9.41 -13.83

∆Evdw, van der Waals energy; ∆Eelectrostatic, electrostatic energy; ∆GPB, the polar solvation energy with the PB model; ∆Gbind is the sum of ∆Evdw + ∆Eelectrostatic + ∆GPB/GB + ∆GSA.

Clearly, it is observed that all eight compounds present low binding free energies (-28.27~ -8.79 kcal/mol), indicating high binding affinities to their targets. In addition, the van der Waals (∆Evdwz) energy is lower than the electrostatic energy (∆Eelectrostatic) (Table 5), suggesting that the twelve complexes are mainly driven by the energy of van der Waals. Moreover, binding energy components show that the non-polar energies also offer large favorable contribution to the binding of inhibitors, whereas the polar solvation energies are unfavorable for the compounds. Thus, the unfavorable electrostatic energy accompanied by the polar solvation contributions is not entirely compensated by the beneficial interactions within the obtained ligand-receptor complex. In addition, the trends of the calculated binding free energies are well consistent with the experimental binding data. It successfully ranks the compounds according to the binding free energies, which presents a high correlation with the bioactivities of the compounds.


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In summary, all the results obtained from the computational analysis may help determine the activity of anti-RA drugs and offer a better understanding of structural features of the drug targets. In addition, the relatively strong binding affinities of these five compounds may explain their good inhibitory activities. Furthermore, the MD and MM-PBSA analysis demonstrates the rational binding modes of the active compounds to their relevant target proteins. Therefore, these compounds may become potential leads of anti-RA drugs in the near future. All these results indicate that the potential therapeutic effect of the candidate compounds for treating RA may be through modulating the relevant proteins, further validating our constructed C-T network. 4 CONCLUSION With over 2,500 years of clinical practice, TCM, as a potentially alternative choice to conventional western-medicine, has attracted much attention in recent years. Presently, to explore the pharmacological mechanisms of anti-RA herbal medicines, an integrated systems pharmacology model was introduced, which combined the knowledge of biology, chemistry and a wide-scale text-mining technique as well as the theoretical background of TCM. Using the wide-scale text mining, we identified seven medicinal herbs like Radix Paeoniae Alba, Anemarrhenae Rhizom, Cinnamomi Ramulus, etc. showing close correlations with RA. After ADME screening, a total of 117 candidate compounds are obtained from these seven herbal medicines. All these compounds could interact with 85 various targets relevant with inflammation, angiogenesis and immune systems, demonstrating that the potential therapeutic effects of each drug for combating RA may be through modulating these relevant proteins and also showing the multi-component therapeutics and multi-target regulations characteristics of TCM. Moreover, the C-T-D network suggests that these herbs exert high efficiency not only for treating RA but also for curing other disorders such as hypertension, atheroscierosis, myocardial infarction, heart failure coronary disease and digestive system diseases, suggesting that multiple diseases may be treated with the common herbal medicine. Furthermore, analysis of the T-P network demonstrates that the seven herbal medicines may simultaneously target several relevant signal pathways, thereby exhibiting the synergistic benefits and efficiency for the treatment of RA. Additionally, the MD summations and MM-PBSA calculations clarify the mechanism of the interactions between the active compounds and their targets. In final, the experimental results demonstrate the reliability of the obtained C-T interactions, further validating our prescreening model. Overall, all these work may offer a novel and reliable strategy to study the molecular mechanisms of botanic drug action for the treatment of RA, and may facilitate the drug discovery and modernization of TCM. ASSOCIATED CONTENT Supporting Information (Table S1) C-T network on treating RA, (Table S2) C-T-D network, with the active compounds, target proteins and relevant diseases.



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ACKNOWLEDGEMENTS We are grateful for the Oasis Scholar Fund of Shihezi University. The Project is also supported by the Key Program of National Natural Science Foundation of China (Grant No. 81530100, 21576036). CONFLICT OF INTEREST The author(s) confirm that this article content has no conflicts of interest. REFERENCE (1) Koenders, M.I.; van den Berg, W. B. Novel therapeutic targets in rheumatoid arthritis. Trends. Pharmacol. Sci. 2015, 36, 189-195. (2) Brennan, F. M.; Mcinnes, I. B. Evidence that cytokines play a role in rheumatoid arthritis. J. Clin. Invest. 2008, 118, 3537-3545. (3) Chen, Y. F.; Jobanputra, P.; Barton, P.; Jowett, S.; Bryan, S.; Clark, W.; Fry-Smith, A.; Burls, A. A systematic review of the effectiveness of adalimumab, etanercept and infliximab for the treatment of rheumatoid arthritis in adults and an economic evaluation of their cost-effectiveness. Health. Technol. Asses. 2006, 10, 1-229. (4) Liu, J.; Liu, R. The Potential Role of Chinese Medicine in Ameliorating Extra-articular Manifestations of Rheumatoid Arthritis. Chin. J. Integr. Med. 2011, 17, 735-737. (5) Zhao, F.; Guo, L.; Yang, Y.; Shi, L., Xu, L.; Yin, L. A network pharmacology approach to determine active ingredients and rationality of herb combinations of Modified-Simiaowan for treatment of gout. J. Ethnopharmacol. 2015, 168, 1-16. (6) Goldbach-Mansky, R.; Wilson, M.; Fleischmann, R.; Olsen, N.; Silverfield, J.; Kempf, P.; Kivitz, A.; Sherrer, Y.; Pucino, F.; Csako, G. Comparison of tripterygium wilfordii Hook F versus sulfasalazine in the treatment of rheumatoid arthritisA randomized trial. Ann. Intern. Med. 2009, 151, 229-240. (7) Zhang, R. X.; Fan, A. Y.; Zhou, A. N.; Moudgil, K. D.; Ma, Z. Z.; Lee, D. Y. W.; Fong, H. H.; Berman, B. M.; Lao, L. Extract of the Chinese herbal formula Huo Luo Xiao LingDan inhibited adjuvant arthritis in rats. J. Ethnopharmacol. 2009, 121, 366-371. (8) Tao, X.; Younger, J.; Fan, F. Z.; Wang, B.; Lipsky, P. E. Benefit of an extract of Tripterygium Wilfordii Hook F in patients with rheumatoid arthritis: A double-blind, placebo-controlled study. Arthritis Rheumatol. 2002, 46, 1735-1743. (9) Yu, H.; Lee, D. Y. W.; Nanjundaiah, S. M.; Venkatesha, S. H.; Berman, B. M.; Moudgil, K. D. Microarray analysis reveals the molecular basis of antiarthritic activity of huo-luo-xiao-ling dan. Evid-Based Compl. Alt. 2013, 2013. (10) Lv, Q. W.; Zhang, W.; Shi, Q.; Zheng, W. J.; Li, X.; Chen, H.; Wu, Q. J.; Jiang, W. L.; Li, H. B; Gong, L. Comparison of Tripterygium wilfordii Hook F with methotrexate in the treatment of active rheumatoid arthritis (TRIFRA): a randomised, controlled clinical trial. Ann. Rheum. Dis. 2014, 0, 1-9. (11) Moudgil, K. D.; Berman, B. M. Traditional Chinese medicine: potential for clinical treatment of rheumatoid arthritis. Expert Rev. Clin. Immunol. 2014, 10, 819. (12) Lao, L.; Fan, A. Y.; Zhang, R. X.; Zhou, A.; Ma, Z. Z.; Lee, D. Y.; Ren, K.; Berman, B. Anti-hyperalgesic and anti-inflammatory effects of the modified Chinese herbal formula Huo Luo Xiao Ling Dan (HLXL) in rats. Am. J. Chinese Med. 2006, 34, 833.


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Steiniger, F.; Thamm, J.; Fahr, A. Lecithin-based novel cationic nanocarriers (Leciplex) II: improving therapeutic efficacy of quercetin on oral administration. Mol. Pharm. 2011, 8, 716-726.



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Systems Pharmacology Dissection of Multiscale ... - ACS Publications

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