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Systems Pharmacological Approach to the Effect of Bulsu-san Promoting Parturition.

1. Introduction

The name of Bulsu-san (BSS) originated from its therapeutic effects that help to promote easy labor as if being touched by merciful Buddha's hand [1]. BSS is composed of Angelicae Sinensis Radix (Danggui, DG) and Cnidium officinale Makino (Cheongung, CG), which is one of the most commonly used herb pairs in Traditional Medicine of East Asia and the usual component ratio is 2:3 (CG:DG) or 1:1 [2]. BSS is widely used in women's medicine in East Asia; its recognized therapeutic effects are as follows: removal of impure blood, blood making, easy parturition, acceleration of labor, elimination of dead fetus or placenta, amelioration of pain, nourishing blood, and promoting blood circulation [3].

What is more, recent experimental research on the CGDG herb pair indicated that they affect the nourishment of blood [4], activate blood circulation, and prevent blood stasis [5]. In addition, the CG-DG herb pair showed significant inhibitory effects on the proliferation and protein synthesis of vascular smooth muscle cells [6]. It was suggested BSS could affect the activities of Akt kinase and eNOS by increasing intracellular Ca + and reducing ROS levels [7] and regulate menstruation and provide relief from pain by enabling the management of uterine smooth muscle contractions [8]. Although BSS has therapeutic effects on various pathological symptoms in pregnant or childbearing aged women, this research focused on the molecular mechanisms and impact of BSS on easing parturition and the acceleration of labor.

In terms of parturition onset, numerous studies have described the complex hormone interactions between estrogen, progesterone, oxytocin, corticosteroid, and prostaglandin. Among these, corticotrophin releasing hormone (CRH) is regarded as a trigger that initiates the labor [9]. The placenta releases substantial amounts of CRH, which stimulates the pituitary glands of both mother and fetus to secrete adreno-corticotropin hormone [10]. This in turn induces the release of estrogen precursor, which is converted into estrogen by the placenta that induces smooth muscle contraction [10]. Additionally, dilatation of cervical connective tissue and smooth muscle is induced by the following changes: a shift from progesterone to estrogen dominance, increased responsiveness to oxytocin via the upregulation of myometrial oxytocin receptor, increased prostaglandins synthesis in uterus, increased myometrial gap junction formation, decreased nitric oxide activity, and increased influx of calcium into myocyte [11].

The hypothesis of this study was that BSS may promote the positive-feedback of hormone loops as well as a series of myometrial and cervical changes to ease parturition and safely accelerate labor. A network based in silico approach was used to identify the effect of BSS on parturition related systems and the aim of this study was to elucidate the effect of BSS on the parturition by system-level analysis. The workflow of the network pharmacological study is summarized in Figure 1.

2. Material and Methods

2.1. Identification of Active Compounds. Compounds in CG and DG were identified using a phytochemical database that is the Traditional Chinese Medicine Systems Pharmacology (TCMSP, http://ibts.hkbu.edu.hk/LSP/tcmsp.php). We applied parameters related to absorption, distribution, metabolism, and excretion (ADME), namely, human drug-likeness (DL) [12], oral bioavailability (OB) [13], and Caco2 permeability (Caco-2) to screen the Potential active compounds in BSS [14].

2.1.1. Drug-Likeness Evaluation. DL helps filter "drug-like" compounds in oriental herbs, as DL represents a qualitative concept for valuations based on how "drug-like" a prospective compound is [15]. Accordingly, a high DL may lead to a greater possibility of therapeutic success, and compounds with a higher DL value are more likely to possess certain biological properties [16]. The calculations of DL in TCMSP database were based on Tanimoto coefficient formula [17] as follows:

F(A,B) = A x B/[A.sup.2] + [B.sup.2] - A x B, (1)

where A represents the molecular parameters of herbal compounds and B is the average molecular parameters of all compounds in the Drugbank database (http://www.drugbank.ca/) [18]. In the present study, we excluded compounds with a DL of <0.08. Other previous researches of herbal formulas set a higher threshold in the range of0.1 to 0.18. However, we found out that most compounds of DG have low DL. In detail, only 36 compounds of 125 in DG show higher or equal DL value than 0.08. For this reason, this study sets a lower threshold of DL than other previous researches to see the most potential targets of BSS.

2.1.2. Oral Bioavailability (OB) Prediction. OB is defined as the ratio of active compounds' absorption into the systemic circulation, which represents the convergence of the ADME process [13]. OB values are dependent on drug dissolution in the gastrointestinal (GI) tract and hepatic and intestinal first-pass metabolism, as well as on intestinal membrane permeation, which makes it a major pharmacokinetic parameter for drug evaluations [16]. In this study, the OB threshold was set as [greater than or equal to] 15%.

2.1.3. Caco-2 Permeability Screening. Caco-2 permeability is used to predict the absorption of an orally administered drug [14]. Surface absorptivity of the small intestine is maximized with the presence of villi and microvilli, for this reason most orally administered drug absorption occurs in the small intestine [19]. Moreover, the movement of orally administered drugs across the intestinal epithelial barrier determines the rate and extent of human absorption and ultimately affects drug bioavailability [20]. In the present study, compounds with OB, DL and Caco-2 values of greater than 15%, 0.08, and >-0.4, respectively, were regarded as active compounds and subjected to further analysis.

2.1.4. Lipinski's Rule (LR) Screening. In addition, the screening standard used was defined based on Lipinski's rule (LR), which identifies druggable compounds as having molecular weight (MW) of [less than or equal to] 500 Da (MW [less than or equal to] 500), chemical composition with [less than or equal to] 5 hydrogen-bond donors, [less than or equal to] 10 hydrogen-bond acceptors, and an octanol-water partition coefficient, AlogP of [less than or equal to] 5 [21]. AlogP can be used to estimate local hydrophobicity, to produce molecular hydrophobicity maps, and to evaluate hydrophobic interactions in protein-ligand complexes [22]. Hdon and Hacc are the number of possible hydrogen-bond donors and acceptors, and the hydrogen-bonding capacity of a drug solute is recognized as a crucial determinant of permeability; moreover high hydrogen-bonding potential is often related to low permeability and absorption [23]. Eventually, in the present study, we selected active compounds satisfying the following criteria: OB [greater than or equal to] 15%; DL [greater than or equal to] 0.08; Caco-2 [greater than or equal to] -0.4; MW [less than or equal to] 500; H-bond donors [less than or equal to] 5; H-bond acceptors [less than or equal to] 10; AlogP [less than or equal to] 5.

2.2. Target Fishing. Aside from filtering active compounds, we also sought to identify the molecular targets of these active compounds. Compound-target interaction profiles were established based on a systematic prediction of multiple drug-target interactions tool which employs random forest (RF) and support vector machine (SVM) methods and integrates chemical, genomic, and pharmacological information for drug targeting and discovery on a large scale [24]. Compound-target interactions satisfying SVM score [greater than or equal to] 0.8 and RF score [greater than or equal to] 0.7 were selected for further study. Additionally, filtered compound-target interaction profile mapping was performed using the UniProt database (http://www.uniprot.org/) [25].

2.3. Gene Ontology (GO) Analysis. Biological process (BP) of gene ontology (GO) analysis was employed to determine the biological properties of target genes [26]. GO annotation indicates the possibility of direct statistical analysis on gene function information. In this research, GO BP terms with P values < 0.01 were employed and the data was collected using the DAVID 6.8 Gene Functional Classification Tool (http://david.abcc.ncifcrf.gov/).

2.4. Network Construction and Analysis. In order to understand the multiscale interactions between the active compounds of BSS and targets, two types of networks were built: (1) the herb-compound-target network (H-C-T network), in which nodes represent either compounds, target genes, or herbs and edges indicate herb-compound-target connections; and (2) the target-pathway network (T-P network) to extract the pathways from KEGG database (http://www.genome.jp/kegg/), and the terms highly associated with parturition with P values < 0.05 were selected as the related pathways of targets in this work. Related targets were mapped onto relevant pathways, which resulted in the T-P network. Both networks were generated in Cytoscape 3.5.1, an open-source biological network visualization and data integration software package [27].

2.5. Target Organ Location Map. Tissue-specific patterns of mRNA expression can indicate important associations with biological events or gene functions [28]. To explore the beneficial effects of BSS during parturition, it is important that the tissue mRNA expression profiles of target genes at the organ level be known [29]. The target organ location map was built according to the Dataset: GeneAtlas U133A, gcrma (http://biogps.org). BioGPS database provides expression data acquired by direct measurements of gene expression obtained by microarrays analysis [30]. First, the mRNA expression patterns of each target gene in 176 parts of organ tissues were obtained. Second, average values were calculated for each gene. Third, frequency of above average mRNA expression tissue organs was inspected. Forth, based on the result from the third step and parturition mechanism theory, mRNA expression data of relevant organ tissues were extracted and categorized into 6 groups, namely, uterus and/or uterus corpus, fetus and/or placenta, hypothalamus and/or pituitary, smooth muscle, and whole blood.

3. Results

3.1. Identification of Active Compounds. 314 compounds of BSS were identified, including 189 molecules in CG and 125 in DG (as shown in Supplementary Material Table S1 in Supplementary Material available online at https://doi.org/10.1155/ 2017/7236436) and active compounds met the criteria OB [greater than or equal to] 15%, Caco-2 [greater than or equal to] -0.4, and DL [greater than or equal to] 0.08, as well as the standards of Lipinski's rule (LR) (as shown in Table 1). In detail, 60 active compounds were initially chosen, but 8 compounds were present in both herbs, namely, 3-butylidene7-hydroxyphthalide, adenine, BdPh, beta-selinene, palmitic acid, senkyunolide-C, senkyunolide-D, and senkyunolideE, and 14 had no target protein information and were thus excluded from the list of active compounds, whereas 27 compounds with lower ADME properties than above thresholds were included, which were reported to be related to oxytocin. In total, 65 active compounds were filtered.

Although ligustilide and ferulic acid have a DL of <0.08, both were included in this study. Since ligustilide (C12, DL = 0.07, OB = 53.72, Caco-2 = 1.3) was reported to be the main compound of DG in uterine contraction [31], and ferulic acid (C42, DL = 0.06, OB = 54.97, Caco-2 = 0.53) has been reported to be useful for the treatment of vascular diseases [6, 32] and blood deficiency syndrome [33] in China and to suppress inflammatory responses and tumor progression [34]. Some other compounds also have been shown experimentally to have various biological activities; for example, crysophanol (C42, DL = 0.21, OB = 18.64, Caco-2 = 0.62) can be used to treat menorrhagia and thrombocytopenia [35]. Perlolyrine (C52, DL = 0.27, OB = 65.95, Caco-2 = 0.88) was confirmed to have a protective effect on injured human umbilical vein endothelial cells [36], and myricanone (C48, DL = 0.51, OB = 57.61, Caco-2 = 0.67) was found to best inhibit mouse skin tumor progression [37].

3.2. Target Fishing. The 65 active compounds interact with 185 target proteins, as shown in Table 2; in other words, on average, each compound on average interacts with 2.85 target proteins. This result confirms the polypharmacological character of oriental medicine and demonstrates the synergistic effects of multiple compounds on multiple targets [38]. Different compounds in CG and DG can directly affect common targets, for example, the target protein "calmodulin (CALM1)" interacts with crysophanol from CG and coniferyl ferulate from DG at the same time, which implies the synergetic or cumulative effects of herbal medicine.

3.3. GO Analysis. 397 biological process terms with P values of <0.01 were sorted using the functional annotation chart of the DAVID 6.8 Gene Functional Classification Tool, based on 185 filtered target genes, and P values were adjusted using the Benjamini-Hochberg method. 30 enriched GO BP terms extracted by P value and gene counts are displayed in Figure 2. It is meaningful that most of the target genes are significantly related to the various BP involved in parturition. For instance, 30 extracted GO BP terms include "MAPK signaling pathways," "steroid hormone mediated signaling pathway," "response to glucocorticoid," "response to estradiol," and "positive regulation of ERK1 and ERK2 cascade." "MAPK signaling pathways" were reported to be activated in human uterine cervical ripening during parturition [39]. "Steroid hormone mediated signaling pathway" is highly related to parturition process as estrogen and progesterone play important roles in pregnancy and parturition, and estrogen induceS the principal stimulatory myometrial contractility [40]. Also, estradiol takes key place in parturition process [41]. It was identified that increased ERK activation is observed at the onset of labor, and it promotes myometrial contractility and development of parturition [42,43]. To sum up, the target genes of BSS are highly associated with the biological process (BP) of parturition.

3.4. Network Construction and Analysis. Network analysis is an efficient tool for visualizing and understanding multiple targeted drug actions and demonstrates drug actions within the context of the whole genome [44,45]. For a better insight of therapeutic impacts, H-C-T and T-P networks were constructed and displayed in Figures 3 and 4, respectively. In the H-C-T network, nodes represent herb names, compounds, and targets. Also in the T-P network, circular nodes represent targets and triangle nodes represent pathways. Besides node size is relative to the degree and edges show interactions between nodes.

H-C-T network confirmed that there were 739 interactions between 185 targets and 65 active compounds of CG and DG: oleic acid (C48, degree = 42) with the highest number of interactions with targets, followed by succinic acid (C63, degree = 40) and stigmasterol (C62, degree = 37). It shows that single molecules target multiple receptors [46]. Also, some compounds from CG and DG were found to share common targets. Likewise, prostaglandin G/H synthase 2 (PTGS2, degree = 56) displayed the most affinitive connections with compounds, followed by gamma-aminobutyric acid receptor subunit alpha-1 (GABRA1, degree = 48), prostaglandin G/H synthase 1 (PTGS1, degree = 37), and muscarinic acetylcholine receptor M1 (CHRM1, degree = 37). Except for C60 (PLA2G1B, degree = 1), the rest of the 64 active compounds are connected with more than one target; likewise, 73 (39.5%) target genes out of 185 interacted with more than one compound. This result demonstrates the multicompounds and multitarget properties of herbal compounds and there was a report that compounds with multiple targets could have greater therapeutic efficacy [47].

In addition, the top 40 pathways were extracted based on gene counts and P value (<0.05), and P value was adjusted by Benjamini-Hochberg method. T-P network using relevant targets of herbal compounds is demonstrated in Figure 4. There were 485 interactions between the top 40 pathways and 135 of 185 target genes. "Metabolic pathways" (degree = 49) and "neuroactive ligand-receptor interaction pathway" (degree = 32) had the highest and the second highest numbers of connections with the targets, followed by "calcium signaling" (degree = 21), "cAMP signaling pathway" (degree = 17), and "cGMP PKG signaling pathway" (degree = 15). These are compelling results that parturition processes are the complex hormone interactions and it is well known that calcium signals within the myometrium are pivotal for uterine contractions [48]. In the same manner, some target genes demonstrated higher degree centrality with top 40 pathways, namely, PI3-kinase subunit gamma (PIK3CG, degree = 23), cAMP-dependent protein kinase catalytic subunit alpha (PRKACA, degree = 20), protein kinase C beta type (PRKCB, degree = 18), and calmodulin (CALM1, degree = 11). We can confirm the same result in the previous researches. For instance, PI3-kinase subunit gamma plays the key role in regulating cAMP, calcium cycling, and beta-adrenergic signaling [49]. Moreover, during the labor, calmodulin-calcium complex activates myosin light-chain kinase, which causes the generation of ATPase activity; eventually, uterine contraction is promoted [50].

H-C-T network explains the multitarget, multicompounds properties and accumulates effect of herbal medicines and T-P network shows that target genes of BSS are highly related to the pathway associated with parturition process.

3.5. Target Organ Location Map. It is important to confirm the tissue mRNA expression profiles of the target genes at the organ level to identify the effects of BSS on parturition. Since there was no mRNA expression information in BioGPS of muscarinic acetylcholine receptor M1 (CHRM1), putative beta-glucuronidase-like protein SMA3 (GUSBP1), and retinol-binding protein 2 (RBP2), excluding these 3 targets from 185 filtered targets, totally 182 genes mRNA expression profiles were analyzed in this study. There were 519 interactions between target genes and organ locations. The networks of target genes tissue mRNA expression profiles and compounds of BSS are shown in Figure 5.

As a result, 159 of 182 target genes displayed beyond average mRNA expression in relevant organ tissues, such as uterus and/or uterus corpus, fetus and/or placenta, hypothalamus and/or pituitary, smoothmuscle, and whole blood.The rest of 23 genes of 182 targets did not display above average mRNA expression in above organ tissues, for example, gamma-aminobutyric acid receptor subunit alpha-6 (GABRA6) and coagulation factor X (F10).

Nevertheless, most genes of 159 demonstrated high expression patterns in several organs of parturition related tissues at the same time. In detail, 60 genes showed most significant mRNA expression in the uterus and/or uterus corpus group, 130 for placenta and/or fetus, 86 for hypothalamus and/or pituitary, 82 for smooth muscle, 80 for pituitary, and 81 for whole blood. Besides, 30 of 159 genes showed expression in all of 6 groups. For instance, muscarinic acetylcholine receptor M2 (CHRM2), neuronal acetylcholine receptor subunit [alpha]-2 (CHRNA2), gamma-aminobutyric acid receptor subunit alpha-3 (GABRA3), NO synthase, inducible (NOS2), cGMP-inhibited 3'?,5'-cyclic phosphodiesterase A (PDE3A), and sodium-dependent dopamine transporter (SLC6A3) recorded beyond average mRNA expression in all six groups. Furthermore, 79% of targets were expressed in two or more organ tissues, which suggests that those organs and target genes of BSS are closely correlated.

4. Discussion

In this study, network pharmacology method with DL, OB, Caco-2, and LR evaluation, multiple drug-target prediction, network analysis, and relevant organ location mapping was used to explain the targets of BSS in relation to the parturition process. There is no denying that network based analysis is powerful approach for identifying the actions of multitargeting herbal medicines at the systems level and our study shows target genes of BSS are strongly connected to parturition related pathways, biological processes, and organs. It was confirmed that 98% of the active compounds of BSS were interacted with more than two targets and 39.5% of the targets related to more than one compound. The synergetic multitarget properties of BSS were visualized, but further discussion about differentiated drug action based on degree centrality and simultaneous targeting effect of more than one compound is required [51]. Also, detailed potential pathways of BSS should be explored deeply in the future.

Similar findings were identified in a few RCT researches in China that using BSS in induction of labor can reduce the delivery time, the amount of bleeding, and the residual rate of placenta [52, 53]. In addition, BSS targets six genes of GABA receptor and NOS, which was reported to be related oxytocin neurons at the time of parturition in rats [54]. Also, BSS targets NOS and NO (nitric oxide) which are involved in the regulation of uterine contractility during pregnancy and is a key factor for the onset of labor [55], and iNOS (inducible nitric oxide synthase) can be upregulated accordantly by similar inflammatory mediators during ripening [11].

In fact, rather than DG, Angelicae Gigantis Radix (Danggwi, AGR) grows naturally in Korea; for that reason, the combination of AGR and CG is commonly used as BSS in Korea. Instead, DG is named as Chinese Danggwi for accurate classification in Korea. Several studies have shown AGR is differs from DG in terms of its main active constituents and genetic form. AGR is mainly composed of water soluble polysaccharide but coumarin, which is liposoluble including nodakenin (1), peucedanone (2), marmesin (3), decursinol (4), 7-hydroxy-6-(2R-hydroxy-3-methylbut3-enyl) coumarin (5), demethylsuberosin (6), decursin (7), decursinol angelate (8), and isoimperatorin (9) [56]. Of these, decursin and its isomer decursinol angelate have been reported to be the active compounds in AGR [57]. It was identified in the experimental studies that AGR and DG act via different mechanisms in the cardiovascular, central nervous system, and anticancer activity but both have similar pharmacological effects [57]. Since the compositions of DG and AGR differ, further study on BSS with AGR is required. Currently, BSS is commonly prescribed to treat cerebra vascular and cardiovascular diseases in China [33], but, in Korea, BSS is widely applied in obstetrics.

The similarity between cervical ripening during parturition and inflammatory reaction has been pointed out in earlier studies; this has been attributed to the induction of leukocyte migration into tissue, thus promoting cervical remodeling and parturition by estrogen [58]. Further study is needed in terms of the effect of BSS on inflammatory reactions and parturition.

Furthermore, the CG-DG herb pair has other names, such as, Gunggui-tang (weight ratios of 2: 3 or 1: 1), Ogeum-san (1:1), Iphyo-san (1:1), and Sinmyo Bulsu-san (1:2), those are prepared at different weight ratios [3]. Accordingly, weight ratio should be determined based on considerations of targeted symptoms for relevant clinical applications.

5. Conclusion

This study results show that Bulsu-san (BSS) is highly connected to the parturition related pathways, biological processes, and organs. Most compounds in BSS work together with multiple target genes in a synergetic way, and this was confirmed using herb-compound-target network and target-pathway network analysis. The mRNA expression of relevant target genes of BSS was elevated significantly in parturition related organ tissues, such as those of the uterus, placenta, fetus, hypothalamus, and pituitary gland.

This study employed the network analytical methods to show the multicompound, multitarget properties of BSS. The results not only support clinical applications of BSS on easing childbirth but also suggest the related target genes and pathways of BSS on promoting parturition according to a systems-level in silico analytic approach. However, detailed mechanisms and other functions of BSS should be discussed further.

https://doi.org/10.1155/2017/7236436

Conflicts of Interest

The authors declare that there are no conflicts of interest.

Acknowledgments

This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (NRF-2015R1D1A1A01059994).

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Su Yeon Suh and Won G. An

Department of Pharmacology, School of Korean Medicine, Pusan National University, Yangsan, Gyeongnam 50612, Republic of Korea

Correspondence should be addressed to Won G. An; wgan@pusan.ac.kr

Received 28 July 2017; Accepted 25 September 2017; Published 29 October 2017

Academic Editor: Gihyun Lee

Caption: Figure 1: The workflow: the network pharmacological approach of Bulsu-san (BSS), namely, active compounds screening, target fishing, network analysis, and relevant organ location mapping was performed in this study.

Caption: Figure 3: H-C-T network: herb-compound-target (H-C-T) network demonstrated multicompound, multitarget property of BSS. In this network, red and blue nodes represent herbs, green nodes show compounds, and pink nodes indicate targets and node size is relative to the degree and edges demonstrate interactions between nodes.

Caption: Figure 4: T-P network: in target-pathway (T-P) network, circular nodes represent compounds and triangles indicate pathways. Node size is relative to the degree and edges demonstrate interactions between nodes.

Caption: Figure 5: Target organ location map: it shows that tissue-specific patterns of mRNA expression are highly active in relative organs of parturition process such as uterus, fetus, placenta, hypothalamus, pituitary, and smooth muscle. Yellow nodes show compounds and pink nodes indicate targets and node size is relative to the degree and edges demonstrate interactions between nodes.
Table 1: 65 Potential active compounds of BSS (compound with
* was present in both herbs).

ID               Active compounds             OB (%)   Caco-2

C1              ()-alpha-Terpineol             46.3     1.28
C2               ()-Aromadendrene             55.74     1.81
C3               ()-Terpinen-4-ol             81.41     1.36
C4              (+)-alpha-Funebrene           52.87     1.79
C5                   (+)-Ledol                16.96     1.43
C6          (1R,5R,7S)-4,7-Dimethyl-7-        16.23     1.86
           (4-methylpent-3-enyl)bicyclo
                 [3.1.1]hept-3-ene
C7      (1S,4aR,8aR)-1-Isopropyl-7-methyl-     19.8     1.86
            4-methylene-2,3,4a,5,6,8a-
             hexahydro-1H-naphthalene
C8           (1S,4E,8E,10R)-4,8,11,11-        21.69     1.86
        tetramethylbicyclo[8.1.0]undeca-4,
                      8-diene
C9        (3E)-3-butylidene-7-hydroxy-2-      42.17     1.03
                 benzofuran-1-one
C10             (L)-alpha-Terpineol            48.8     1.39
C11                (R)-Linalool                39.8     1.33
C12               (Z)-Ligustilide             53.72     1.3
C13           1-Acetyl-beta-carboline         67.12     1.18
C14      1-beta-Ethylacrylate-7-aldehyde-     28.53     0.45
                  beta-carboline
C15        1H-Cycloprop(e)azulen-7-ol,        82.33     1.37
           decahydro-1,1,7-trimethyl-4-
        methylene-, (1aR-(1aalpha,4aalpha,
              7beta,7abeta,7balpha))-
C16                 1-Terpineol               49.83     1.24
C17      2,6-Di(phenyl)thiopyran-4-thione     69.13     1.74
C18      2-[(2S,5S,6S)-6,10-Dimethylspiro     37.62     1.44
          [4.5]dec-9-en-2-yl]propan-2-ol
C19 *     3-Butylidene-7-hydroxyphthalide     62.68      1
C20       4,7-Dihydroxy-3-butylphthalide      106.09    0.69
C21                 49070_FLUKA               85.51     1.29
C22         4-Hydroxy-3-butylphthalide        70.31     0.9
C23                 58870_FLUKA               49.01     1.82
C24 *                 Adenine                 62.81     -0.3
C25                     ADO                   15.98    -1.56
C26               alpha-Cubebene              16.73     1.83
C27               alpha-Selinene              31.81     1.82
C28            Aromadendrene oxide 2           65.1     1.56
C29 *                  BdPh                   42.44     1.32
C30               beta-Chamigrene             31.99     1.82
C31 *              beta-Selinene              24.39     1.83
C32                beta-Cubebene              32.16     1.82
C33                  Cadinene                 17.12     1.88
C34                Caffeic acid               25.76     0.21
C35                   Carotol                 149.03    1.46
C36                   Cedrene                 51.14     1.82
C37                Chuanxiongol               22.19     0.94
C38               cis-Thujopsene              56.43     1.84
C39             Coniferyl ferulate             4.54     0.71
C40                 Crysophanol               18.64     0.62
C41                     FA                    68.96     -1.5
C42             Ferulic acid (CIS)            54.97     0.53
C43      InChI=1/C15H24/c1-10-7-8-15-9-12     55.56     1.79
           (10)14(3,4)13(15)6-5-11(15)2/
             h7,11-13H,5-6,8- 9H2,1-4H
C44              L-Bornyl acetate             65.52     1.29
C45              Methyl palmitate             18.09     1.37
C46                 Myricanone                 40.6     0.67
C47               Nicotinic acid              47.65     0.34
C48                 Oleic acid                33.13     1.17
C49 *              Palmitic acid               19.3     1.09
C50                 Perlolyrine               65.95     0.88
C51                     PLO                   14.07     0.69
C52                 Scopoletol                27.77     0.71
C53               Senkyunolide A              26.56     1.3
C54               Senkyunolide G              39.52     0.63
C55 *             Senkyunolide-C               46.8     0.87
C56 *             Senkyunolide-D              79.13     0.12
C57 *             Senkyunolide-E               34.4     0.55
C58               Senkyunolide-K              61.75     0.52
C59                Sinapic acid               64.15     0.48
C60                Sphingomyelin               0.31    -0.46
C61                Stearic acid               17.83     1.15
C62                Stigmasterol               43.83     1.44
C63                Succinic acid              29.62    -0.44
C64                   Sucrose                  7.17    -2.89
C65                Wallichilide               42.31     0.82

ID               Active compounds             DL     Herb

C1              ()-alpha-Terpineol            0.03    DG
C2               ()-Aromadendrene             0.1     CG
C3               ()-Terpinen-4-ol             0.03    CG
C4              (+)-alpha-Funebrene           0.1     CG
C5                   (+)-Ledol                0.12    DG
C6          (1R,5R,7S)-4,7-Dimethyl-7-        0.09    CG
           (4-methylpent-3-enyl)bicyclo
                 [3.1.1]hept-3-ene
C7      (1S,4aR,8aR)-1-Isopropyl-7-methyl-    0.08    DG
            4-methylene-2,3,4a,5,6,8a-
             hexahydro-1H-naphthalene
C8           (1S,4E,8E,10R)-4,8,11,11-        0.08    CG
        tetramethylbicyclo[8.1.0]undeca-4,
                      8-diene
C9        (3E)-3-butylidene-7-hydroxy-2-      0.08    DG
                 benzofuran-1-one
C10             (L)-alpha-Terpineol           0.03    CG
C11                (R)-Linalool               0.02    CG
C12               (Z)-Ligustilide             0.07    CG
C13           1-Acetyl-beta-carboline         0.13    CG
C14      1-beta-Ethylacrylate-7-aldehyde-     0.31    CG
                  beta-carboline
C15        1H-Cycloprop(e)azulen-7-ol,        0.12    CG
           decahydro-1,1,7-trimethyl-4-
        methylene-, (1aR-(1aalpha,4aalpha,
              7beta,7abeta,7balpha))-
C16                 1-Terpineol               0.03    CG
C17      2,6-Di(phenyl)thiopyran-4-thione     0.15    DG
C18      2-[(2S,5S,6S)-6,10-Dimethylspiro     0.09    CG
          [4.5]dec-9-en-2-yl]propan-2-ol
C19 *     3-Butylidene-7-hydroxyphthalide     0.08   CG&DG
C20       4,7-Dihydroxy-3-butylphthalide      0.1     CG
C21                 49070_FLUKA               0.12    CG
C22         4-Hydroxy-3-butylphthalide        0.08    CG
C23                 58870_FLUKA               0.1     CG
C24 *                 Adenine                 0.03   CG&DG
C25                     ADO                   0.18    CG
C26               alpha-Cubebene              0.11    CG
C27               alpha-Selinene              0.1     CG
C28            Aromadendrene oxide 2          0.14    CG
C29 *                  BdPh                   0.07   CG&DG
C30               beta-Chamigrene             0.08    DG
C31 *              beta-Selinene              0.08   CG&DG
C32                beta-Cubebene              0.11    CG
C33                  Cadinene                 0.08    DG
C34                Caffeic acid               0.05    CG
C35                   Carotol                 0.09    CG
C36                   Cedrene                 0.11    CG
C37                Chuanxiongol               0.1     CG
C38               cis-Thujopsene              0.12    DG
C39             Coniferyl ferulate            0.39    DG
C40                 Crysophanol               0.21    CG
C41                     FA                    0.71    CG
C42             Ferulic acid (CIS)            0.06    DG
C43      InChI=1/C15H24/c1-10-7-8-15-9-12     0.1     DG
           (10)14(3,4)13(15)6-5-11(15)2/
             h7,11-13H,5-6,8- 9H2,1-4H
C44              L-Bornyl acetate             0.08    CG
C45              Methyl palmitate             0.12    CG
C46                 Myricanone                0.51    CG
C47               Nicotinic acid              0.02    DG
C48                 Oleic acid                0.14    CG
C49 *              Palmitic acid              0.1    CG&DG
C50                 Perlolyrine               0.27    CG
C51                     PLO                   0.43    CG
C52                 Scopoletol                0.08    DG
C53               Senkyunolide A              0.07    CG
C54               Senkyunolide G              0.08    CG
C55 *             Senkyunolide-C              0.08   CG&DG
C56 *             Senkyunolide-D              0.1    CG&DG
C57 *             Senkyunolide-E              0.08   CG&DG
C58               Senkyunolide-K              0.08    CG
C59                Sinapic acid               0.08    CG
C60                Sphingomyelin              0.51    DG
C61                Stearic acid               0.14    CG
C62                Stigmasterol               0.76    DG
C63                Succinic acid              0.01    DG
C64                   Sucrose                 0.23    CG
C65                Wallichilide               0.71    CG

Table 2: Related targets of potential compounds in BSS.

UniProt                      Target name
ID

P80404     4-aminobutyrate aminotransferase, mitochondrial
P33121           Long-chain-fatty-acid--CoA ligase 1
O60488           Long-chain-fatty-acid--CoA ligase 4
P00813                   Adenosine deaminase
P07327                Alcohol dehydrogenase 1A
P00325                Alcohol dehydrogenase 1B
P00326                Alcohol dehydrogenase 1C
P29274                 Adenosine A2a receptor
P35348              Alpha-1A adrenergic receptor
P35368              Alpha-1B adrenergic receptor
P25100              Alpha-1D adrenergic receptor
P08913              Alpha-2A adrenergic receptor
P18089              Alpha-2B adrenergic receptor
P18825              Alpha-2C adrenergic receptor
P08588               Beta-1 adrenergic receptor
P07550               Beta-2 adrenergic receptor
Q5SY84               Adenylosuccinate synthetase
P21549           Serine- -pyruvate aminotransferase
O43865            Putative adenosylhomocysteinase 2
P15121                    Aldose reductase
P13716          Delta-aminolevulinic acid dehydratase
P51649         Succinate semialdehyde dehydrogenase,
                            mitochondrial
P04745                     Alpha-amylase 1
P04746                Pancreatic alpha-amylase
P04114                  Apolipoprotein B-100
P10275                    Androgen receptor
P06576        ATP synthase subunit beta, mitochondrial
P06276                     Cholinesterase
P10415                Apoptosis regulator Bcl-2
Q06187               Tyrosine-protein kinase BTK
P00915                  Carbonic anhydrase I
P62158                       Calmodulin
P42574                        Caspase-3
P04040                        Catalase
P06307                     Cholecystokinin
P20248                        Cyclin-A2
P30305              M-phase inducer phosphatase 2
P24941             Cell division protein kinase 2
P11597           Cholesteryl ester transfer protein
P28329               Choline O-acetyltransferase
O14757          Serine/threonine-protein kinase Chk1
P36222               Chitinase-3-like protein 1
P11229          Muscarinic acetylcholine receptor M1
P08172          Muscarinic acetylcholine receptor M2
P20309          Muscarinic acetylcholine receptor M3
Q15822     Neuronal acetylcholine receptor subunit alpha-2
P36544    Neuronal acetylcholine receptor protein, alpha-7 chain
Q99966          Cbp/p300-interacting transactivator 1
P02452                Collagen alpha-1(I) chain
Q02388               Collagen alpha-1(VII) chain
P17538                   Chymotrypsinogen B
P07339                       Cathepsin D
P04798                   Cytochrome P450 1A1
P05177                   Cytochrome P450 1A2
Q9ULA0                 Aspartyl aminopeptidase
P27487                 Dipeptidyl peptidase IV
P21728                  Dopamine D1 receptor
P14416                 D(2) dopamine receptor
P25101                      Endothelin-1
Q07075                 Glutamyl aminopeptidase
Q6UWV6             Ectonucleotide pyrophosphatase/
                  phosphodiesterase family member 7
P04626         Receptor tyrosine-protein kinase erbB-2
P03372                    Estrogen receptor
Q92731                 Estrogen receptor beta
P00742                  Coagulation factor Xa
P00734                        Thrombin
P08709                 Coagulation factor VII
P07148            Fatty acid-binding protein, liver
P01100                  Proto-oncogene c-Fos
P15408                  Fos-related antigen 2
P35575                  Glucose-6-phosphatase
P14867    Gamma-aminobutyric acid receptor subunit alpha-1
P47869    Gamma-aminobutyric-acid receptor alpha-2 subunit
P34903    Gamma-aminobutyric-acid receptor alpha-3 subunit
P48169    Gamma-aminobutyric-acid receptor subunit alpha-4
P31644    Gamma-aminobutyric-acid receptor alpha-5 subunit
Q16445    Gamma-aminobutyric-acid receptor subunit alpha-6
P17677                      Neuromodulin
P47871                        Glucagon
P14136             Glial fibrillary acidic protein
Q2TU84              Growth-inhibiting protein 18
P23415             Glycine receptor alpha-1 chain
P00367        Glutamate dehydrogenase 1, mitochondrial
P17174         Aspartate aminotransferase, cytoplasmic
P00505        Aspartate aminotransferase, mitochondrial
P42262                  Glutamate receptor 2
P49841             Glycogen synthase kinase-3 beta
Q15486      Putative beta-glucuronidase-like protein SMA3
P19367                      Hexokinase-1
P04035     3-hydroxy-3-methylglutaryl-coenzyme A reductase
P00738                       Haptoglobin
O14756                     Oxidoreductase
P08238                Heat shock protein HSP 90
P28223             5-hydroxytryptamine 2A receptor
P01344              Insulin-like growth factor II
P01857                Ig gamma-1 chain C region
P22301                     Interleukin-10
P05231                      Interleukin-6
P01308                         Insulin
Q12809       Potassium voltage-gated channel subfamily
                             H member 2
Q12791      Calcium-activated potassium channel subunit
                               alpha 1
P35968      Vascular endothelial growth factor receptor 2
P09848               Lactase-phlorizin hydrolase
Q32P28                 Prolyl 3-hydroxylase 1
Q8IVL6                 Prolyl 3-hydroxylase 3
P06858                   Lipoprotein lipase
P09960                Leukotriene A-4 hydrolase
P21397           Amine oxidase [flavin-containing] A
P27338           Amine oxidase [flavin-containing] B
Q16539           Mitogen-activated protein kinase 14
Q00266     S-adenosylmethionine synthetase isoform type-1
P31153     S-adenosylmethionine synthetase isoform type-2
P23368        NAD-dependent malic enzyme, mitochondrial
Q16798       NADP-dependent malic enzyme, mitochondrial
Q3SYC2           2-acylglycerol O-acyltransferase 2
P05164                     Myeloperoxidase
Q15788             Nuclear receptor coactivator 1
Q15596             Nuclear receptor coactivator 2
P29475              Nitric-oxide synthase, brain
P35228            Nitric oxide synthase, inducible
P29474           Nitric oxide synthase, endothelial
P16083              NRH dehydrogenase [quinone] 2
Q14994      Nuclear receptor subfamily 1 group I member 3
P04150                 Glucocorticoid receptor
P08235               Mineralocorticoid receptor
Q16620            BDNF/NT-3 growth factors receptor
P04181        Ornithine aminotransferase, mitochondrial
P00480      Ornithine carbamoyltransferase, mitochondrial
Q9BYC2    Succinyl-CoA:3-ketoacid-coenzyme A transferase 2,
                            mitochondrial
O15460          Prolyl 4-hydroxylase subunit alpha-2
P49585        Choline-phosphate cytidylyltransferase A
Q14432     CGMP-inhibited 3',5'-cyclic phosphodiesterase A
O00330      Pyruvate dehydrogenase protein X component,
                            mitochondrial
P52945          Pancreas/duodenum homeobox protein 1
P06401                  Progesterone receptor
P48736     Phosphatidylinositol-4,5-bisphosphate 3-kinase
                  catalytic subunit, gamma isoform
P11309        Proto-oncogene serine/threonine-protein
                            kinase Pim-1
P61925      cAMP-dependent protein kinase inhibitor alpha
P14618             Pyruvate kinase isozymes M1/M2
P04054                    Phospholipase A2
P00749          Urokinase-type plasminogen activator
P00747                       Plasminogen
P00491             Purine nucleoside phosphorylase
P27169            Serum paraoxonase/arylesterase 1
Q07869    Peroxisome proliferator-activated receptor alpha
Q03181    Peroxisome proliferator-activated receptor delta
P37231    Peroxisome proliferator activated receptor gamma
Q9UBK2    Peroxisome proliferator-activated receptor gamma
                         coactivator 1-alpha
P17612          mRNA of PKA Catalytic Subunit C-alpha
P05771               Protein kinase C beta type
P35030                        Trypsin-3
P60484        Phosphatidylinositol-3,4,5-trisphosphate
             3-phosphatase and dual-specificity protein
                          phosphatase PTEN
P43115          Prostaglandin E2 receptor EP3 subtype
P23219              Prostaglandin G/H synthase 1
P35354              Prostaglandin G/H synthase 2
P18031         mRNA of Protein-tyrosine phosphatase,
                         non-receptor type 1
P10082                       Peptide YY
P63000       Ras-related C3 botulinum toxin substrate 1
P50120                Retinol-binding protein 2
P08100                        Rhodopsin
P19793            Retinoic acid receptor RXR-alpha
O00767                   Acyl-CoA desaturase
Q14524       Sodium channel protein type 5 subunit alpha
P31040    Succinate dehydrogenase [ubiquinone] flavoprotein
                       subunit, mitochondrial
P16109                       P-selectin
P05121            Plasminogen activator inhibitor 1
P14410             Sucrase-isomaltase, intestinal
O76082            Solute carrier family 22 member 5
Q9UBX3           Mitochondrial dicarboxylate carrier
P11168      Solute carrier family 2, facilitated glucose
                        transporter member 2
P23975       Sodium-dependent noradrenaline transporter
Q01959          Sodium-dependent dopamine transporter
P31645         Sodium-dependent serotonin transporter
P35610               Sterol O-acyltransferase 1
P00441              Superoxide dismutase [Cu-Zn]
P08047                Transcription factor Sp1
P12931       Proto-oncogene tyrosine-protein kinase SRC
P36956       Sterol regulatory element-binding protein 1
Q12772       Sterol regulatory element-binding protein 2
Q9P2R7     Succinyl-CoA ligase [ADP-forming] beta-chain,
                            mitochondrial
Q99973             Telomerase protein component 1
P01375                  Tumor necrosis factor
Q16881           Thioredoxin reductase, cytoplasmic
P55851           Mitochondrial uncoupling protein 2
P55916           Mitochondrial uncoupling protein 3

UniProt   Gene Name
ID

P80404      ABAT
P33121      ACSL1
O60488      ACSL4
P00813       ADA
P07327      ADH1A
P00325      ADH1B
P00326      ADH1C
P29274     ADORA2A
P35348     ADRA1A
P35368     ADRA1B
P25100     ADRA1D
P08913     ADRA2A
P18089     ADRA2B
P18825     ADRA2C
P08588      ADRB1
P07550      ADRB2
Q5SY84      ADSS
P21549      AGXT
O43865     AHCYL1
P15121     AKR1B1
P13716      ALAD
P51649     ALDH5A1
P04745      AMY1A
P04746      AMY2A
P04114      APOB
P10275       AR
P06576      ATP5B
P06276      BCHE
P10415      BCL2
Q06187       BTK
P00915       CA1
P62158      CALM1
P42574      CASP3
P04040       CAT
P06307       CCK
P20248      CCNA2
P30305     CDC25B
P24941      CDK2
P11597      CETP
P28329      CHAT
O14757      CHEK1
P36222     CHI3L1
P11229      CHRM1
P08172      CHRM2
P20309      CHRM3
Q15822     CHRNA2
P36544     CHRNA7
Q99966     CITED1
P02452     COL1A1
Q02388     COL7A1
P17538      CTRB1
P07339      CTSD
P04798     CYP1A1
P05177     CYP1A2
Q9ULA0      DNPEP
P27487      DPP4
P21728      DRD1
P14416      DRD2
P25101      EDNRA
Q07075      ENPEP
Q6UWV6      ENPP7
P04626      ERBB2
P03372      ESR1
Q92731      ESR2
P00742       F10
P00734       F2
P08709       F7
P07148      FABP1
P01100       FOS
P15408      FOSL2
P35575      G6PC
P14867     GABRA1
P47869     GABRA2
P34903     GABRA3
P48169     GABRA4
P31644     GABRA5
Q16445     GABRA6
P17677      GAP43
P47871      GCGR
P14136      GFAP
Q2TU84      GIG18
P23415      GLRA1
P00367      GLUD1
P17174      GOT1
P00505      GOT2
P42262      GRIA2
P49841      GSK3B
Q15486     GUSBP1
P19367       HK1
P04035      HMGCR
P00738       HP
O14756     HSD17B6
P08238    HSP90AB1
P28223      HTR2A
P01344      IGF2
P01857      IGHG1
P22301      IL10
P05231       IL6
P01308       INS
Q12809      KCNH2
Q12791     KCNMA1
P35968       KDR
P09848       LCT
Q32P28     LEPRE1
Q8IVL6     LEPREL2
P06858       LPL
P09960      LTA4H
P21397      MAOA
P27338      MAOB
Q16539     MAPK14
Q00266      MAT1A
P31153      MAT2A
P23368       ME2
Q16798       ME3
Q3SYC2     MOGAT2
P05164       MPO
Q15788      NCOA1
Q15596      NCOA2
P29475      NOS1
P35228      NOS2
P29474      NOS3
P16083      NQO2
Q14994      NR1I3
P04150      NR3C1
P08235      NR3C2
Q16620      NTRK2
P04181       OAT
P00480       OTC
Q9BYC2      OXCT2
O15460      P4HA2
P49585     PCYT1A
Q14432      PDE3A
O00330      PDHX
P52945      PDX1
P06401       PGR
P48736     PIK3CG
P11309      PIM1
P61925      PKIA
P14618      PKM2
P04054     PLA2G1B
P00749      PLAU
P00747       PLG
P00491       PNP
P27169      PON1
Q07869      PPARA
Q03181      PPARD
P37231      PPARG
Q9UBK2    PPARGC1A
P17612     PRKACA
P05771      PRKCB
P35030      PRSS3
P60484      PTEN
P43115     PTGER3
P23219      PTGS1
P35354      PTGS2
P18031      PTPN1
P10082       PYY
P63000      RAC1
P50120      RBP2
P08100       RHO
P19793      RXRA
O00767       SCD
Q14524      SCN5A
P31040      SDHA
P16109      SELP
P05121    SERPINE1
P14410       SI
O76082     SLC22A5
Q9UBX3    SLC25A10
P11168     SLC2A2
P23975     SLC6A2
Q01959     SLC6A3
P31645     SLC6A4
P35610      SOAT1
P00441      SOD1
P08047       SP1
P12931       SRC
P36956     SREBF1
Q12772     SREBF2
Q9P2R7     SUCLA2
Q99973      TEP1
P01375       TNF
Q16881     TXNRD1
P55851      UCP2
P55916      UCP3

Figure 2: GO analysis: 30 enriched biological process (BP) of gene
ontology (GO) terms sorted by P value < 0.01 and gene counts are
displayed. The 7-axis represents enriched biological process (BP)
terms for the target genes, and the %-axis shows gene counts
and--log 10 (P value).

GO Analysis                                     Count   -log 10
                                                        (P-value)

response to drug                                  34      23.3
response to hypoxia                               20      13.6
positive regulation of transcription from RNA
polymerase II promoter                            28       5.3
aging                                             18      11.7
oxidation-reduction process                       22       5.8
positive regulation of cell proliferation         20       6.2
cell proliferation                                18       6.4
positive regulation of transcription,
DNA-templated                                     19       5.0
response to glucocorticoid                        12      10.1
cell-cell signaling                               15       6.2
adenylate cyclase-activating adrenergic
receptor signaling pathway                         9      11.0
transcription initiation from RNA polymerase
II promoter                                       12       6.2
response to estradiol                             10       6.3
lipid metabolic process                           11       5.1
response to lipopolysaccharide                    11       5.0
positive regulation of ERK1 and ERK2 cascade      11       4.7
platelet activation                               10       5.4
cholesterol metabolic process                      9       6.2
response to cold                                   8       7.0
response to nicotine                               8       7.0
positive regulation of MAPK cascade                9       5.6
positive regulation of protein kinase B
signaling                                          9       5.5
response to hydrogen peroxide                      8       6.0
response to ethanol                                9       4.8
steroid hormone mediated signaling pathway         8       5.6
cellular response to lipopolysaccharide            9       4.6
glucose transport                                  7       5.9
response to nutrient                               8       4.9
circadian rhythm                                   8       4.8
response to fatty acid                             6       6.1

Note: Table made from bar graph.
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Title Annotation:Research Article
Author:Suh, Su Yeon; An, Won G.
Publication:Evidence - Based Complementary and Alternative Medicine
Date:Jan 1, 2017
Words:8365
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