Discovery of potential asthma targets based on the clinical efficacy of Traditional Chinese Medicine formulas

Journal Pre-proof Discovery of potential asthma targets based on the clinical efficacy of Traditional Chinese Medicine formulas Yu Wang, Yan-Jiao Chen, Cheng Xiang, Guang-Wei Jiang, Yu-Dong Xu, Lei-Miao Yin, Dong-Dong Zhou, Yan-Yan Liu, Yong-Qing Yang PII:

S0378-8741(19)31053-0

DOI:

https://doi.org/10.1016/j.jep.2020.112635

Reference:

JEP 112635

To appear in:

Journal of Ethnopharmacology

Received Date: 19 March 2019 Revised Date:

23 January 2020

Accepted Date: 24 January 2020

Please cite this article as: Wang, Y., Chen, Y.-J., Xiang, C., Jiang, G.-W., Xu, Y.-D., Yin, L.-M., Zhou, D.-D., Liu, Y.-Y., Yang, Y.-Q., Discovery of potential asthma targets based on the clinical efficacy of Traditional Chinese Medicine formulas, Journal of Ethnopharmacology (2020), doi: https:// doi.org/10.1016/j.jep.2020.112635. This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. © 2020 Published by Elsevier B.V.

Discovery of Potential Asthma Targets Based on the Clinical Efficacy of Traditional Chinese Medicine Formulas

Yu Wang1,2, Yan-Jiao Chen1, Cheng Xiang1, Guang-Wei Jiang1, Yu-Dong Xu1, Lei-Miao Yin1, Dong-Dong Zhou1, Yan-Yan Liu1, Yong-Qing Yang1*

Institutional Affiliations: 1. International Union Laboratory on Acupuncture Based Target Discovery, International Joint Laboratory on Acupuncture Neuro-immunology, Shanghai Research Institute of Acupuncture and Meridian, Yue Yang Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai 201203, China 2. Experiment Center for Science and Technology, Shanghai University of Traditional Chinese Medicine, Shanghai 201203, China

Address Correspondence to: Yong-Qing Yang, MD, PhD, Prof. 1200 Cai Lun Road, Zhangjiang High-Tech Park, Shanghai 201203, China Shanghai University of Traditional Chinese Medicine Tel: 86-21-51322045(O), 86-21-54592134(Lab) Fax: 86-21-51322045(O), 86-21-64395975(Lab) Email: [email protected]

1

ABSTRACT Ethnopharmacological relevance Standard therapy for asthma, a highly heterogeneous disease, is primarily based on bronchodilators and immunosuppressive drugs, which confer short-term symptomatic relief but not a cure. It is difficult to discover novel bronchodilators, although potential new targets are emerging. Traditional Chinese Medicine (TCM) formulas have been used to treat asthma for more than 2,000 years, forming the basis for representative asthma treatments. Aim of the study Based on the efficacy of TCM formulas, anti-asthmatic herbal compounds bind proteins are potential targets for asthma therapy. This analysis will provide new drug targets and discovery strategies for asthma therapy. Materials and methods A list of candidate herbs for asthma was selected from the classical formulas (CFs) of TCM for the treatment of wheezing or dyspnea recorded in Treatise on Cold Damage and Miscellaneous Diseases (TCDMD) and from modern herbal formulas identified in the SAPHRON TCM Database using the keywords “wheezing” or “dyspnea”. Compounds in the selected herbs and compounds that directly bind target proteins were acquired by searching the Herbal Ingredients' Targets Database (HITD), TCM Data Bank (TCMDB) and TCM Integrated Database (TCMID). Therapeutic targets of conventional medicine (CM) for asthma were collected by searching Therapeutic Target Database (TTD), DrugBank and PubMed as supplements. Finally, the enriched gene ontology (GO) terms of the targets were obtained using the Database for Annotation Visualization and Integrated Discovery (DAVID) and protein-protein interactions (PPI) networks 2

were constructed using Search Tool for the Retrieval of Interacting Genes/Proteins (STRING). The effects of two selected TCM compounds, kaempferol and ginkgolide A, on cellular resistance in human airway smooth muscle cells (ASMCs) and pulmonary resistance in a mouse model were investigated. Results The list of 32 candidate herbs for asthma was selected from 10 CFs for the treatment of wheezing or dyspnea recorded in TCDMD and 1037 modern herbal formulas obtained from the SAPHRON TCM Database. A total of 130 compounds from the 32 selected herbs and 68 herbal compounds directly bind target proteins were acquired from HITD and TCMDB. Eighty-eight therapeutic targets of CM for asthma were collected by searching TTD and PubMed as supplements. DAVID and STRING analyses showed targets of TCM formulas are primarily related to cytochrome P450 (CYP) family, transient receptor potential (TRP) channels, matrix metalloproteinases (MMPs) and ribosomal protein. Both TCM formulas and CM act on the same types of targets or signaling pathways, such as G protein-coupled receptors (GPCRs), steroid hormone receptors (SHRs), and JAK-STAT signaling pathway. The proteins directly targeted by herbal compounds, TRPM8, TRPA1, TRPV3, CYP1B1, CYP2B6, CYP1A2, CYP3A4, CYP1A1, PPARA, PPARD, NR1I2, MMP1, MMP2, ESR1, ESR2, RPLP0, RPLP1 and RPLP2, are potential targets for asthma therapy. In vitro results showed kaempferol (1×10-2 mM) and ginkgolide A (1×10-5 mM) significantly increased the cell index (P<0.05 vs. histamine, n=3) and therefore relaxed human ASMCs. In vivo results showed kaempferol (145 µg/kg) and ginkgolide A (205 µg/kg) significantly reduced pulmonary resistance (P<0.05 vs. methacholine, n=6). Conclusion 3

Potential target discovery for asthma treatment based on the clinical effectiveness of TCM is a feasible strategy.

Abbreviations ASM, airway smooth muscle; CFs, classical formulas; CHCs, Chinese herb compounds; CHFs, Chinese herbal formulas; CHMs, Chinese herbal medicines; CM, conventional medicine; CMM, Chinese materia medica; CMHs, Chinese medicine herbs; EOS, eosinophils; GA, ginkgolide A; GABA, gamma-aminobutyric acid; GCSs, glucocorticosteroids; GINA, the Global Initiative for Asthma; Glu, glutamic acid; Hist, histamine; ICAAI, the International Collaboration in Asthma, Allergy and Immunology; ICSs, inhaled corticosteroids; IgE, immunoglobulin E; KP, kaempferol; LABAs, ultralong-acting beta-agonists; Mch, methacholine; MMPs, matrix metalloproteinases; NRs, nuclear receptors; PBS, phosphate buffer saline; PPARs, peroxisome proliferator-activated receptors; ROS, reactive oxygen species; RPs, ribosomal proteins; SHRs, steroid hormone receptors; TCDMD, Treatise on Cold Damage and Miscellaneous Diseases; TCM, Traditional Chinese Medicine.

Key words: asthma; targets; herbs; signaling pathway; bioinformatics analysis

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1. Introduction Asthma is a highly prevalent, chronic respiratory disease affecting as many as 358 million people of all ages worldwide (GBD 2015 Chronic Respiratory Disease Collaborators, 2017). Accordingly, asthma is a major global health challenge and a considerable economic burden. Strengthening the clinical and basic asthma research is still a common goal worldwide. Asthma is a highly heterogeneous disease at both the clinical and mechanistic levels (Carr and Bleecker, 2016). The immunological and inflammatory stages remain the targets for disease control (Nagai, 2012). The current treatment of asthma is mostly based on relieving symptoms or inhibiting the release or activity of pathogenic mediators using potent bronchodilators. The three major classes of bronchodilators are beta2-adrenoceptor agonists, muscarinic receptor antagonists and xanthine (Global Initiative for Asthma, 2019). Novel classes of bronchodilators, such as selective phosphodiesterase inhibitors, K+ channel openers, vasoactive intestinal peptide analogues, Rho kinase inhibitors, brain natriuretic peptide and analogs, nitric oxide donors, E-prostanoid receptor 4 agonists and bitter taste receptor agonists (Cazzola et al., 2012), are constantly being identified. The gold standard of therapeutic intervention is still glucocorticosteroids (GCSs), with the addition of ultralong-acting beta-agonists (LABAs), although they are not effective in all patients. Approximately 10% of asthma patients have severe asthma (Pawankar et al., 2013) and do not respond to these treatments, even at high doses or in combination with oral corticosteroids, which may have numerous side effects (Barnes, 2011; Canonica et al., 2016). Additionally, relapse after drug withdrawal is common (Sheth et al., 2006). In recent years, many drug targets have been discovered and new drug research has been conducted on a variety of effector immune cells and immune factors. Therapeutic anti-IgE 5

antibodies, such as omalizumab, are now widely used in the therapy of asthma as an effective and well-tolerated treatment for using as add-on therapy in patients with severe persistent allergic asthma (Normansell et al., 2014). Omalizumab treatment reduces the need for systemic GCSs as rescue therapy but not as maintenance therapy (Humbert et al., 2014). Monoclonal antibodies are not effective in treating all patients with asthma because of concerns about long-term efficacy (Papadopoulos et al., 2009), safety (Food and Drug Administration, 2014) and cost effectiveness (Lai et al., 2015). Despite accelerated research and major advances in the treatment of asthma, standard therapy is primarily based on immunosuppressive agents and bronchodilators, which confer short-term symptom relief but not a cure. It has proven difficult to discover novel classes of bronchodilators, although potential new targets are emerging based on current strategy (Cazzola et al., 2012). Curative treatment for asthma poses a challenge. There is a clear need for new treatment strategies and new drugs for asthma that overcome the shortcomings of currently available therapeutics (Olin and Wechsler, 2014). The classic target identification and validation process begin with molecule identification, proceed with validation in an animal model, and conclude with clinical validation. Clinical efficacy, safety and disease heterogeneity and variability are important considerations in the development of new drugs (Gough et al., 2014; Hittinger et al., 2015; Mitka, 2012). Therefore, there has been an international effort to conduct research on new drug target discovery strategies, new drug targets and new drugs for asthma (Nagai, 2012). Drug target discovery based on clinical effects is a new strategy. The curative effect of Traditional Chinese Medicine (TCM) has been observed for more than 2,500 years (Cheung, 2011b), forming an independent system of theory, diagnosis and treatment. 6

The understanding of the human body and the concept of disease are fundamentally different in TCM and conventional medicine (CM). TCM plays an important role in health maintenance for people in Asia and is increasingly used in countries worldwide (Cheung, 2011a). TCM encompasses a wide range of practices, including TCM formulas and acupuncture. In recent decades, a large number of studies have analyzed chemical compounds in Chinese herbal medicines (CHMs) and their functional target proteins (Hu et al., 2016; Huang et al., 2015; Li, 2016). Several representative Chinese herb compounds (CHCs), including ephedrine (Waldeck, 2002), arsenic trioxide (Chen et al., 1997), artemisinin (Guo, 2016), and berberine (Pang et al., 2015), have already contributed to CM (Wang et al., 2018). These results provide a reference direction for the CM-based treatment of asthma: the curative effect of TCM. Therefore, a new strategy based on the analysis of effective CHMs and their targets may be useful for finding potential drug targets for asthma. Asthma is called “xiao chuan” in TCM: “xiao” is wheezing, and “chuan” is dyspnea, and these terms grouped together mean asthma. A systematic theoretical series of Chinese herbal formulas (CHFs) has been formed for asthma since the Eastern Han Dynasty. Treatise on Cold Damage

and

Miscellaneous

Diseases

(TCDMD),

compiled

by

Zhang

Zhongjing

(A.D.150-A.D.219) in the Eastern Han Dynasty, is the earliest monograph on the diagnosis and treatment of miscellaneous diseases in Chinese history, as well as one of the classics of TCM. In TCDMD, there are 328 CHFs specifically defined as classical formulas (CFs) in the field of TCM. Throughout the past 2,000 years, 10 CFs for asthma have been used in TCM practice (Scheid et al., 2009). Ephedrine was the first oral beta 2-adrenoceptor agonist (Waldeck, 2002). The efficacy of CHFs on asthma has been recognized (Liu et al., 2018; Shergis et al., 2016). In the past decade, 7

researchers began to investigate the potential use of these formulas, and the potential for the development of herbal interventions for asthma has been suggested (Li, 2011). Based on the clinical effectiveness of TCM formulas for asthma, the proteins directly targeted by anti-asthmatic CHCs are the potential targets of interest in asthma research. By analyzing the protein-protein interaction (PPI) network and predicting biological processes and molecular functions, proteins directly bound by chemical composition of anti-asthmatic herbs are the potential target proteins for asthma, thus providing new drug targets and discovery strategies for the treatment of asthma.

8

2. Materials and methods The flow diagram of the search process is shown in Fig. 1.

Fig. 1. Flow diagram of the search for potential asthma targets. A total of 32 candidate Chinese medicine herbs for asthma were selected from the 10 CFs for the treatment of wheezing or dyspnea recorded in Treatise on Cold Damage and Miscellaneous Diseases and form1037 modern herbal formulas for wheezing or dyspnea in SAPHRON TCM Database. A total of 130 herbal compounds in the 32 selected herbs and 68 herbal compounds that directly bind target proteins were acquired by searching Herbal Ingredients' Targets Database and Traditional Chinese Medicine Data Bank. Eighty-eight therapeutic targets of CM for asthma were collected by searching Therapeutic Target Database and PubMed as supplements; 79 of these CM targets matched UniProt IDs. Then, bioinformatics analysis and functional annotation were executed by

9

DAVID and STRING to identify potential targets for asthma based on the clinical efficacy of TCM.

2.1 Selection of TCM formulas and herbs for asthma The TCM formulas for asthma were divided into two parts. First, the CFs that treat asthma according to the classical work TCDMD were selected. Second, modern herbal formulas for asthma were obtained from SAPHRON TCM Database served by Shanghai Innovative Research Center of Traditional Chinese Medicine (http://www.sirc-tcm.sh.cn) which contains 190,000 modern herbal formulas from academic journals published in Chinese since 1950. Using the Chinese character “wheezing (xiao)” or “dyspnea (chuan)” as the keyword, we searched the SAPHRON TCM Database and collected the modern herbal formulas (1 modern herbal formulas was recorded in each item) with target syndromes and diseases containing the keyword “wheezing” or “dyspnea”. The list of candidate herbs for asthma had three inclusion criteria: (1) herbs used in the 10 CFs for asthma; (2) frequency of use greater than 20% in the collected modern herbal formulas for asthma; and (3) herbs with anti-asthmatic effectiveness according to the book Compendium Of Materia Medica (Ben Cao Gang Mu) (Li Shizhen, A.D.1518-A.D.1593). Three special herbs, Glycyrrhiza uralensis Fisch. ex DC.(Root and rhizome), Zingiber officinale Roscoe (Root and rhizome) and Ziziphus jujuba Mill. var. inermis (Bunge) Rehd. (Fruit), were excluded despite a high rate of utilization, because they are used as adjuvants and messengers in CHFs.

2.2 Collection of CHCs of herbs for asthma CHCs in the 32 selected herbs for asthma were acquired by searching Herbal Ingredients' Targets Database (HITD, http://lifecenter.sgst.cn/hit/) (Ye et al., 2011). As a supplement, if the 10

herbs were not included in HITD, TCM-Mesh (http://mesh.tcm.microbioinformatics.org/) (Zhang et

al.,

2017)

and

Traditional

Chinese

Medicine

Integrated

Database

(TCMID,

http://www.megabionet.org/tcmid/) (Huang et al., 2018) were searched. All of the compounds in the selected herbs were identified by searching the name of the herbs in these databases.

2.3 Collection of candidate therapeutic targets of CHCs for asthma Candidate target proteins of the CHCs were acquired by searching HITD, TCMID, PubChem (https://pubchem.ncbi.nlm.nih.gov/)

(Kim

et

al.,

2016)

and

ChEMBL

(https://www.ebi.ac.uk/chembl/) (Mendez et al., 2019) using the name of each CHC.

2.4 Collection of therapeutic targets of CM for asthma Using “asthma” as the keyword, we searched TTD (http://bidd.nus.edu.sg/group/cjttd/) to collect the targets of CM for asthma, including successful targets, clinical trial targets and research targets.

To

supplement

the

research

targets

in

TTD,

we

searched

PubMed

(http://www.ncbi.nlm.nih.gov/pubmed) using asthma [Title] AND target [Title] as the keyword with no data restrictions and collected research targets of CM for asthma. In addition, the protein targets of anti-asthmatic drugs were searched in DrugBank (https://www.drugbank.ca/) (Wishart et al., 2018).

2.5 Biological processes and molecular functions Biological processes and molecular functions were predicted by Database for Annotation, Visualization, and Integrated Discovery (DAVID) 6.8 (http://david.abcc.ncifcrf.gov/) (Huang da et al., 2009). Classification stringency was as follows: Kappa, similarity term overlap=4; similarity threshold=0.40; classification, initial group membership=3; and multiple linkage threshold=0.50.

2.6 Predicted PPI network 11

The PPI network was constructed with the online analysis tool STRING 10.5 (http://www.string-db.org/) (Szklarczyk et al., 2017). A confidence level of 0.9 was used as analysis parameter.

2.7 The effects of TCM compounds on the cellular resistance of human airway smooth muscle cells TCM compounds including kaempferol and ginkgolide A were selected. The effects of kaempferol (1×10-2 mM) and ginkgolide A (1×10-5 mM) on the cellular resistance of human airway smooth muscle cells to histamine (8.5 mM) were examined by real-time cell analysis (RTCA, Roche) according to a previous description (Yin et al., 2018).

2.8 The effects of TCM compounds on the pulmonary resistance in mouse model The TCM compounds including kaempferol (145 µg/kg) and ginkgolide A (205 µg/kg) were also investigated in vivo. The measurement of pulmonary resistance by the FinePoint RC system (Buxco) was modified according to a previously described protocol (Yin et al., 2018).

2.9 Statistical analysis Data are presented as the mean ± SEM. Data were analyzed using one-way ANOVA followed by the least significant difference (LSD) post hoc test or the Games-Howell test, depending on the data and on the hypothesis tested. A P-value <0.05 was considered statistically significant.

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3. Results 3.1 CFs and herbs for asthma There are 10 CFs for the treatment of dyspnea (xiao) recorded in TCDMD. According to TCM, the herbs that evoke the principal curative action on the main pattern/syndrome or primary symptom are called the sovereign herbs. The following is a list of the 18 sovereign herbs used in the 10 CFs as follows: Aconitum carmichaeli Debx.(Seminal root), Asarum heterotropoides F.Schmidt (Rhizome), Belamcanda chinensis (L.) Redouté (Rhizome), Cinnamomum cassia (L.) J.Presl(Branch), Descurainia sophia (L.) Webb ex Prantl (Seed), Ephedra sinica Stapf (Herbaceous stalk), Glycyrrhiza uralensis Fisch.(Root and rhizome), Gypsum fibrosum, Paeonia lactiflora Pall. (Root), Pinellia ternata Ten. ex Breitenb.(Rhizome), Poria cocos (Schw.) Wolf (Sclerotium), Prunus armeniaca L.(Seed), Zingiber officinale Roscoe (Root and rhizome), Ziziphus jujuba Mill. var. inermis (Bunge) Rehd. (Fruit) (Wang et al., 2020).

3.2 Modern herbal formulas and herbs for asthma Using the Chinese character for “wheezing” or “dyspnea” as the keyword, we searched SAPHRON TCM Database and collected modern herbal formulas (1 modern herbal formula was recorded for each item) with targeted syndromes and diseases containing the keyword “wheezing” or “dyspnea”. A total of 1037 modern herbal formulas with targeted syndromes and diseases containing the keyword “wheezing” or “dyspnea” were collected from SAPHRON TCM Database. A total of 129 herbs were ranked from high to low according to the frequency of used in 1037 modern herbal formulas. The list of 32 candidate herbs for asthma was generated based on the following criteria: (1) 15 herbs used in the 10 CFs for asthma; (2) 25 herbs with usage frequency 13

in the top 20% of 129 herbs, ranked from high to low in frequency according to the usage frequency in 1037 modern herbal formulas; and (3) 7 herbs with anti-asthmatic efficacy according to the Compendium Of Materia Medica (Ben Cao Gang Mu) (Table 1). 3.3 CHCs and candidate therapeutic target proteins of herbs for asthma In total 130 CHCs of 32 herbs for asthma were acquired by searching HITD and TCMD (Wang et al., 2020). All 130 compounds were mainly classified as aliphatic natural products (16%, 21/130), terpenoids (12%, 15/130), flavonoids (11%, 14/130), simple aromatic natural products (9%, 12/130), alkaloids (5%, 6/130), carbohydrates (3%, 4/130), benzopyranoids (2%, 2/130), lignans (2%, 2/130), steroids(2%, 2/130), amino acids and peptides (1%, 1/130), polycyclic aromatic natural products (1%, 1/130) and tannins (1%, 1/130). The 443 candidate protein targets of the 130 active compounds were acquired by searching the HITD; among these candidates, 68 protein targets were described as direct targets in HITD (Table 2). 3.4 Targets of CM for asthma A total of 67 targets of CM for asthma (including 27 successful targets, 21 clinical trial targets and 19 research targets) from TTD and 21 research targets from PubMed were obtained. Then, 88 anti-asthmatic target proteins, including 79 with gene ID were obtained (Wang et al., 2020). Four targets, PARP1, PPARG, ALOX5 and TNF, were in the lists of both candidate therapeutic targets of CHCs and therapeutic targets of CM. Finally, 143 targets were obtained. 3.5 Pathway and network analysis of targets for asthma To identify the molecular networks and pathways of candidate therapeutic targets of CHCs and to identify similarities and differences between targets of CHCs and CM, we utilized DAVID 14

and STRING 10.5 for GO analysis and de novo pathway generation, respectively. 3.6 Functional classification of target proteins Biological processes and molecular functions were predicted by DAVID. A total of 143 target protein genes were uploaded, and 135 matched Homo sapiens gene. The functional classification of the targets is detailed in Table 3; these targets belonged to 9 functional categories and the terms are described below. Among 68 candidate therapeutic targets of CHCs for asthma, 2 targets were associated with G protein-coupled receptors (GPCRs), 2 with positive regulation of B cell proliferation and the Janus kinase (JAK)-signal transducer and activator of transcription (STAT) signaling pathway; 3 with transient receptor potential (TRP) channels; 5 with oxidoreductases or cytochrome P450 (CYP) enzymes, 2 with the peroxisome proliferator-activated receptor (PPAR) signaling pathway, 3 with cysteine switches; 3 with steroid hormone receptors (SHRs) and the PPAR signaling pathway, and 3 with ribosomal proteins (RPs). Among the targets of CM for asthma, 18 are associated with GPCRs; 2 with positive regulation of B cell proliferation and the JAK-STAT signaling pathway, 3 with metalloprotease, 1 with oxidoreductase and CYP enzymes,1with cysteine switches and 1 with SHRs. In particular, CHCs targets were closely related to TRP channels, the PPAR signaling pathway and PRs; Targets of CM were closely related to metalloproteases. Targets of CHCs and CM were closely related to GPCRs, positive regulation of B cell proliferation, the JAK-STAT signaling pathway, CYP enzymes, matrix metalloproteinases (MMPs) and SHRs. 3.7 Predicted of PPI network of the targets for asthma The PPI network of CHCs targets was obtained by uploading the 68 gene IDs of the 68 15

targets into the online analysis tool STRING. The most enriched networks were as follows: oxidoreductases, the JAK-STAT signaling pathway, cysteine switches, SHRs, and the PPAR signaling pathway. JUN, RELA, PPARA, PPARG, CYP3A4 and CYP2B6 were the hub proteins (Fig. 2).

Fig. 2. The PPI networks enriched for genes encoding targets of CHCs for asthma. PPI networks enriched for genes encoding targets of CHCs for asthma were analyzed using STRING to identify interaction networks implicated in impaired differentiation. The most enriched networks are shown: oxidoreductase, the JAK-STAT signaling pathway, cysteine switches, steroid hormone receptor and the PPAR signaling pathway. JUN, RELA, PPARA, PPARG, CYP3A4 and CYP2B6 are the hubs. Network nodes represent proteins. Edges represent protein-protein associations. Line color indicates the type of interaction evidence. 16

3.8 The effects of TCM compounds in vitro and in vivo In vitro results showed that TCM compounds (1×10-2 mM kaempferol or 1×10-5 mM ginkgolide A) significantly alleviated the histamine-induced contraction of human ASMCs, respectively (P<0.05 vs. histamine, Fig. 3A). Consistently, In vivo results showed that kaempferol (145 µg/kg) or ginkgolide A (205 µg/kg) significantly reduced the pulmonary resistance in mouse model (P<0.05 vs. methacholine, Fig. 3B).

Fig. 3. In vitro and in vivo effects of TCM compounds. (A) The effect of TCM compounds on the cellular resistance of human airway smooth muscle cells induced by histamine. Terbutaline sulfate (2×10-2 mM) was used as positive control. # P< 0.05 vs. PBS, *P< 0.05 vs. model group; n=3; (B) The effect of TCM compounds on pulmonary resistance in a mouse airway contractions model induced by methacholine. Terbutaline sulfate (125 µg/kg) was used as positive control. * P< 0.05 vs. model group; n=6. Abbreviation: PBS: phosphate buffer saline, Mch: methacholine, Hist: histamine, KP: kaempferol, GA: ginkgolide A, TB: terbutaline sulfate, RI: pulmonary resistance.

17

4. Discussion Target identification and validation are the first key stages of the drug development (Stitziel and Kathiresan, 2017; Wang et al., 2004). The three basic strategies, which remain dominant for classical drug target identification, are the physiological, mechanism-driven and gene-driven approaches (Knowles and Gromo, 2003; Lindsay, 2005). In this postgenomic era, novel drug target discovery strategies for targeted or personalized treatment, such as chemogenomics (Bredel and Jacoby, 2004), biocomputational (Sakharkar et al., 2008), whole-organism screening (Muller and Hemphill, 2016), targeting autophagy (Gao et al., 2017), modular probe (Rutkowska et al., 2016), reverse chemical genetics (Wong et al., 2016) and chemical strategies (Winter et al., 2015) have been developed through research on asthma that is refractory to conventional treatment. Various tools and technologies such as systems biology (Haanstra and Bakker, 2015), quantitative chemical proteomics (Wang et al., 2017), gene expression signatures (Sithara et al., 2017), structural modification of natural products (Yao et al., 2017) and biofocussed chemoprospecting (Thakkar et al., 2017) have been used in different approaches to accelerate target identification and validation. Strategies targeting a single cell type or mediator may not be optimal for the treatment of asthma because of the redundant and overlapping responses of inflammatory cells. A more plausible approach may be to target a common upstream event that controls the pathogenic responses of multiple inflammatory components. The one-size-fits-all principle on which asthma therapy was initially based has been radically changing for several years and has been found to not hold true. It is important to continue searching for new asthma therapeutics (Mullane, 2011). There is a demand for better drugs with improved compliance that can modify the nature of 18

the disease rather than just offer symptomatic relief (Shahid, 2013). The holistic and synergetic nature of TCM formulas improves their performance as a systems-level intervention for a complex disease. TCM formulas have been used to treat infective diseases for thousands of years. The numerous clinical TCM practices in disease therapy provide a large chemical resource for drug discovery. TCM formulas and CM have the same therapeutic targets in asthma, but the unique therapeutic targets of TCM formulas provide new strategies for the treatment of asthma. As a highly heterogeneous disease (Teague et al., 2014), asthma is usually characterized by chronic airway allergic inflammation (Global Initiative for Asthma, 2019), bronchial hyperresponsiveness and airway smooth muscle (ASM) contraction (Trevor and Deshane, 2014). Immunological

and

inflammatory

processes,

airway

remodeling

and

bronchial

hyperresponsiveness are the underlying causes of asthma attacks and are predominately related to tissue reactions. The immune-Mediated inflammatory stages and the ASM contraction are still the target steps for the controller (Nagai, 2012). Our DAVID and STRING analyses revealed that the targets of CM are closely related to GPCRs, the inflammatory response, the adenosine receptor and the JAK-STAT signaling pathway. The targets of CHCs are closely related to TRP channels, CYP enzymes, RPs and the PPAR signaling pathway. Although both CHCs and CM act on the same types of targets or signaling pathways, such as GPCRs, SHRs and the JAK-STAT signaling pathway, the unique therapeutic target of TCM provides new therapeutic strategies for the treatment of asthma. 4.1 GPCRs There are numerous types of GPCRs, the most intensively studied drug targets (Hauser et al., 2017), including the β2-adrenergic receptor, prostaglandin E2 receptor, chemokine receptor, 19

adenosine receptor, etc. (Shu et al., 2016) GPCRs on human airway smooth muscle cells (ASMCs) have been a major target of asthma therapy for decades and GPCR ligands still constitute frontline asthma treatment today (Wright et al., 2013). Overcoming ASMC contraction is a prominent therapeutic strategy (Dowell et al., 2014). In addition to finding new GPCR targets, the current challenge is to advance the study of GPCR regulation and signaling in human ASMCs to create new ligands, modify existing ligands or target modulators of GPCR function. BDKRB2, ADRB1, CYSLTR1, EDNRB, EDNRA, HRH1 and TACR1 are successful targets; GPR35 and HRH4 are research targets. CCR3, CCR4, CXCR1, CXCR2, LTB4R, GPR44 and TACR2 are clinical trial targets. The CHC targets GABBR1 (Martin et al., 1999) and OR1D2 (Selbie et al., 1992) are also GPCRs. The GABBR1 (or GPRC3A) gene encodes the gamma- aminobutyric acid (GABA) B receptor 1 (Zai et al., 2005). GABBR1 is associated with the hypothalamic-pituitary-adrenal (HPA) axis response to a stressor (Vangeel et al., 2017). Both GABA receptor signaling and glutamate have been implicated in proliferation, migration and differentiation (Lujan et al., 2005). Through GABAB1, GABA is thought to fine-tune inhibitory synaptic transmission including the effect of glutamic acid (Glu), the main excitatory neurotransmitter in asthma as a neuroelectrical disorder (Hoang et al., 2010). In addition, GABBR1 overexpression significantly restored the function of miRNAs that regulate proliferation and invasion (Longqiu et al., 2016). Therefore, activating GABBR1 may inhibit Glu-induced asthma. Olfactory receptors (ORs) represent the largest superfamily of GPCR genes. OR1D2 is functionally expressed in human ASMCs at the RNA and protein levels, and it was shown to trigger transient Ca2+ increases in human ASMCs via a cAMP-dependent signal transduction 20

cascade. Furthermore, the activation of OR2AG1 can inhibit the histamine-induced contraction of human ASMCs and induce the secretion of IL-8 and granulocyte-macrophage colony stimulating factor (GM-CSF) (Kalbe et al., 2016). ORs might be new therapeutic targets for asthma, and blocking ORs may be a promising strategy for the treatment of early-stage chronic inflammatory lung diseases. 4.2 Cytochrome P450 (CYP) family Our research revealed that the CYP family members targeted by CHCs (CYP1A2, CYP1A1, CYP1B1, CYP3A4 and CYP2B6) were different from those targeted by CM. CYP enzymes are membrane-bound hemoproteins that play a pivotal role in xenobiotic detoxifications (Estabrook, 2003), cellular metabolism and homeostasis. Drug metabolism is catalyzed by the CYP system (Guengerich, 2008), as is the metabolism of diverse endogenous compounds such as steroids, bile acids, unsaturated fats, prostaglandins, and leukotrienes (Manikandan and Nagini, 2018). There is strong evidence that an imbalance between the reducing and oxidizing systems favoring a more oxidative state occurs in asthma (Lan et al., 2014). Oxidative stress is involved in the pathogenesis of asthma (Sahiner et al., 2011). The oxidant-antioxidant imbalance plays an important role in the repeated cycles of airway inflammation observed in asthma (Nadeem et al., 2014). Inflammatory cells (such as eosinophils (EOSs), neutrophils, and lymphocytes from the lung/blood) and pulmonary resident cells (such as bronchial epithelial/smooth muscle cells) can generate reactive oxygen species (ROS) (Sutcliffe et al., 2012). Large amounts of ROS and reactive nitrogen species (RNS) can be produced directly or indirectly through various pathological and physiological cellular signaling pathways involved in asthma. When the body lacks the necessary endogenous antioxidant capacity, signal transduction systems become disordered, and the redox imbalance 21

activates stress-sensitive signal transduction pathways such as inflammation, the JAK-STAT, NF-KB and PI3K pathway, leading to the development and progression of asthma. Antioxidant treatments may be useful to combat oxidative stress in asthma, but there is not strong clinical support for this notion (Wood et al., 2012). The failure of antioxidant trials may relate to the inadequacy of current antioxidants to reduce oxidative stress. Therefore, more effective antioxidant drugs and interventions are needed (Lutter et al., 2015). Therefore, CYP family members (CYP1A2, CYP1A1, CYP1B1, CYP3A4 and CYP2B6) may be new targets and CYP agonists may be candidate antioxidants for asthma. 4.3 JAK-STAT pathway DAVID analysis results showed that the IL-2, IL-4, IL-5 and IL-13 cytokines are related to the inflammatory response and JAK-STAR signaling pathway. IL-2 and IL-4 are CHCs targets and IL-6 is a CM target. These cytokines can positively regulate the JAK-STAT pathway (Jung et al., 2015; Kurgonaite et al., 2015), which is an evolutionarily conserved signaling pathway mediating the response to extracellular soluble factors such as cytokines, growth factors and hormones (Jobst et al., 2016). The JAK-STAT pathway is the principal signaling pathway affected by a wide array of cytokines and growth factors (Stark and Darnell Jr, 2012). Following the binding of cytokines to their cognate receptor, STATs are activated by members of the JAK family of tyrosine kinases. Once activated, STARs dimerize and translocate to the nucleus, where they modulate the expression of target genes (Kisseleva et al., 2002), including genes that control essential cellular processes, such as differentiation, proliferation, survival and the immune response. Cytokine receptor dimerization upon ligand stimulation induces JAK activation, leading to the recruitment and phosphorylation of STAT and selective gene expression regulation. JAK-STAT signaling is 22

complex and involves multiple transmembrane receptors, activating kinases (JAK1-3, TYK2) and STAT family members (STAT1-6) that function in specific combinations (O'Shea et al., 2015). The mammalian JAK family has four members, JAK1, JAK2, JAK3 and tyrosine kinase 2 (TYK2) (Yamaoka et al., 2004), that play pivotal roles in the pathophysiology of many diseases including neoplastic and autoimmune diseases (Laurence et al., 2012). Classic immune (type I/II) cytokine receptors do not have intrinsic protein kinase activity but do associate with JAKs. JAK1 gene polymorphisms are associated with asthma susceptibility (Hsieh et al., 2011), and JAK3 plays a role in the pathogenesis of asthma (Malaviya et al., 2010). Targeting PI3K or JAK may prove effective in reducing T-cell activation and subsequent cytokine production in asthma (Southworth et al., 2016). TYK signaling cascades play a critical role in the pathogenesis of allergic airway inflammation (Ulanova et al., 2005). IL-4R mediates JAK-STAT signaling (Kurgonaite et al., 2015). Clinical trials of therapies targeting Immunoglobulin E (IgE) and the T2 cytokines IL-4, IL-5, and IL-13 have demonstrated that these treatments improve asthma-related clinical outcomes and/or steroid-sparing properties. These results suggest that IL-2 and IL-4 are potential targets for downregulating the JAK-STAT signaling pathway for the treatment of asthma. 4.4 TRP channels TRPM8, TRPA1 and TRPV3 are CHC targets that belong to the calcium ion transmembrane transporter family. The immunological background of asthma is well established but asthma is more than an immunological disorder. Recent studies have highlighted an emerging role for neuro-immune interactions in mediating allergic diseases (Voisin et al., 2017). TRP channels are well studied in the airway, as their activation leads to neurogenic inflammation which is crucial in airway constriction and hyperreactivity. The role of TRP channels, such as TRPA1 (Yang and Li, 23

2016), TRPV1 (Choi et al., 2018), TRPV2 (Cai et al., 2013) and TRPV4 (Naumov et al., 2016) in asthma is becoming increasingly apparent. Common intracellular GPCRs, RTKs and Ca2+ pathways regulate via the activation and sensitization of TRP channels (Gouin et al., 2017), suggesting that TRP channels are new potential targets for asthma treatment. 4.5 Adenosine receptor The adenosine receptor ADORA2A is a CHC target, and other adenosine receptors, such as ADORA1, ADORA2B and ADRB2, are successful targets for the treatment of asthma. Adenosine is one of the human body’s most important neuromodulators in both the central and peripheral nervous systems (Jacobson et al., 2006). The effects of adenosine are modulated via four receptor subtypes, A1 (ADORA1), A2A (ADORA2A), A2B (ADORA2B), and A3 (ADORA3), all of which belong to the family of GPCRs (Fredholm et al., 2011). Increasingly persuasive evidence implicates adenosine in the pathophysiology of asthma (Rorke and Holgate, 2002). As an inflammatory mediator, adenosine participates in the continuous airway inflammatory response through receptors (A2A, A2B and A3) on the mast cell surface (Singh et al., 2016) and in bronchial stenosis in asthmatic patients through the A1 receptor on cell of airway (Pacini et al., 2018). The A2A receptor can regulate the balance of Treg/Th17 cells in asthma (Wang et al., 2016). Selective blockade of these receptors is being exploited by the pharmaceutical industry in an attempt to generate novel therapies for asthma (de Lera Ruiz et al., 2014; Pejman et al., 2014). The A2A receptor has potential in asthma therapeutic applications. 4.6 Steroid hormone receptor The SHRs NR1H4, ESR1, ESR2, NR1I2, PPARA and PPARD are direct targets of herbs, and NR3C1, which encodes the glucocorticoid receptor, is a successful target (Vitellius et al., 24

2016). SHRs are intracellular transcription factors that can be activated, among other possibilities, by the specific and high affinity binding of ligand to exert positive or negative effects on target gene expression. Through PPIs with other sequence-specific transcription factors, SHRs can also regulate the activity of many proteins that are switched on during the inflammatory response (Beato and Klug, 2000). Inflammation is the hallmark of asthma. The glucocorticoid receptor gene, NR3C1, plays a key role in controlling of inflammation of asthma (Newton and Giembycz, 2016). NR3C1 (Panek et al., 2015) and PPARG (Palmer et al., 2007) are successful therapeutic targets in asthma. GCSs are essential drugs and the most important anti-inflammatory agents in the treatment of asthma. Despite having the considerable efficacy of GCSs, only 59% of asthma patients have optimal disease control (Chapman et al., 2008) because of poor compliance due to corticophobia, several side effects associated with steroids, complex drug regimens and the need for prolonged use. These steroids are not disease-modifying agents and they control symptoms only as long as they are taken (Jatakanon et al., 1999; Kikuchi et al., 2005). Patients taking GCSs are also at risk for significant glucocorticoid-related side effects (Szefler and Leung, 1997) and GCSs resistance (Shahid, 2013). These steroid-resistant cases are usually patients with severe asthma with predominant neutrophilic inflammation (Dinwiddie and Muller, 2002). More research is required to find a solution for this issue. TCM formulas target numerous SHRs, including ESR2, ESR1, PPARA, PPARD, PPARG, and NR1I2. There is considerable evidence for a role for sex and sex hormones in the pathogenesis of asthma (Laffont et al., 2017; McCallister et al., 2013). Androgens and glucocorticoids exert anti-inflammatory effects in chronic inflammatory diseases, whereas the role of estrogens is under debate (Capellino et al., 2007). Asthma prevalence and severity are greater in women than in men, 25

and mounting evidence suggests this is in part related to female steroid sex hormones. The effect of estrogens appears to depend on estrogen concentration (low, pro-inflammatory; high, anti-inflammatory) (Calabrese, 2001). Estradiol (E2) has traditionally been appreciated as a key regulator of sexual development, reproduction, the menstrual cycle, and pregnancy; however, its role in modulating functions in a variety of nonreproductive systems in men and women is receiving increased attention (Scariano et al., 2008). E2 acts through two estrogen receptors, ESR1 and ESR2, which belong to the nuclear receptor (NR) superfamily of transcription factors are potential targets for asthma therapy. PPARA, PPARD, PPARG are members of PPAR family of NRs that function as ligand-activated transcription factors. They participate in a range of cellular processes including lipid metabolism, glucose homeostasis, proliferation and differentiation, as well as in the positive and negative regulation of inflammation (Yessoufou and Wahli, 2010). Common genetic variation at the PPARG locus may play an important role in modulating the long-term control of asthma in children and young adults (Palmer et al., 2007). These functions suggest that PPARs are physiological sensors in different stress situations and are valuable targets for innovative therapies (Yessoufou and Wahli, 2010). Asthma can be effectively prevented by concomitant administration of the PPARA agonist rosiglitazone (Liu et al., 2015), pioglitazone (Anderson et al., 2016) or troglitazone (Luczak et al., 2017). NR1I2, also known as steroid and xenobiotic receptor, is also in the NR family of ligand-dependent transcription factors and is a critical transcriptional regulator of a number of important drug metabolizing enzymes and transporters. NR1H4, another nuclear hormone receptor, is involved in metabolic regulation mediated by bile acids in a postprandial state (Calkin and 26

Tontonoz, 2012). Further study on the role of NR1I2 and NR1H4 in asthma is needed. 4.7 MMPs MMP1 and MMP2 are herbal targets and MMP12 is research target. MMPs are a family of enzymes characterized by a common zinc ion at their active site. In general, MMPs are thought to be involved in the normal maintenance of the extracellular matrix; however, they have also been implicated in inflammation and cell–cell signaling (Kelly and Jarjour, 2003). MMPs are important in inflammatory cell migration, healing and pathologic remodeling in the lung (Atkinson et al., 2011; Kelly and Jarjour, 2003; Van Eerdewegh et al., 2002). Asthma is a chronic inflammatory disease of the airways, in which MMPs, bound to cells or within the extracellular matrix, are induced and cause lung pathophysiology (Crosby and Waters, 2010). MMP1 levels are associated with bronchial hyperresponsiveness and MMP1 activation is related to severity of disease exacerbation. ASM/mast cell interactions contribute to asthma severity by transiently increasing MMP activation, ASM growth and airway responsiveness (Naveed et al., 2016). MMP2 and MMP9 (Barbaro et al., 2014; Naik et al., 2017) are also associated with asthma. Although MMPs have received great attention in asthma research, there is no specific asthma drug targeting MMPs in clinical application. Therefore, MMPs are worthy of further attention. 4.8 Ribosomal protein The PRs RPLP0, RPLP1 and RPLP2 are CHC targets. Many RPs function as transcription factors (Naora, 1999), and a growing number of various functions in addition to protein synthesis have been identified for RPs, including the induction of proliferation and apoptosis. Further study on the role of RPs in asthma is needed. 4.9 The in vitro and in vivo effects of TCM compounds 27

TCM compounds, including kaempferol and ginkgolide A, were selected to investigate the anti-asthmatic effect on the potential associated targets according to STRING and DAVID results. Kaempferol and ginkgolide A are associated with potential targets CYP3A4 and NR1I2, respectively (Park and Choi, 2019; Kliewer et al. 2002). In vitro results showed that TCM compounds (kaempferol or ginkgolide A) significantly alleviated the histamine-induced contraction of human ASMCs, respectively. Consistently, In vivo results showed that kaempferol or ginkgolide A significantly reduced the pulmonary resistance in mouse model.

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5. Conclusion TCM formulas exhibit broad activity on multiple asthma pathologic mechanisms, including bronchorelaxing activity, anti-inflammatory and immunomodulatory effects, and the inhibition of airway remodeling and the restoration of HPA axis disturbances. These actions of CHM may be beneficial for treating corticosteroid-resistant asthma (Hong et al., 2011). Bioinformatics analyses of TCM formulas are useful for the identification of key target proteins and pathways associated with asthma. Moreover, some crucial proteins, such as GABBR1, OR1D2, IL2, IL4, TRPM8, TRPA1, TRPV3, CYP1B1, CYP2B6, CYP1A2, CYP3A4, CYP1A1, PPARA, NR1I2, PPARD, MMP1, MMP2, ESR1, ESR2, RPLP0, RPLP1 and RPLP2, are potential targets for asthma therapy. Potential target discovery for asthma treatment based on the clinical effectiveness of TCM is a feasible strategy.

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Acknowledgments This work was supported by the National Natural Science Foundation of China (No. 81973951, 81922076, 81973952, 81473760) and the National Key R&D Program of China (No. 2018YFC1704600).

Author contributions Yu Wang ([email protected]) performed the main experiments and analysis and drafted the manuscript. Yan-Jiao Chen ([email protected]), Cheng Xiang ([email protected]) and Guang-Wei Jiang ([email protected]) conducted cell experiments and animal experiments. Yu-Dong Xu ([email protected]), Lei-Miao Yin ([email protected]), Dong-Dong Zhou ([email protected]) and Yan-Yan Liu ([email protected]) analyzed the data and searched the literature. Yong-Qing Yang ([email protected]) designed the research, analyzed the data and wrote the manuscript. All authors reviewed the manuscript.

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42

Table 1. The list of 32 candidate herbs for asthma and three inclusion criteria Rank

Herbs

1

Ephedra sinica Stapf (Herbaceous stalk)

2

Prunus armeniaca L. (Seed)

3

Pinellia ternata Ten. ex Breitenb. (Rhizome)

4

Acanthopanax gracilistylus W.W.Sm. (Seed)

5

Poria cocos (Schw.) Wolf (Sclerotium)

6

Perilla frutescens (L.) Britton (Seed)

7

Citrus reticulata Blanco (Peel)

8

Asarum heterotropoides F.Schmidt (Rhizome)

9

Atractylodes macrocephala Koidz. (Rhizome)

10

Pheretima aspergillum (E. Perrier)

11

Descurainia sophia (L.) Webb ex Prantl (Seed)

12

Scutellaria baicalensis Georgi (Root)

13

Morus alba L. (Bark)

14

Cinnamomum cassia (L.) J.Presl(Branch)

15

Astragalus membranaceus Moench (Root)

16

Fritillaria cirrhosa D.Don (Bulb)

17

Codonopsis pilosula Nannf. (Root)

18

Sinapis alba L.(Seed)

19

Zingiber officinale Roscoe (Root)

20

Paeonia lactiflora Pall. (Root)

21

Aster tataricus L.f. (Root)

22

Citrus aurantium L. (Fruit)

23

Tussilago farfara L. (Flower)

24

Platycodon grandiflorum(Jacq.)A.DC. (Rhizome)

25

Magnolia officinalis Rehder & E.H.Wilson (Bark)

26

Gypsum Fibrosum

43

Classical

Modern

formulas

formulas

herbal

Compendium Of MateriaMedica

27

Belamcanda chinensis (L.) Redouté (Rhizome)

28

Ginkgo biloba L.(Seed)

29

Trichosanthes kirilowii Maxim. (Fruit)

30

Peucedanum praeruptorum Dunn (Root)

31

Stemona sessilifolia (Miq.) Miq. (Root)

32

Aconitum carmichaeli Debx.(Seminal root)

44

Table 2. 68 candidate therapeutic target proteins of CHCs for asthma No.

Target proteins

UniProt ID

Gene symbol

1

3-hydroxy-3-methylglutaryl-coenzyme A reductase

P04035

HMGCR

2

5,6-dihydroxyindole-2-carboxylic acid oxidase

P17643

TYRP1

3

60S acidic ribosomal protein P0

P05388

RPLP0

4

60S acidic ribosomal protein P1

P05386

RPLP1

5

60S acidic ribosomal protein P2

P05387

RPLP2

6

72 kDa type IV collagenase

P08253

MMP2

7

Adenosine receptor A2a

P29274

ADORA2A

8

Amine oxidase [flavin-containing] A

P21397

MAOA

9

Amine oxidase [flavin-containing] B

P27338

MAOB

10

Apoptosis regulator BAX

Q07812

BAX

11

Arachidonate 5-lipoxygenase

P09917

ALOX5

12

Bifunctional protein NCOAT

O60502

MGEA5

13

Bile acid receptor

Q96RI1

NR1H4

14

Caspase-3

P42574

CASP3

15

Cell-death-related nuclease 7

P34387

crn-7

16

Collagen alpha-1(III) chain

P02461

COL3A1

17

Cytochrome P450 1A1

P04798

CYP1A1

18

Cytochrome P450 1A2

P05177

CYP1A2

19

Cytochrome P450 1B1

Q16678

CYP1B1

20

Cytochrome P450 2B6

P20813

CYP2B6

21

Cytochrome P450 3A4

P08684

CYP3A4

22

Cytosolic phospholipase A2

P47712

PLA2G4A

23

Dolichyl-phosphate beta-glucosyltransferase

Q9Y673

ALG5

24

Estrogen receptor

P03372

ESR1

25

Estrogen receptor beta

Q92731

ESR2

26

Estrogen sulfotransferase

P49888

SULT1E1

27

Gamma-aminobutyric acid type B receptor subunit 1

Q9UBS5

GABBR1

28

Heparin-binding growth factor 2

P09038

FGF2

45

29

Integrin alpha-IIb

P08514

ITGA2B

30

Interleukin-2

P60568

IL2

31

Interleukin-4

P05112

IL4

32

Interleukin-8

P10145

IL8

33

Interstitial collagenase

P03956

MMP1

34

Katanin p60 ATPase-containing subunit A1

O75449

KATNA1

35

Kv channel-interacting protein 2

Q9NS61

KCNIP2

36

Lipoprotein lipase

P06858

LPL

37

Maltase-glucoamylase, intestinal

O43451

MGAM

38

Myeloperoxidase

P05164

MPO

39

Nitric oxide synthase, inducible

P35228

NOS2

40

Nuclear receptor subfamily 1 group I member 2

O75469

NR1I2

41

Olfactory receptor 1D2

P34982

OR1D2

42

Pepsin A

P00790

PGA5

43

Peroxidase C1A

P00433

PRXC1A

44

Peroxisome proliferator-activated receptor alpha

Q07869

PPARA

45

Peroxisome proliferator-activated receptor delta

Q03181

PPARD

46

Peroxisome proliferator-activated receptor gamma

P37231

PPARG

47

Phosphatidylinositol-5-phosphate 4-kinase type-2 alpha

P48426

PIP4K2A

48

Plasminogen

P00747

PLG

49

Platelet basic protein

P02775

PPBP

50

Poly [ADP-ribose] polymerase 1

P09874

PARP1

51

Putative adenosylhomocysteinase 2

O43865

AHCYL1

52

Serine/threonine-protein kinase 6

O14965

AURKA

53

Serine/threonine-protein phosphatase 2B catalytic subunit alpha isoform

Q08209

PPP3CA

54

Signal transducer and activator of transcription 3

P40763

STAT3

55

Sodium/potassium-transporting ATPase subunit alpha-1

P05023

ATP1A1

56

Telomerase protein component 1

Q99973

TEP1

57

Trans-cinnamate 4-monooxygenase

P92994

CYP73A5

58

Transcription factor AP-1

P05412

JUN

46

59

Transcription factor p65

Q04206

RELA

60

Transient receptor potential cation channel subfamily A member 1

O75762

TRPA1

61

Transient receptor potential cation channel subfamily M member 8

Q7Z2W7

TRPM8

62

Transient receptor potential cation channel subfamily V member 3

Q8NET8

TRPV3

63

Tumor necrosis factor

P01375

TNF

64

Tyrosinase

P14679

TYR

65

Tyrosine-protein kinase JAK1

P23458

JAK1

66

Tyrosyl-DNA phosphodiesterase 1

Q9NUW8

TDP1

67

Vascular endothelial growth factor A

P15692

VEGFA

68

Xanthine dehydrogenase/oxidase

P47989

XDH

47

Table 3. Functional classification of targets for asthma by DAVID Group

Terms

Targets of CHCs

Targets of CM

Group 1

G-protein coupled receptor

GABBR1, OR1D2

ADORA2B, GPR35, CYSLTR1, EDNRB, EDNRA, HRH4, HRH1, LTB4R, PTGDR2, BDKRB2, ADRB2, ADRB1, CCR4, CCR3, CXCR2, TACR1, CXCR1, TACR2

Group 2

positive regulation of B cell proliferation; JAK-STAT

IL2, IL4

IL5, IL13

signaling pathway Group 3

Metalloprotease

-

ADAM8, ADAM10, ADAM33

Group 4

TRP channels

TRPM8, TRPA1, TRPV3

-

Group 5

Cytochrome P450

CYP1B1, CYP2B6, CYP1A2,

TBXAS1

CYP3A4, CYP1A1 Group 6

Steroid hormone receptor; PPAR signaling pathway

PPARA, PPARD, NR1I2,

-

Group 7

Peptidase

MMP1, MMP2

MMP12

M10A,

cysteine

switch,

Matrix

metallopeptidase Group 8

Steroid hormone receptor

ESR1, ESR2, NR1I2

NR3C1

Group 9

Ribosomal protein; cytoplasmic translation

RPLP0, RPLP1, RPLP2

-

Abbreviations: CHCs: Chinese herb compounds; CM: conventional medicine.

48

Highlights •

10 classical formulas for asthma and sovereign medicinal herbs of the classical formulas are discussed.

•

130 herb compounds of 32 herbs and 68 targets for asthma are discussed.

•

88 modern medicine targets for asthma from TTD and PubMed are discussed.

•

The proteins directly targeted by herbal compounds, such as TRPM8, TRPA1, TRPV3, CYP1B1, CYP2B6, CYP1A2, CYP3A4, CYP1A1, PPARA, PPARD, NR1I2, MMP1, MMP2, ESR1, ESR2, RPLP0, RPLP1 and RPLP2, are potential targets for asthma therapy.