identifying potential quality markers of xin-su-ning

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Phytomedicine

journal homepage: www.elsevier.com/locate/phymed

Identifying potential quality markers of Xin-Su-Ning capsules acting onarrhythmia by integrating UHPLC-LTQ-Orbitrap, ADME prediction andnetwork target analysis

Rui Guoa,b,1, Xiaoxiao Zhangc,1, Jin Sua, Haiyu Xua,e,⁎, Yanqiong Zhanga,⁎, Fangbo Zhanga,Defeng Lia, Yi Zhanga, Xuefeng Xiaob,⁎, Shuangcheng Mad,⁎, Hongjun Yanga

a Institute of Chinese Materia Medica, China Academy of Chinese Medical Sciences, Beijing, PR Chinab Tianjin University of Traditional Chinese Medicine, Tianjin 300193, PR Chinac Beijing University of Chinese Medicine, Beijing 100029, PR ChinadNational Institutes for Food and Drug Control, Beijing 100050, PR Chinae Shanxi institute of international trade & Commerce, Xianyang 712046, PR China

A R T I C L E I N F O

Keywords:Quality markerTraditional Chinese medicineUHPLC-LTQ-OrbitrapAbsorption-distribution-metabolism-excretionNetwork target

A B S T R A C T

Background: Quality marker (Q-markers) has been proposed as a novel concept for quality evaluation andstandard elaboration of traditional Chinese medicine (TCM). Xin-Su-Ning capsule (XSNC) has been extensivelyused for the treatment of arrhythmia with the satisfactory therapeutic effects in clinics. However, it is lack ofreliable and effective Q-markers of this prescription.Purpose: To identify potential Q-markers of XSNC against arrhythmia.Study Design: An integrative pharmacology-based investigation was performed.Methods: Ultra-high-pressure liquid chromatography coupled with linear ion trap-Orbitrap tandem mass spec-trometry (UHPLC-LTQ-Orbitrap) was performed to identify the preliminary chemical profile of XSNC in a rapidand high-throughput manner. Then, in silico Absorption-Distribution-Metabolism-Excretion (ADME) modelswere utilized to screen candidate active chemical compounds characterized by drug-likeness features. In addi-tion, drug target-disease gene interaction network was constructed, and network features were calculated toidentify key candidate targets and the potential Q-markers of XSNC against arrhythmia.Results: A total of 41 chemical compounds with good drug-likeness and more chances to be absorbed into bodywere identified as the candidate bioactive chemical compounds which might offer contributions to the ther-apeutic effects of XSNC against arrhythmia in vivo. Following the prediction of 921 XSNC putative targets andthe construction of XSNC putative target-known therapeutic target of arrhythmia interaction network, 315 hubnodes with high connectivity were selected. Functionally, the hub nodes were involved into modulation ofcardiac sympatho-vagal balance, regulation of energy production and metabolism, as well as angiogenesis andvascular circulation during the development and progression of arrhythmia. Moreover, 63 major hubs withnetwork topological importance were chosen as XSNC candidate targets against arrhythmia. Furthermore,berberine, palmatine, scopoletin, liquiritigenin, naringenin, formononetin, nobiletin, tangeretin, 5-de-methylnobiletin, kushenol E and kurarinone hitting the corresponding XSNC candidate targets were screened outto be the potential Q-markers of XSNC against arrhythmia.Conclusion: Our integrative pharmacology-based approach combining UHPLC-LTQ-Orbitrap, in silico ADMEprediction and network target analysis may be efficient to identify potential Q-markers of TCM prescriptions.Our data showed that berberine, palmatine, scopoletin, liquiritigenin, naringenin, formononetin, nobiletin,tangeretin, 5-demethylnobiletin, kushenol E and kurarinone might function as candidate markers for qualitativeevaluation of XSNC.

https://doi.org/10.1016/j.phymed.2018.01.019Received 27 July 2017; Received in revised form 20 December 2017; Accepted 21 January 2018

⁎ Corresponding authors.

1 These authors contributed equally to this work.E-mail addresses: [email protected] (H. Xu), [email protected] (Y. Zhang), [email protected] (X. Xiao), [email protected] (S. Ma).

Phytomedicine 44 (2018) 117–128

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Introduction

Since traditional Chinese medicine (TCM) herbs usually containhundreds of different chemical compounds, it is difficult to performquality control of them (Liu et al., 2010). According to the Pharmaco-poeia of China in 2015, the existing quality standards of TCM herbs arehardly associated with biological actions and therapeutic efficacy. Inrecent years, quality marker (Q-markers) has been proposed as a novelconcept for quality evaluation and standard elaboration of TCM (Liuet al., 2016; Guo, 2017; Ding et al., 2017). Q-markers are defined as theinherent chemical compounds from herbal medicine or generatedcompounds during the processing preparation (Liu et al., 2016). Due tothe key biological activities, Q-markers may offer great contributions tothe therapeutic effects of TCM prescriptions and often closely related tothe pharmacological mechanisms (Liu et al., 2017). Therefore, biolo-gical active chemical compounds may be an important part of Q-mar-kers. Integrative pharmacology (IP) has been proved as an efficientapproach to screen biological active chemical compounds and to in-vestigate the underlying pharmacological mechanisms of TCMs by in-tegrating high-throughput chemical identification, Absorption-Dis-tribution- Metabolism-Excretion (ADME)/pharmacokinetics (PK) studyand network analysis (Xu and Yang, 2014; Xu et al., 2017). Our re-search group has recently performed several IP-based investigations toefficiently identify and validate a list of biological active chemicalcompounds of various TCM Patent Prescriptions, such as Nao-Xin-Tongcapsule (Xu et al., 2016) and Guan-Xin-Jing capsule (Zhang et al.,2017b).

Xin-Su-Ning capsule (XSNC), approved by the China Food and DrugAdministration, has been extensively used for the treatment of ar-rhythmia with the satisfactory therapeutic effects in clinics. XSNCconsists of 11 Chinese herbs, including Coptis chinensis Franch. (Huang-Lian, HL), Pinellia ternata (Thunb.) Breit. (Ban-Xia, BX), Poria cocos(Schw.) Wolf (Fu-Ling, FL), Citrus aurantium L. (Zhi-Shi, ZS), Dichroafebrifuga Lour. (Chang-Shan, CS), Nelumbonucifera Gaertn. (Lian-Zi-Xin,LZX), Sophora flavescens Ait. (Ku-Shen, KS), Artemisia annua L. (Qing-Hao, QH), Pana: c ginseng C. A. Mey. (Ren-Shen, RS), Ophiopogon ja-ponicus (L. f) Ker-Gawl. (Mai-Dong, MD) and Glycyrrhiza uralensis Fisch.(Gan-Cao, GC). Chemically, there are a number of alkaloids identifiedin different herbs such as HL (Yuan et al., 2017), KS (Hou et al., 2016),LZX (Xie et al., 2016), etc. Meanwhile, other phytochemical com-pounds, such as saponins, flavonoids, etc., have been isolated from thecorresponding herbs containing in XSNC (Byong-Kyu et al., 2015; Liuet al., 2016). However, only berberine was indicated to be a marker ofXSNC for qualitative identification and quantitative analysis, accordingto the instruction of Committee for the Pharmacopoeia of China in2015. Therefore, it is of great significance to screen novel and efficientQ-markers for this prescription, which may improve the level of qualitycontrol and promote the internationalization of TCMs.

In the current study, an IP-based approach was employed to identifypotential Q-Markers of XSNC by combining high-throughput chemicalanalysis, in silico ADME prediction and network target identification(Fig. 1). Briefly, ultra-high-pressure liquid chromatography coupledwith linear ion trap-Orbitrap tandem mass spectrometry (UHPLC-LTQ-Orbitrap) was performed to identify the preliminary chemical profile ofXSNC in a rapid and high-throughput manner. Then, in silico ADMEmodels were utilized to screen the candidate active chemical com-pounds characterized by the drug-likeness features. Finally, drug target-disease gene interaction network was constructed, and network featureswere calculated to identify candidate targets and potential Q-markers ofXSNC acting on arrhythmia.

Materials and methods

Reagents and chemicals

UHPLC-grade acetonitrile was purchased from Fisher Scientific Co.

(Loughborough, UK). Water was purified using a Milli-Q system(Millipore, Billerica, MA, USA). Other reagents were analytical grade.Reference standards of matrine, sophocarpine, jatrorrhizine, epi-berberine, coptisine, scopoletin, berberine, hesperidin, liquiritigenin,nobiletin, tangeretin, 5-demethylnobiletin and kuraridine were pur-chased from the National Institute for the Control of Pharmaceuticaland Biological Products (Beijing, China). All reference standards hadhigh purities which were more than 98%, and were suitable for UHPLC-LTQ-Orbitrap analysis. XSNC were supplied by Shanxi MomentumPharmaceutical Co., Ltd (Batch NO. 150603; Shanxi, China).

Preparation of samples and standard solution

XSNC were completely removed the capsule and weighed 0.5 g ofthe powder precisely. The powder was soaked in 45ml of 75% ethanolfor 60min, ultrasonically extracted at room temperature for 30min,and settled to a volume of 50ml. Respective standard stock solutions ofthirteen chemical compounds (matrine, sophocarpine, jatrorrhizine,epiberberine, coptisine, scopoletin, berberine, hesperidin, liquir-itigenin, nobiletin, tangeretin, 5-demethylnobiletin, kuraridine) wereprepared at concentrations of 50 ng/ml by weighing the desired amountof each component into a volumetric flask and dissolving it in me-thanol. All the samples were filtered through 0.22mm nylon membranefilters and analyzed directly by UHPLC-LTQ-Orbitrap.

Instrument and UHPLC-LTQ-Orbitrap conditions

Sample analyses were performed on a Thermo Accela UHPLCsystem (Thermo Fisher Scientific, San Jose, CA, USA) equipped with abinary pump, an online degasser, a thermostated autosampler, a ther-mostatically controlled column compartment, and adiode array de-tector (DAD). A reverse-phase Welch Xtimate C18 (4.6× 250mm,5 µm) column was used with a flow rate of 0.4ml/min at 30 °C. Thetemperature of sample room was set to 4 °C and the injection volumewas10 µL. The mobile phase was a mixture of 0.2% ammonia and 0.1%formic acid in water (A) and acetonitrile (B), respectively. The fol-lowing linear gradient was used: 0–30min, 6%B; 30–40min, 6–17%B;40–46min, 17–20%B; 46–66min, 20–30%B; 66–90min, 30–40%B;90–95min, 40–50%B; 95–105min, 50–100%B; 105–115min, 100%B.The on-line UV spectra were recorded in the range of 200–400 nm.

For LC-ESI-MSn experiments, a Thermo Fisher LTQ-OrbitrapVelosPro Hybrid mass spectrometer (Thermo Fisher Scientific, Bre-men,Germany) equipped with an electrospray ionization (ESI) source wasconnected to the above UHPLC instrument. The experiment was per-formed on both the positive and negative ion modes and full scans wasacquired in the range of 50–1500m/z with a resolution of 30,000 and

Fig. 1. Schematic diagram for identifying potential quality-markers of XSNC acting onarrhythmia by integrating UHPLC-LTQ-Orbitrap, ADME prediction and network targetanalysis.

R. Guo et al. Phytomedicine 44 (2018) 117–128

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the resolution of followed MSn scan in the Orbitrap was 15,000. Theparameters for the ESI source were set as follows: source temperature,350 °C; sheath gas flow rate, 3000 kPa; sheath and auxiliary gas flowrate, 1000 kPa; spray voltage, 350 V; capillary temperature, 300 °C. TheMass Frontier 6.0 (Thermo Fisher Scientific) software and Xcalibur 2.1(Thermo Fisher Scientific) software were employed for data analysis.The accuracy error threshold was fixed at 10 ppm.

Prediction of oral absorption and bioavailability using in silico ADMEmodels

Structural information (*.mol or *.sdf files) of the XSNC chemicalcompounds were downloaded from ChemSpider (http://www.chemspider.com/) or drawn using Chemdraw 12.0 and saved in“.mol” format. ADME estimation of these chemical compounds wascarried out using ACD/Percepta software 5.07 (ACD/Labs, Toronto,ON, Canada), including the passive intestinal permeability of Caco-2module and the PK explorer module.

Known therapeutic targets of arrhythmia

Known therapeutic targets of arrhythmia were collected from theDrugBank database (Wishart et al., 2008) (http://www.drugbank.ca/,version: 3.0, November 13, 2016) and the OMIM database(Hamosh et al., 2005) (www.omim.org/, last updated October 31,2013). Drug-target interactions, in which drugs are approved by theFood and Drug Administration (FDA) for the treatment of arrhythmia,and the targets are human genes/proteins, were enrolled in this study.Detailed information of known therapeutic targets of arrhythmia isprovided in Supplementary Table S1.

Protein–protein interaction data

Protein–protein interaction (PPI) data were derived from the ex-isting PPI databases [12–19] as shown in Supplementary Table S2.

Predicting putative targets of XSNC

MedChem Studio (version 3.0; Simulations Plus, Inc., Lancaster, CA,USA, 2012) was used as an efficient drug similarity search tool toidentify known drugs with similar structures to chemical compoundscontaining in XSNC (Yu et al., 2016a). We only selected the component-putative target pairs, in which the structural similarity scores of che-mical compounds to known drugs were higher than 0.80 (moder-ate∼high similarity). Detailed information of XSNC putative targets isprovided in Supplementary Table S3.

Drug target-disease gene interaction network analysis

Drug target-disease gene interaction network was constructed usingthe links among XSNC putative targets and known therapeutic targets ofarrhythmia. Network visualization was performed using Navigatorsoftware (version 2.2.1, Toronto, ON, Canada). After that, the hubs withthe degree more than two-fold median value of all nodes' degree werescreened according to our previous studies (Yu et al., 2016a; Zhanget al., 2016a,b, 2017a). Then, the hub network was constructed basedon the direct interactions among hubs. Moreover, four topologicalproperties of the hub network, including “degree”, “betweenness”,“closeness”, and “coreness”, were calculated to screen the XSNC can-didate targets with topological importance. The definitions of the fourtopological features were reported as our previous studies (Guo et al.,2016; Zhang et al., 2016c, 2017b). Major hubs were identified only thetopological features of hubs were higher than the correspondingmedian values.

Pathway enrichment analysis

A pathway enrichment analysis was performed using the DatabaseVisualization and Integrated Discovery software (DAVID, http://david.abcc.ncifcrf.gov/home.jsp, version 6.7) based on the pathway dataobtained from the Kyoto Encyclopedia of Genes and Genomes database(KEGG, http://www.genome.jp/kegg/, updated on November 18,2016) (Dennis et al., 2003; Kanehisa et al., 2000). Only functionalannotations having the enrichment P values corrected by both algo-rithms Bonferroni and Benjamini (P < 0.05) were selected for furtheranalysis.

Results and discussion

Characterization and rapid identification of chemical compounds of XSNCusing UHPLC-LTQ-Orbitrap

Chromatographic techniques coupled with mass spectrometry mayprovide avenues for rapid identification of known and unknown com-pounds containing TCM herbs. The UHPLC-LTQ-Orbitrap methodcombining the efficient separation and the great capability for struc-tural characterization, was employed as a fast, sensitive and reliableplatform for high-throughput identification of the chemical compoundsof TCMs, independent of the macro- and micro-chemical compounds(Wang et al., 2015). In the present study, a specific UHPLC-ESI-LTQ/Orbitrap MSn protocol was performed to rapidly identify the com-pounds of XSNC as many as possible after optimizing the LC and MSconditions systemically. The total ion chromatograms (TIC) of XSNC areillustrated in the positive and negative ion modes as shown in Fig. 2.

For the compounds with chemical standards, we compared the re-tention time, as well as accurate and high-resolution mass and tandemmass spectra. As a result, 13 compounds (Compound 5, 6, 19, 20, 21,30, 32, 36, 44, 56, 57, 61 and 65) were identified as matrine, sopho-carpine, jatrorrhizine, epiberberine, coptisine, scopoletin, berberine,hesperidin, liquiritigenin, nobiletin, tangeretin, 5-demethylnobiletinand kuraridine, respectively. For the compounds without chemicalstandards, the molecular formula was established by high-accuratequasi-molecular ion such as [M−H]−, [M+CH3COO]−, [M]+, [M+H]+, and [M+Na]+ within a mass error of 5.0 ppm and fractionalisotope abundance. After that, the MSn information was also used toconfirm the structures of compounds by comparing the fragmentationpatterns and pathways with 13 standards or the related literatures(Guo et al., 2014; Liu et al., 2011; Sun et al., 2014; Yu et al., 2016a).

For example, high-accurate quasi-molecular ions of compound 36were obtained in both positive and negative ion modes at m/z611.19360 and 609.18079, which was identified as hesperidin(C28H34NO15) by comparing the retention time and high-resolutionmass spectra with the standards. Meanwhile, the MSn informationshowed that the [M+H]+ ion of hesperidin at m/z 611 was fragmentedby the continuous loss of 162 Da (–C6H10O5, glucose) at m/z 449 and146 Da (–C6H10O4, rhamnose) at m/z 303, which were in line with theprevious literatures (Yu et al., 2016b, 2014) and also were utilized tospeculate the structures for other derivatives of flavones glycosides,such as neohesperidin, naringin, Liquiritin apioside, etc. Overall, a totalof 73 chemical compounds including thirty-two flavonoids and twenty-five alkalodis, were identified in XSNC or characterized with their re-tention times and MSn data as summarized in Table 1. Among them,flavonoids and alkalodis were the top two categories which were re-spectively derived from multiple herbs such as ZS, GC, BX, KS and LZX,etc.

Prediction of oral absorption and bioavailability for chemical compoundscontaining in XSNC

Evaluation of oral absorption and bioavailability may provide in-depth insights into the therapeutic effects of TCM formulae due to their


119

http://www.chemspider.com/

http://www.chemspider.com/

http://www.drugbank.ca/

http://www.omim.org/

http://david.abcc.ncifcrf.gov/home.jsp

http://david.abcc.ncifcrf.gov/home.jsp

http://www.genome.jp/kegg/

oral administration (Tao et al., 2013). Generally, a compounds withPapp values greater than 7×106 cm/s and oral bioavailability (OB, F%) greater than 40% had excellent oral absorption and good drug-likeness characteristics (Yazdanian et al., 1998). Here, the caco-2 andthe PK explorer modules of ACD/Percepta software were utilized topredict the Papp and OB values for the chemical compounds containingin XSNC. As a result, a total of 41 chemical compounds (Compound1–11, 13–14, 16, 27, 29, 32, 36–37, 42–49, 51–55, 57, 59–60, 62–64,67–68, 72) were predicted to have good drug-likeness with morechances to be absorbed into body and contribute to the therapeuticeffects of XSNC against arrhythmia in vivo.

Putative targets of XSNC

On the basis of chemical compounds' structural similarity, a total of921 XSNC putative targets were predicted (Supplementary Table S3).Among them, 596 (64.71%), 181 (30.37%), 210 (22.80%), 520(56.46%), 97 (10.53%), 195 (21.17%), 228 (24.76%), 425 (46.15%),479 (52.01%), 716 (77.74%), 355 (38.55%) and 17 (1.85%) were re-spectively the putative targets of Pinellia ternata (Thunb.) Breit., Dichroafebrifuga Lour., Poria cocos (Schw.) Wolf, Glycyrrhiza uralensis Fisch.,Coptis chinensis Franch., Sophora flavescens Ait., NelumbonuciferaGaertn., Ophiopogon japonicus (L. f) Ker-Gawl., Artemisia annua L., Pana:c ginseng C. A. Mey., Citrus aurantium L. and Coptis chinensis Franch. Of921 XSNC putative targets, 329 were known therapeutic targets of ar-rhythmia, implying the candidate pharmacological effects of XSNC tothis disease.

According to the results of enrichment analysis based on BiologicalProcess and Molecular Function obtained from Gene ontology (GO),XSNC putative targets were frequently involved into several biologicalprocesses during oxidative phosphorylation, such as carboxylic acidmetabolic process (P = 2.1E−28), oxoacid metabolic process(P= 3.7E−26), organic acid metabolic process and ion transport(P= 2.3E−25), as well as often had signaling receptor activity(P= 1.1E−48). Regarding to the enriched pathways, XSNC putativetargets were significantly associated with neuromodulation pathways,including Neuroactive ligand-receptor interaction (P=6.8E−55),Calcium signaling pathway (P=6.6E−27), Serotonergic synapse(P= 9.1 E−15) and GABAergic synaps (P=4.3E−17), as well as

energy produce and metabolism pathways, including Glutathione me-tabolism (P= 1.3E−24), cAMP signaling pathway (P= 6.1E−21),cGMP-PKG signaling pathway (P= 4.4E−12).

Pharmacological mechanisms of XSNC acting on arrhythmia

Drug target-disease gene interaction network included 1092 nodesand 10,071 interactions. According to the node degree in the network, atotal of 315 hub nodes, the degree values of which were more than two-fold of the median degree of all nodes, were selected. Among them, 227hubs were XSNC putative targets and 186 hubs were known therapeutictargets of arrhythmia.

To investigate the pharmacological mechanisms of XSNC acting onarrhythmia, the hub network was constructed using the direct inter-actions between hubs, and contained 315 hub nodes and 4967 edges.Functionally, the hub nodes were divided into three functional mod-ules, including modulation of cardiac sympatho-vagal balance, regula-tion of energy production and metabolism, as well as angiogenesis andvascular circulation (Fig. 3).

The autonomic nervous system plays crucial roles in modulatingcardiac excitability and contractile function (Habecker et al., 2016). Inthe setting of arrhythmia, the neurohumoural systems are activated,leading to the increased sympathetic stimulation and reduced vagaltone (Kalla et al., 2016). At the early stage, this imbalance may be anadaptive response to maintain cardiac output; However, in the longterm, it may result in the maladaptive environment of persistent sym-pathetic activity and the progression into fatal arrhythmia(Zucker et al., 2012) Thus, the therapies targeted to the cardiac vagusand sympathetic nervous system may be efficient to attenuate ar-rhythmia. In the current study, our data showed that the hubs of XSNCputative target-arrhythmia related gene interaction network, includingADRA1A, ADRA1B, ADRA1D, ADRA2A, ADRA2B, ADRA2C, ADRB2,ADRB3, CHRM1, CHRM2, CHRM3, CHRM4, CHRM5, were significantlyinvolved into G-protein coupled acetylcholine receptor signalingpathway, Alpha-adrenergic receptor activity/ epinephrine binding,suggesting that XSNC may contribute to the reverse the imbalance ofsympatho-vagal system during arrhythmia.

In addition, accumulating studies have revealed that hypoxic con-ditions during arrhythmia often induce inadequate intake of nutrients

Fig. 2. UHPLC-ESI- LTQ-Orbitrap-MS of XSNC in the positive (A) and negative ion modes (B).


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Table 1MS data of ESI-MS spectra and identification of the XSN enteric-coated tablet.

No. RT (min) Measuredmass (m/z)

MS2 Polarity Formula Compound Name Error (ppm) CACO-2× 10−6

F (%)

1 9.23 265.18961[M+H]+

247.18025 [M+H−H2O]+,164.10681 [M+H−C5H11ON]+

112.07552 [M+H−C10H15ON]+

Positive C15H24O2N2 Sophoranol (Guo, et al., 2011;Liu et al., 2011)

−1.445 38 96.9

2 10.83 265.18967[M+H]+

247.18025 [M+H−H2O]+

164.10678 [M+H−C5H11ON] +,

148.11198 [M+H−C5H10O2N] +,112.07552 [M+H−C9H15ON]+

Positive C15H24O2N2 Oxymatrine (Guo, et al., 2011;Liu et al., 2011)

−1.385 86 99.7

3 12.83 263.17401[M+H]+

195.14905 [M+H−C4H4O]+,166.12251 [M+H−C5H7NO]+,

148.11197 [M+H−C5H7NO−H2O]+

Positive C15H22O2N2 Oxysophocarpine (Liu et al.,2006; Liu et al., 2011)

−1.394 67 99.6

4 13.65 249.19507[M+H]+

176.10677 [M+H−C4H11N]+,150.12755 [M+H−C5H9ON]+,148.11200 [M+H−C5H11ON]+

Positive C15H24ON2 Sophoridine −1.010 114 99.5

5 15.25 249.19507[M+H]+

231.18524 [M+H−H2O] +, 176.10675 [M+H−C4H11N]+, 148.11209 [M+H−C5H11ON]+

Positive C15H24ON2 Matrine (Liu et al., 2011) −1.010 114 99.5

6 16.37 247.17932[M+H]+

229.14194 [M+H−H2O] +,179.15425 [M+H−C4H4O]+,150.12769 [M+H−C5H7ON]+,136.11203 [M+H−C6H9ON]+

Positive C15H22ON2 Sophocarpine (Liu et al.,2006; Liu et al., 2011)

−1.170 90 99.5

7 19.23 247.17935[M+H]+

229.14194 [M+H−H2O] +,179.15425 [M+H−C4H4O]+,150.12769 [M+H−C5H7ON]+,136.11203 [M+H−C6H9ON]+

Positive C15H22N2O 7,11-Dehydromatrin (Liuet al., 2011)

−1.210 143 99.5

8 19.81 265.18982[M+H]+

150.12756 [M+H−C5H9O2N] + Positive C15H24N2O2 Lamprolobine (Liu et al.,2011)

−1.235 146 99.7

9 21.72 314.17358[M+H]+

269.11734 [M+H−C2H7N]+,175.07538 [M+H−C8H13ON]+

107.04909 [M+H−C12H17NO2]+

Positive C19H23NO3 Armepavine/ Armepavineisomer

−1.490 191 99.4

312.15869[M−H]−

No Negative −0.730

10 22.84 314.17358[M+H]+

269.11703 [M+H−C2H7N]+,175.07513 [M+H−C8H13ON]+,107.04897 [M+H−C12H17NO2]+


−1.550 191 99.4

11 24.30 312.15753[M+H]+

297.13574 [M+H−CH3]+,

269.11710 [M+H−C2H5N]+

205.10963 [M−H−C7H7O]+,175.07523 [M−H−C8H11NO]+

Positive C19H21NO3 Pronuciferine −1.610 203 99.7

12 26.23 342.16852[M]+

297.11215 [M−C2H8N]+

265.08600 [M−C3H12NO]+Positive C20H23NO4 Magnoflorine (Sun et al.,

2014)−1.615 0.2 5.7

13 27.74 261.15839[M+H]+

243.14906 [M+H−H2O]+,215.15410 [M+H−HCOOH]+

Positive C15H20N2O2 9a-Hydroxysophoramine/ 7a-Hydroxysophoramine/Baptifoline (Liu et al., 2011)

−1.364 8 63.8

14 28.55 314.17352[M+H]+

299.15125 [M+H−CH3]+,283.13266 [M+H−CH3−OH]+,269.11713 [M+H−C2H7N]++


−1.640 191 99.4

15 29.43 487.14200[M+H]+

341.08501 [M+H−C6H10O4] +,179.03300 [M+H−C6H10O4−C6H10O5] +

Positive C21H26O13 Fabiatrin (Yu et al., 2016) −2.617 0.1 4.4

485.12710[M−H]−


16 33.41 324.12167[M+H]+

309.09958 [M+H−CH3] +,280.09705 [M+H−CH3CHO]+

Positive C19H17NO4 Groenlandicine (Jiang et al.,2012)

−1.365 244 99.7

322.10715[M−H]−


17 34.10 352.11618[M]+

337.09427 [M+H−CH3],308.09164 [M+H−C2H5O]

Positive C20H18NO5 Berberastine (Jiang et al.,2012)

−1.769 0.1 5.6

18 36.29 579.1673 [M+H]+

No Positive C27H30O14 Isorhoifolin (Ye et al., 2014) −3.532 0 1.2

577.1524[M−H]−


19 37.74 338.13727[M]+

323.11536 [M−CH3],308.09192 [M−CH3−CH3],294.11295 [M−CH3CHO]

Positive C20H20O4N Jatrorrhizine (Jiang et al.,2012)

−1.415 0.4 4.5

20 38.05 336.12192[M]+

321.09985 [M−CH3],308.12854 [M−CO],292.09726 [M− CH3CHO]

Positive C20H18O4N Epiberberine (Wang et al.,2014; Jiang et al., 2012)

−1.115 2 0.1

21 38.27 320.09055[M]+

292.09720 [M−CO],290.08163 [M−CH2O],277.07358 [M−CH2O−CH],262.08658 [M−CH2O−CO]

Positive C19H14O4N Coptisine (Huo et al., 2016;Jiang et al., 2012)

−1.184 0.9 0.4

22 38.69 338.13745[M]+

321.09985 [M−CH3],308.12854 [M−CO]

Positive C20H20O4N Columbamine (Huo et al.,2016; Jiang et al., 2012)

−1.235 0.3 4.8

(continued on next page)


121

Table 1 (continued)



F (%)

23 38.97 549.15906[M−H]−

417.11942 [M−H−C5H8O4]−,297.07706 [M−H−C9H16O8]−

255.06639 [M−H−C11H18O9]−

Negative C26H30O13 Liquiritin apioside (Yanget al., 2017)

−0.907 0.1 9.1

551.17291[M+H]+

No Positive −3.007

24 39.20 597.17755[M+H]+

289.0691 [M+H−C6H10O5−C6H10O4]+,195.0641 [M+H−C6H10O5−C6H10O4] +

Positive C27H32O15 Eriocitrin/Neoeriocitrin (Yuet al., 2016)

−3.874 0 0.9

595.16500[M−H]−

577.15649 [M−H−H2O]−,459.11496 [M−H−C8H8O2]−,287.05661 [M−H−C12H20O9]−,235.02534 [M−H−C16H24O9]−

Negative −0.767 0 1.2

25 39.79 595.16187[M+H]+

No Positive C27H30O15 Vicenin-2 (Ye et al., 2014) −3.877 0 0.04

26 40.13 417.11777[M−H]−

255.06630 [M−H−C6H10O5]− Negative C21H22O9 Liquiritin (Yang et al., 2017) −0.239 1 62.8

27 41.58 322.10593[M]+

307.08401 [M−CH3],294.11298 [M−CO],279.08914 [M−CO−CH3],251.08330 [M−2CO−CH3]

Positive C19H15NO4 Berberrubine (Yang et al.,2017; Jiang et al., 2012)

−1.454 233 98.9

28 41.92 352.15295[M]+

337.13129 [M−CH3]+,322.10751 [M−CH3−CH3]+,308.12860 [M−CH3−H−CO]+,294.10699 [M−CH3−CH3−CO]+

Positive C21H22O4N Palmatine isomer (Chen et al.,2008)

−1.315 2 0.2

29 42.39 193.04855[M+H]+

178.02589 [M+H−CH3]+,165.05452 [M+H−CO]+,149.05956 [M+H−CO2]+,133.02840 [M+H−CH3−HCOO]+

Positive C10H8O4 Scopoletin (Yu et al., 2016;Duan et al., 2014)

−0.985 153 99.4

191.03427[M−H]−

176.01135 [M−H−CH3]−,146.93845 [M−H− C2H4OH]−,102.94865 [M−H− C2H4OH−CH3CHO]−

Negative 0.385

30 44.79 352.15268[M]+

337.13126 [M−CH3],322.10760 [M−CH3−CH3],308.12857 [M− CH3−H−CO]

Positive C21H22O4N Palmatine (Chen et al., 2008;Sun et al., 2014)

−1.655 2 0.2

31 45.23 336.12149[M]+

321.09998 [M−CH3]+,308.12625 [M−CO]+,292.09738 [M−CH3−H−CO]+,278.08234 [M−CH3−CH3−CO]+

Positive C20H18O4N Berberine (Huo et al., 2016;Jiang et al., 2012)

−1.695 1 0.1

32 46.02 273.07471[M+H]+

179.03391 [M+H−C6H6O] +,153.01828 [M+H −C8H8O] +,147.04417 [M+H −C6H6O3] +

Positive C15H12O5 Naringenin isomer −1.040 99 98.4

271.05930[M−H]−


33 46.11 581.18359[M+H]+

273.07452 [M+H−C6H10O5−C6H10O4]+,153.0176 [C7H5O]+

Positive C27H32O14 Naringin (Yu et al., 2016; Yeet al., 2014)

−2.582 0 5.1

579.17017[M−H]−

459.11551 [M−H−C8H8O]−,339.07263 [M−H−C12H6O5]−,313.07251 [M−H−C10H18O8]−,271.06213 [M−H−C12H20O9]−,235.02556 [M−H−C16H24O8]−

Negative −0.662

34 46.54 417.11798[M−H]−

255.06702 [M−H−C6H10O5]−,211.07689 [M−H−C6H10O5−CO2]−

Negative C21H22O9 Isoliquiritin (Yang et al.,2017)

−0.029 1 59.3

419.13168[M+H]+


35 47.89 609.18079[M−H]−

459.11380 [M−H−C9H10O2]−,301.07190 [M−H−C12H20O9]−,286.04858 [M−H−C12H20O9−CH3]−,242.05872[M−H−C12H20O9−CH3−CH3CHO]−

Negative C28H34O15 Hesperidin (Yu et al., 2016;Ye et al., 2014)

−0.607 0 3.6

611.19360[M+H]+

449.14163 [M+H−C6H10O5]+,303.08472 [M+H−C6H10O5−C6H10O4]+,177.05367 [C10H9O3]+

Positive −3.447

36 50.12 350.13702[M+H]+

335.11530 [M+H−CH3]+,306.11276 [M+H−CH3CHO]+

Positive C21H19NO4 Dihydrochelerythrine (Jianget al., 2012 et al., )

−1.665 242 67.7

37 50.23 303.08499[M+H]+

285.07584 [M+H−H2O]+,177.05464 [M+H−C6H6O3]+,153.01822 [M+H−C9H10O2]+

Positive C16H14O6 Isomer of Hesperetin (Yeet al., 2014)

−1.325 101 98.5

301.07007[M−H]−

286.0485 [M−H−CH3]−,283.0610 [M−H−H2O]−,257.0819 [M−H−CO2]−,242.0585 [M−H−CO2−CH3]−,

Negative −0.355



122

Table 1 (continued)



F (%)

38 50.27 611.19397[M+H]+

449.1423 [M+H−C6H10O5]+,303.0851 [M+H−C6H10O5−C6H10O4]+,177.0538 [M+H−C6H10O5−C6H10O4−C6H6O3]+,153.0176 [C7H5O]+

Positive C28H34O15 Neohesperidin (Yu et al.,2016)

−3.077 0 5.3

609.18079[M−H]−

489.14163 [M−H−C4H8O4]−,343.08331 [M−H−C10H18O8]−,301.07260 [M−H−C12H20O9]−

Negative −0.917

39 53.09 465.13635[M+H]+

No Positive C22H24O11 Hesperetin-7-O-rutinoside (Yuet al., 2016)

−2.358 0 3.5

463.12170[M−H]−


40 53.76 549.15771[M−H]−

No Negative C26H30O13 Isoliquiritin apioside (Yang,et al., 2017)

−2.557 0 3.7

551.17230[M+H]+


41 56.55 417.11731[M−H]−

255.06625 [M−H−C6H10O5]−,135.00903 [M−H−C14H18O6]−

Negative C21H22O9 Liquiritin isomer/ Isoliquiritinisomer

−0.699 1 62.8

419.13095[M+H]+


42 57.53 301.10297[M+H]+

283.09375 [M+H−H2O]+,139.03886 [M+H−C6H10O5]+

Positive C17H16O5 Cnidilin (Duan et al., 2014) −4.080 243 71.3

43 63.24 255.06516[M−H]−

135.00871 [M−H− C8H8O]−,119.05034 [M−H− C7H4O3]−

Negative C15H12O4 Liquiritigenin (Zhou et al.,2004; Yang et al., 2017)

−0.165 174 99.2

257.07938[M+H]+

242.05717 [M+H−CH3]+,239.07011 [M+H−H2O]+,211.07524 [M+H−HCOOH]+,147.04395 [M+H−C6H6O2]+,137.32027 [M+H−C8H8O]+

Positive −1.455

44 70.14 281.13820[M−H]−

263.1288 [M−H−H2O]−,237.1493 [M−H−CO2]−,219.1390 [M−H−H2O−CO2]−,193.1599 [M−H−2CO2]−

Negative C15H22O5 Artemisinin (Zhou et al.,2012)

−0.140 239 99.4

283.15234[M+H]+


45 73.63 273.07413[M+H]+

179.03380 [M+H−C6H6O]+,153.0182 [M+H−C8H8O]+,147.0441 [M+H−C6H6O3]+

Positive C15H12O5 Naringenin (Yu et al., 2016) −1.560 99 98.4

271.06003[M−H]−

177.0193 [M−H−C6H6O]−,151.00362 [M−H−C8H8O]−

Negative −0.070

46 75.67 303.08444[M+H]+

No Positive C16H14O6 Hesperetin (Yu et al., 2016; Yeet al., 2014)

−1.815 101 98.5

301.07068[M−H]−

286.04803 [M−H−CH3]−,283.06073 [M−H−H2O]−,257.08157 [M−H−CO2]−,242.05815 [M−CH3COO]−,199.03973 [M−H−C4H6O3]−,125.02442 [M−H−C10H8O3]−

Negative −0.295

47 77.45 355.14938[M+H]+

337.14020 [M+H−H2O]+,219.09627 [M+H− C8H8O2]+,193.11952 [M+H−C9H6O3]+,185.02063 [M+H−C10H18O2]+

Positive C21H22O5 Xanthohumol/Isoxanthohumol (Zhang et al.,2007)

−4.620 90 193 91.9 83.2

48 77.68 359.07562[M−H]−

344.05347 [M−H−CH3]− Negative C18H16O8 Arcapillin −0.524 11 99

361.08975[M+H]+

346.06793 [M+H−CH3]+,328.05756 [M+H−CH3−H2O]+,311.05484 [M+H−CH3−H2O−OH]+

Positive −2.044

49 78.55 255.06525[M−H]−

211.07675 [M−H−CO2]−,135.00894 [M−H−C8H8O]−,119.05062 [M−H−C7H4O3]−

Negative C15H12O4 Isoliquiritigenin (Zhou et al.,2004; Yang et al., 2017)

0.065 131 99.2

257.07938[M+H]+

242.05711 [M+H−CH3]+,239.07004 [M+H−H2O]+,211.07521 [M+H−HCOOH]+,163.03879 [M+H−C6H6O]+,147.04391 [M+H−C6H6O2]+,137.02322 [M+H−C8H8O]+

Positive −1.425

50 79.00 821.39307[M−H]−

351.05792 [M−H−C30H46O4]− Negative C42H62O16 Glycyrrhizin (Zhou et al.,2004; Yang et al., 2017)

−2.800 0 0.00001

51 79.60 267.06531[M−H]−

252.04251 [M−H−CH3]− Negative C16H12O4 Formononetin (Zhang et al.,2007)

0.125 191 87.2

269.07925[M+H]+

254.05716 [M+H−CH3]+,237.05437 [M+H−CH3−OH]+,107.04895 [M+H−C9H6O3]+

Positive -1.585



123

Table 1 (continued)



F (%)

52 81.28 367.11722[M−H]−

352.0952 [M−H−CH3]−,335.0923 [M−H−CH3−OH]−,309.04034 [M−H−C4H10]−,298.04834 [M−H−C5H9]−,283.02460 [M−H−C6H12]−

Negative C21H20O6 Glycycoumarin (Zhou et al.,2004; Li et al., 2011)

−0.395 141 82.1

369.13095[M+H]+


53 82.05 255.06506[M−H]−

211.07584 [M−H−CO2]−,135.00848 [M−H−C8H8O]−

Negative C15H12O4 Liquiritigenin isomer/Isoliquiritigenin isomer

−0.125 174 99.2

257.07932[M+H]+


54 84.08 455.20330[M+H]+

No Positive C26H30O7 Kushenol N/Obacunone (Yuet al., 2016; Zhang et al.,2007; Duan et al., 2014)

−3.0901 26 86.9

453.18936[M−H]−

435.1840 [M−H−H2O]−,421.16571 [M−H−CH4O]−,275.16519 [M−H−C9H6O4]−,177.01933 [M−H−C17H24O3]−,

Negative 2.181 240 6.5

55 85.00 403.13690[M+H]+

388.11526 [M+H−CH3]+,373.09186 [M+H−2CH3]+,342.10953 [M+H−C2H5O2]+

Positive C21H22O8 Nobiletin (Yu et al., 2016; Yeet al., 2014)

−1.844 230 99.3

56 85.07 439.20956[M+H]+

303.15900 [M+H−C8H8O2]+,179.03377 [M+H−C17H24O2]+

Positive C26H30O6 Kuraridine (Zhang et al.,2007)

−1.955 2 63.8

437.19501[M−H]−

419.18609 [M−H−H2O]−,275.16562 [M−H−C9H6O3]−,161.02435 [M−H−C17H24O3]−

Negative 0.125

57 85.61 367.11740[M−H]−

352.09555 [M−H−CH3]−,339.12366 [M−H−CO]−,309.04071 [M−H−C4H10]−,297.04111 [M−H−C5H10]−,284.03311 [M−H−C6H11]−

Negative C21H20O6 Isoglycycoumarin (Zhou et al.,2004)

−0.215 158 50.5

369.13092[M+H]+


58 87.76 485.3229 [M+H]+

No Positive C30H44O5 Dehydrotumulosic acid (Xiaet al., 2014)

−3.271 0.2 1.9

483.30804[M−H]−

465.3005 [M−H−H2O]−,439.3206 [M−H−CO2]−,387.25345 [M−H−C6H8O]−,301.21713 [M−H−C10H14O3]−,169.08687 [M−H−C21H30O2]−

Negative −2.391

59 87.87 353.10153[M−H]−

338.07883 [M−H−CH3]−,298.04773 [M−H−C4H7]−,219.06618 [M−H−C8H6O2]−

Negative C20H18O6 Licoisoflavone A (Li et al.,2011)

−0.435 20 90.1

355.11530[M+H]+


60 88.68 373.12628[M+H]+

358.10468 [M+H−CH3]+,343.08133 [M+H−C2H6]+,312.09918 [M+H−C2H5O2]+

Positive C20H20O7 Tangeretin (Ye et al., 2014) −1.899 235 96.2

61 89.57 437.15842[M−H]−

419.14938 [M−H−H2O]−,409.16571 [M−H−CO]−,393.17026 [M−H−CO2]−,299.12885 [M−H−C7H6O3]−,287.12903 [M−H−C8H6O3]−,261.14984 [M−H−C9H4O4]−

Negative C25H26O7 Kushenol C −1.060 2 80.3

439.17200[M+H]+


62 90.26 423.17911[M−H]−

262.15286 [M−H−C9H6O3]−,161.02475 [M−H−C16H22O3]−

Negative C25H28O6 Kushenol F (Ma et al., 2003) −1.105 8 58.2

425.19348[M+H]+

301.07022 [M+H−C9H16]+,289.14325 [M+H−C8H8O2]+,165.01801 [M+H−C9H16−C8H8O2]+

Positive −2.265

63 90.46 365.10184[M−H]−

350.07935 [M−H−CH3]−,307.02502 [M−H−CH4H10]−,295.02518 [M−H−C5H10]−,282.01715 [M−H−C6H11]−

Negative C21H18O6 Glycyrol −0.125 177 21.4

367.11548[M+H]+


64 91.53 389.12067[M+H]+

No Positive C20H20O8 5-Demethylnobiletin (Yeet al., 2014)

−2.424 118 97.5

65 95.32 485.32300[M+H]+

No Positive C30H44O5 3-epi-dehydrotumulosic acid −3.181 0.2 1.9

483.30826[M−H]−

465.29993 [M−H−H2O]−,439.32104 [M−H−CO2]−,337.25323 [M−H−C6H10O4]−

Negative −2.241



124

and oxygen to the body (Hool, 2005; Brown et al., 2014). Here, the hubnodes contributed to the regulation of energy production and nutritionmetabolism, such as Oxidative phosphorylation (involved hubs:NDUFA1∼13, NDUFAB1∼10, NDUFC1∼2, NDUFS1∼8, NDUFV1∼3and SDHB), Glycolysis/Gluconeogenesis (involved hubs: ADH1A∼B,ADH5∼7, ALDH3A1, ALDH1B1, ALDH1A3, ALDH3B2, ALDH9A1,ALDH3A2, LDHA, LDHB, LDHC, ALDH7A1, PKM), Glutathione meta-bolism (involved hubs: GSTO2, GSTA5, GGT1, GPX1∼4, GSR,GSTA1∼4, GSTM1∼5, GSTP1, GSTT1, GSTK1, MGST1∼3, GSTO1),Pyruvate metabolism (involved hubs: LDHD, ALDH1B1, ALDH9A1,ALDH3A2, ACACA, ACACB, LDHA, LDHB, LDHC, MDH1, MDH2,ALDH7A1, PKM), indicating that XSNC may ensure a sufficient oxygen

and nutrient supply for the body, which may be very helpful to thepatients' outcome.

Moreover, ischemic preconditioning for repairing myocardiumprovides an enticing option to reduce the severity of arrhythmias(Su et al., 2015). Growing evidence show that cardioprotection withischemic preconditioning may be related to the enhanced expression ofangiogenic growth factors (Wang et al., 2011; Keshava et al., 2001).Interestingly, our data found that the hubs of XSNC putative target-arrhythmia related gene interaction network were also frequently in-volved into VEGF signaling pathway (involved hubs: AKT1, KDR,MAPK1, MAPK11, MAPK14, MAPK3, PIK3CB, PIK3R1, PIK3R3, PRKCA,PRKCB, PRKCG, PTGS2, RAF1, SRC, VEGFA) and Vascular smooth

Table 1 (continued)



F (%)

66 96.07 439.20911[M+H]+

421.20038 [M+H−H2O]+,315.08585 [M+H−C9H16]+,303.15869 [M+H−C8H8O2]+,297.07565 [M+H−C9H18O]+,179.03354 [M+H−C17H24O2]+

Positive C26H30O6 Isokurarinone (Zhang et al.,2007)

−2.405 2 63.8

437.19513[M−H]−

275.16562 [M−H−C9H6O3]−,161.02446 [M−H−C9H6O3−C8H18]−

Negative −0.615

67 96.18 423.17999[M−H]−

261.14975 [M−H−C9H6O3]−,161.02496 [M−H−C16H22O3]−

Negative C25H28O6 Kushenol E (Guo et al., 2011) −0.225 8 51.3

425.19339[M+H]+


68 96.64 439.21078[M−H]−

275.16513 [M−H−C8H4O4]−,163.04041 [M−H−C8H4O4−C8H16]−

Negative C25H28O7 Kushenol L/ Kushenol X (Guoet al., 2011)

−0.545 22 17 77.9 82.4

69 97.81 485.36254[M−H]−

441.33661 [M−H−CO2]+,423.32635 [M−H−CO2−H2O]+,337.25305 [M−H−C7H16O3]+

Negative C31H50O4 Tumulosic acid (Xia et al.,2014)

−4.265 0 11

70 97.91 407.18433[M−H]−

261.14935 [M−H−C6H10O4]− Negative C25H28O5 Kushenol A (Zhang et al.,2007)

−0.970 3 69.6

409.19833[M+H]+


71 101.76 485.32330[M+H]+

No Positive C30H44O5 Poria acid B (Kang et al.,2014)

−2.881 0 52.8

483.30820[M−H]−


72 101.93 437.19473[M−H]−

419.18680 [M−H−H2O]−,275.16556 [M−H−C6H10O5]−

Negative C26H30O6 Kurarinone (Zhang et al.,2007)

−1.135 9 85.2

439.20901[M+H]+


Papp: apparent permeability coefficient at the indicated concentrationsin the basolateral-to-apical (B-A)direction across a Caco-2 cell monolayer.

Fig. 3. Functional modules of the hub interaction network. The hub nodes were divided into three functional modules, including modulation of cardiac sympatho-vagal balance,regulation of energy production and metabolism, as well as angiogenesis and vascular circulation.


125

muscle contraction (involved hubs: ADCY1, ADORA2A, ADRA1D,ADRA1B, ADRA1A, AGTR1, EDNRA, AVPR1A, PRKCA, PRKCB, PRKCD,PRKCE, PRKCG, MAPK1, MAPK3, RAF1, CACNA1C, CACNA1D,CALM1), implying that XSNC may reduce malignant ventricular ar-rhythmia and improve cardiac repair via activation of angiogenesisthrough several proangiogenic factors.

Identification of the potential Q-markers of XSNC acting on arrhythmia

To identify the potential Q-markers of XSNC acting on arrhythmia,we calculated four topological features (degree, node-betweeness, clo-seness and k-core value) of each node in the hub network, and chose 72nodes as major hubs since their topological feature values were higherthan the corresponding median cutoff points (Supplementary Table S4).Among them, 63 were XSNC putative targets and considered as thecandidate targets of this prescript. As shown in Fig. 4, the chemicalcompounds containing in herbs of XSNC may exert the followingtherapeutic effects through regulating the corresponding candidatetargets and pathways: Neuro-modulation by involving Neuroactive li-gand-receptor interaction and Gap junction; Anti-inflammation via Tcell receptor signaling pathway, NOD-like receptor signaling pathway,Toll-like receptor signaling pathway and B cell receptor signalingpathway; Promoting angiogenesis and improving vascular circulationby targeting VEGF signaling pathway, regulating vascular smoothmuscle contraction and vasoconstriction; Supplying energy and nutri-tion for the body via involving oxidative phosphorylation. Especially,inflammatory changes in cardiac tissues have been reported to be as-sociated with the occurrence and exacerbation of arrhythmia(Lewek et al., 2014). The inflammatory background of the arrhythmiahas also been supported by the curable effect of the anti-inflammatorytreatment (Klein et al., 2000). Our data mentioned above found thatXSNC candidate targets were frequently involved into inflammatorysignaling pathways, implying the potential roles of XSNC in reversingthe inflammatory changes during arrhythmia.

In addition, we found that several chemical compounds containingherbs of XSNC, including scopoletin (compound 29), liquiritigenin

(compound 43), naringenin (compound 45), formononetin (compound51), nobiletin (compound 55), tangeretin (compound 60), 5-de-methylnobiletin (compound 64), kushenol E (compound 67) and kur-arinone (compound 72), were all predicted to hit the XSNC candidatetargets (CHRM1, CYSLTR1, DRD2, DRD4, HTR1A, HTR2A, MAPK14,NFKB1, P2RY12, PPARA, PTGS2 and TNF). As shown in Fig. 4 andTable 2, 5-Demethylnobiletin, naringenin, nobiletin, scopoletin andtangeretin obtained from Citrus aurantium L. may be significantly as-sociated with Neuroactive ligand-receptor interaction, Toll-like re-ceptor signaling pathway, VEGF signaling pathway and Regulation ofvascular circulation; Candidate targets of formononetin, kurarinone andkushenol E, containing Sophora flavescens Ait. may be importantcomponents in various pathways related to neuro-modulation, in-flammation, vascular circulation and energy production; Scopoletinfrom Artemisia annua L. and liquiritigenin from Glycyrrhiza uralensisFisch. were also play a role in reversing the pathological changes duringarrhythmia via regulating the corresponding candidate targets. Moreimportantly, although the contents of these chemical compounds inXSNC were relative low, they all behaved good drug-likeness (Papp≥7 × 106 cm/s and F ≥ 40%) according to our ADME prediction, im-plying that they may be easily to be absorbed into the body. Therefore,considering the bioactivities and the pharmacological relevance, weidentified scopoletin, liquiritigenin, naringenin, formononetin, nobi-letin, tangeretin, 5-demethylnobiletin, kushenol E and kurarinone asthe potential Q-markers of XSNC against arrhythmia.

Moreover, two chemical compounds identified in Coptis chinensisFranch.–palmatine (Compound 30) and berberine (Compound 31) mayfunctionally exert the anti-inflammation effects and improved vascularcirculation through regulating their candidate targets (HTR2A,MAPK14, PTGS2 and NFKB1, Figs. 4 and 2). Consistently, Coptis chi-nensis Franch. as the principle herb of XSNC, has been indicated to exerta key role in treating heart fire and have broad spectrum antibioticproperties. We also found that they were the top two chemical com-pounds with highest contents in XSNC (Table 1). These findings implythat palmatine and berberine may be the major chemical compounds inCoptis chinensis Franch., although our ADME prediction found that they

Fig. 4. Illustration of associations among herbs, chemical constituents, network targets, involved pathways and the corresponding therapeutic effects of XSNC. Note: green nodes refer toherbs containing in XSNC; blue nodes refer to chemical constituents containing in each herb of XSNC; yellow nodes refer to XSNC candidate targets; blue nodes with red markers refer topotential Q-markers of XSNC; yellow nodes with red markers refer to XSNC candidate targets directly regulated by potential Q-markers of XSNC. (For interpretation of the references tocolour in this figure legend, the reader is referred to the web version of this article.)


126

had poor oral absorption rates (Papp 1×106 cm/s and 21×106 cm/s,respectively) and OB (F 0.1 % and 0.2 %, respectively). More im-portantly, Huang et al. (1989) firstly reported the antiarrhythmic ef-fects of berberine on ischemic ventricular arrhythmia;Wang et al. (2012) revealed that the ability of berberine to protectdiabetic rats against cardiac arrhythmias might make it possible to be aprospective therapeutic agent in clinical management of cardiac diseasesecondary to diabetes. Taken together, we considered palmatine andberberine to be the potential Q-markers of XSNC against arrhythmiadue to their high content and crucial therapeutic effects.

Conclusions

These findings suggest that the IP-based approach combiningUHPLC-LTQ-Orbitrap, in silico ADME prediction and network targetanalysis may be efficient to identify potential Q-markers of TCM pre-scriptions. Our data showed that berberine, palmatine, scopoletin, li-quiritigenin, naringenin, formononetin, nobiletin, tangeretin, 5-de-methylnobiletin, kushenol E and kurarinone may function as thepotential Q-markers for qualitative evaluation of XSNC.

Acknowledgments

Financial support was provided by the 973 Program of China (No.2015CB554406), National Key Technology R&D Program of China (No.2011BAI07B08) and National Natural Science Foundation of China (No.81473414, 81673834).

Conflict of interest-

The authors declare that there is no conflict of interests regardingthe publication of this paper.

Authors' contribution

GR and ZX carried out the experiments and drafted the manuscript.ZY, XH and MS conceived of the study, participated in its design andcoordination, as well as helped to draft the manuscript. The other au-thors participated in the design of the study and performed the statis-tical analysis. All authors read and approved the final manuscript.

Supplementary materials

Supplementary material associated with this article can be found, inthe online version, at doi:10.1016/j.phymed.2018.01.019.

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Table 2Information of potential Q-markers of XSNC against arrhythmia.

Herbs Potential Q-markers CACO-2(×10−6)

F (%) XSNC candidate targets Associated-functions

Coptis chinensis Franch. Berberine 1 0.1 HTR2A//MAPK14/PTGS2 Anti-inflammation/Improving vascularcirculation

Coptis chinensis Franch. Palmatine 2 0.2 NFKB1 Anti-inflammationArtemisia annua L./ Citrus

aurantium L.Scopoletin 153 99.4 CHRM1/CYSLTR1/NFKB1/TNF/DRD2/

DRD4/HTR1A/HTR2ANeuro-modulation/Anti-inflammation/Promoting angiogenesis/Improving vascularcirculation

Glycyrrhiza uralensis Fisch. Liquiritigenin 174 99.2 CHRM1/CYSLTR1/NFKB1/TNF Neuro-modulation/Anti-inflammation/Improving vascular circulation

Citrus aurantium L. Naringenin 99 98.4 CHRM1/CYSLTR1/NFKB1/TNF Neuro-modulation/Anti-inflammation/Improving vascular circulation

Sophora flavescens Ait. Formononetin 191 87.2 CHRM1/CYSLTR1/NFKB1/TNF Neuro-modulation/Anti-inflammation/Improving vascular circulation

Citrus aurantium L. Nobiletin 230 99.3 CHRM1/CYSLTR1/NFKB1/TNF Neuro-modulation/Anti-inflammation/Improving vascular circulation

Citrus aurantium L. Tangeretin 235 96.2 CHRM1/CYSLTR1/NFKB1/TNF Neuro-modulation/Anti-inflammation/Improving vascular circulation

Citrus aurantium L. 5-Demethylnobiletin 118 97.5 CHRM1/CYSLTR1/NFKB1/TNF Neuro-modulation/Anti-inflammation/Improving vascular circulation

Sophora flavescens Ait. Kushenol E 8 51.3 CHRM1/CYSLTR1/NFKB1/TNF/P2RY12/PPARA

Neuro-modulation/Anti-inflammation/Improving vascular circulation/Energy production

Sophora flavescens Ait. Kurarinone 9 85.2 CHRM1/CYSLTR1/NFKB1/TNF/ PTGS2 Neuro-modulation/Anti-inflammation/Improving vascular circulation


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