Analyzing the effective compounds, potential targets and diseases of Jianpi Jiedu recipe based on network pharmacology and function validation of cytobiology

Xue-Qing Hu，Ru Jia，Xuan Liu ，Qin Song，Hui-Rong Zhu , Qi Li,，Qing Ji,*，Yu Feng,*

1Cancer Institute, Shuguang Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai 201203, China. 2Department of Medical Oncology, Shuguang Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai 201203, China

#These authors contributed equally to this work

Introduction

Long-term clinical practice has evidenced the therapeutic efficacy of the Chinese herbal prescription Jianpi-Jiedu Recipe (JPJDR) on kinds of tumors. JPJDR is an experienced prescription and consists of Huangqi(Astragalus membranaceus (Fisch.) Bunge.) 24g,Dangshen (Codonopsis pilosula (Franch.) Nannf.) 12g,Baizhu (Atractylodes macrocephala Koidz.) 12g,Yiyiren (Root of Coix lacryma-jobi L.var.mayuen(Roman.) Stapf) 20g, Bayuezha (Fructus Akebiae Trifoliatae) 9g and Yeputaoteng (Vitis quinquangularis Rehd.) 15g. JPJDR was effective in reducing the metastasis rate and reversing drug-resistance in colorectal cancer treatment [1-2]. Chinese herbal formulae are complicated in compounds, targets and action mechanism. The emergence of databases, like Cancer HSP [3], TCMSP[4], TCMID[5], TCM-PTD[6],TCM Database@Taiwan[7] DrugBank et al[8] and development of network pharmacology [9-10] and bioinformatics [11] provide new ways to screen the potential targets and predict their function mechanism of JPJDR.

Network pharmacology was firstly proposed in 2007 by professor Hopkins, who have regarded it as a novel model for drug development [9]. Currently, network pharmacology is widely used and certain achievement has been obtained. Xu Yujie et al. applied the methods of molecular docking and computer network pharmacology to screen the active compounds of Chinese herbs for coronary heart disease treatment. His team also constructed a drug-target-disease network to investigate the regularity of traditional Chinese medicine on a complex network in the body [12]. Li Shao’s team in Tsinghua University used the network pharmacology to explain the material bases of the cold syndrome-heat syndrome, et al. [13-16]. We also have discussed the active ingredients, targets and therapeutic mechanism of Yinchenhao Decoction [17] [18] and Huangqi Decoction in inhibiting liver fibrosis [19], as well as Xiantang Decoction in alleviating inflammatory bowel disease [20]. This study aims to explore the effective active ingredients, targets, and involved pathways of JPJDR based on multiple online databases and network pharmacology to provide scientific bases for the clinical application of JPJDR.

Materials and methods

Data mining and network construction

The active compounds of JPJDR were firstly mined from online databases, including Cancer HSP(http://lsp.nwu.edu.cn/CancerHSP.php), TCMSP(http://lsp.nwsuaf.edu.cn/tcmsp.php), TCMID(http://www.megabionet.org/tcmid), TCM-PTD(http://tcm.zju.edu.cn/ptd), and TCM Database @Taiwan (http://tcm.cmu.edu.tw). Secondly, oral bioavailability (OB) value and drug-like index (DL) of each compound were derived from the TCMSP database.Thirdly, targets of those active compounds were obtained from Drugbank database(http://tcm.zju.edu.cn/ptd). Then the active compound-target network of JPJDR was constructed using Cytoscape software 3.3. The KEGG enrichment of predicted targets was analyzed using the DAVID database, including biological functions and signaling pathways. Top 10 diseases and 15 KEGG pathways with the most genes were listed in tables (P<0.05).

OB evaluation

OB value is one of the most important pharmacokinetic parameters to detect drug absorption, distribution,metabolism, and excretion. It is a key indicator for determining the bioavailability of bioactive molecules.To be more specific, the oral bioavailability refers to the relative amount and rate at which a drug is absorbed into the systemic blood circulation after oral administration. At present, the calculating method of the OB value mainly depends on the computer model OBioavail 1.1, which has been established by Wang Yonghua. In this study, OB>30% was used as a cutoff value for effective compounds.

DL evaluation

DL refers to a certain similarity between a compound and a known drug in the Drugbank database. The DL is calculated with the Tanimoto coefficient. Generally, a compound with DL>0.18 is considered to be similar to a drug in the Drugbank database.

Cell proliferation detection with cell counting kit-8(CCK-8)

Colorectal cancer LoVo cells were purchased from the Chinese Academy of Sciences in Shanghai and cultured in F12K, supplemented with 10% (v/v) heat-inactivated fetal calf serum (Gibco, USA), 1.5 g/L sodium bicarbonate (Sinopharm, China), 2 mmol/L glutamine(Sinopharm) at 37 °C in a 5% CO2 humidified atmosphere. Cells were seeded in 96-well plates at a density of 2 x 103 cells/well. When the cells were completely adherent to the plated, the completed medium was replaced with serum-free medium overnight. Ampelopsis (CAS NO: 27200-12-0) was purchased from TAUTO (China) and Quercetin (CAS NO: 117-39-5), Formononetin (CAS NO: 486-62-4),Stigmasterol (CAS NO: 83-48-7), Diosgenin (CAS NO:14144-06-0), Kaempferol (CAS NO: 520-18-3) and Isorhamnetin (CAS NO:480-19-3) from Herbputify(China) and β-sitosterol (CAS NO: S1270) and Oxymatrine (CAS NO: Y0002015) from Sigma-Aldrich(Germany) with purity>98%. They were dissolved in dimethyl sulfoxide and diluted with phosphate buffer saline (PBS). They were added at gradient concentrations (Ampelopsis: 0, 6.25, 12.5, 25, 50 100,200, 400 μmol/L; Quercetin: 0, 6.25, 12.5, 25, 50 100,200 μmol/L; other compounds: 0, 25, 50 100, 200 μmol/L). Same volume of PBS was added as the control group. Forty-eight hours later, the Cell Counting Kit-8(CCK-8, Dojindo, Japan) solution was added at a ratio of 10%. Then the plates were placed at 37 ° C for 4 hours. Finally, the absorbance was measured at 490 nm/ 630 nm (dual wavelength) using a microplate reader(Bio Tek, USA).

Results

Screening of active compounds in JPJDR

The active compounds of JPJDR were screened using the network pharmacology-related databases. Results showed that there were 109 compounds in Huangqi, 255 compounds in Dangshen, 40 compounds in Baizhu, 76 compounds in Yiyiren, 7 compounds in Yeputaoteng,and 26 compounds in Bayuezha. According to the cutoff value of OB>30% and DL>0.18, active compounds were further selected. Finally, 19, 21, 4, 9, 1 and 4 compounds in Huangqi, Dangshen, Baizhu, Yiyiren,Yeputaoteng, and Bayuezha, respectively were screened out (Supplementary Table S1).

JPJDR involved-KEGG pathways

Figure 1 Active compound-target network of JPJDR

Table 1 Key target-related diseases of JPJDR

Table 2 KEGG pathway enrichment of key targets of JPJDR

Figure 2 Effect of Ampelopsis from JPJDR on colorectal cell proliferation

Targets of JPJDR were identified according to the Drugbank database, and the active compound-target network was constructed by Cytoscape software 3.3.Initial screening results showed that those 50 compounds in JPJDR actively targeted to 437 proteins with 1275 edges. Among them, Huangqi, Dangshen,Baizhu, Yiyiren, Yeputaoteng, and Bayuezha targeted to 733, 214, 33, 48, 1 and 51 proteins, respectively (Table S2). Among them, the targets with apparent relevance to the screened compounds included PTGS2、PTGS1、MST1、NCOA2、HSP90、GABRA1、PPARG、GLDC、AR、CHRM1、ADRB2、RXRA、NOS3、NOS2、MAOB、ESR2 and so on (Figure1).

Target proteins of JPJDR closely mediated the initiation and development of cancer, metabolic disorders, cardiovascular diseases, neurological diseases,immune dysfunction et al. Cancers in colorectum,stomach, liver, lung, and esophagus were the most relevant (Table 1). The KEGG pathway analyses also showed that JPJDR mainly targeted to the PI3K/AKT signaling pathways, MAPK pathway, TNF pathway et al., which are closely related to cancer (Table 2).

Effect of a ctive c ompounds fr om J PJDR on the proliferation of colorectal cancer cells

The potential targets of active compounds from JPJDR were closely related to the occurrence and development of cancer. Network pharmacology results showed that key compounds of JPJDR included Quercetin,Formononetin, Stigmasterol, Diosgenin, β-sitosterol,Oxymatrine, Kaempferol, Isorhamnetin, Ampelopsis et al. JPJDR is mainly used in the clinic to treat patients with colorectal cancer, so we verified the effect of those 9 screened compounds on colorectal cancer cells.Results showed that among all the 9 key compounds,only Ampelopsis could inhibit the proliferation of colorectal cancer cells dose-dependently (Figure 2),while other compounds such as Quercetin, Oxymatrine and Formononetin had no significant inhibitory effect on the proliferation of LoVo cells.

Discussion

Chinese herbal formulae are generally composed of multiple herbs with complex compounds and various targets, which also make its research complicated and difficult. At present, a combination of network pharmacology and bioinformatics paved a new way to study the synergistic compounds in a formula. Active compounds and their potential targets can be mined from databases to explain the mechanisms of formulae systematically. Furthermore, formulae new roles may be discovered [21-23].

Chinese herbal Recipe JPJDR is effective on patients with colorectal cancer in the clinic. JPJDR in combined with chemotherapy can prolong the progression-free survival and overall survival of patients with metastatic colorectal cancer. The formula also improved their quality of life and reduced the chemotherapy-induced hematological adverse reactions [24]. The therapeutic mechanisms of JPJDR remain elusive due to its complicated compounds and targets. The continuous development of online databases such as Cancer HSP,TCMSP, and Network Pharmacology [9-10] and Bioinformatics [11] facilitated the research on formulae’function explanation.

In this study, a total of 50 key active compounds of JPJDR were screened, and 437 targets were predicted.Key active compounds of JPJDR include Quercetin,Formononetin, Stigmasterol, Diosgenin, β-sitosterol,Oxymatrine, Kaempferol, Isorhamnetin, and Ampelopsis. The quercetin has been found in the several herbs in JPJDR and it owns the most targets,which regulate activities of coagulation factors [25],various transcription factors [26], prostaglandin receptors et al [27]. Although network pharmacology has also predicted that quercetin targets to the most number of proteins, its inhibitory effect on proliferation of colorectal cancer cells is not obvious, while the ampelopsis in Yeputaoteng can inhibit colorectal cancer in a dose-dependent manner. Further study on its therapeutic effects on colorectal cancer-bearing mice are needed. JPJDR contains various kinds of compounds belonging to glucoside, flavone, flavonoid,sterol et al. which lays the foundation for its diverse pharmacologic action. Looking for target proteins of Chinese herbs bridges the complicated formulae with diseases. DAVID analyses demonstrated that the active compounds of JPJDR are effective on cancers, as it involves multiple cancer-related signaling pathways,like PI3K/AKT signaling pathway, MAPK signaling pathway, TNF signaling pathway et al. Interestingly,some of those pathways interacted with each other.Zhou J et al. has reported the crosstalk between MAPK/ERK and PI3K/AKT signaling pathways [28].The interaction among signaling pathways may explain the effects a formula better than that of a signal Chinese herb or a compound. Interactions among those pathways and how those active compounds cooperatively act need to be further studied.

Additionally, certain pathways participated in the initiation and development of kinds of diseases, so JPJDR is theoretically effective to treat multiple diseases. For example, MAPK signaling pathway involves in cardiovascular diseases, Alzheimer's disease,renal fibrosis et al. [29-31]. Therefore, it is rational to refer that JPJDR might be effective for those disorders.So network pharmacology is an approach to discover new therapeutic indications of a formula.

Network pharmacology is also limited in predicting potential active compounds and targets due to the incompleteness of online databases, the variation of herbal compound composition which is correlated with production area and preparation methods, unknown interaction among compounds and the individual metabolic difference. Therefore, it is necessary to verify the effects of screened active compounds and role of targeted proteins, which better benefit the clinical application of traditional Chinese medicine and disease treatment.

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