Original Article A systematic elucidation of the sanguinarine mechanism in human disease using network pharmacology

Int J Clin Exp Med 2019;12(12):13446-13454 www.ijcem.com /ISSN:1940-5901/IJCEM0101387. Original Article A systematic elucidation of the sanguinarine mechanism in human disease using network pharmacology. Yiyang Zhang*, Jingtong Shuai, Shenhe Su, Qiang Li*. Institute of Tobacco Control & Health Sciences, Agronomy College, Hunan Agricultural University, Changsha 410128, Hunan Province, P. R. China. *Equal contributors.. Received August 23, 2019; Accepted October 10, 2019; Epub December 15, 2019; Published December 30, 2019. Abstract: Sanguinarine (SNG), [C20H14NO4] +, is a quaternary benzo phenanthridine alkaloid, which can be discovered. in many Papaveraceae plants. It is chiefly collected from the roots of the hematogenous plant, the seeds of the Mexican prickly poppy, and the leaves and fruits of the plume poppy. There is no systematic analysis of its pharma- cological mechanism yet. The TCMSP was used to evaluate the medicinal properties of SNG. The potential target of SNG was determined using the Comparative Toxicogenomics Database (CTD). Utilizing the WebGestalt website, the pathways of Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) were analyzed. For visual observation, a drug-target-pathway network was established using Cytoscape. Our results indicated that SNG has excellent drug potency with 50 hypothetical target genes. Through an analysis of GO, KEGG, and the drug network, these targets were associated with apoptosis, platinum drug resistance, the p53 signaling pathways, pathways in cancer, and so on. SNG is predicted to play a systematic pharmacological role in a network of multiple targeted proteins and pathways.. Keywords: Sanguinarine, druggability, enrichment analysis, target prediction, network pharmacology. Introduction. A large number of natural products have shown suitable pharmacological activities in many fields [1]. Many new drugs derived from natural products, which were used to treat diseases, for instance, both bacterial and fungal infec- tions [2], Alzheimer’s disease [3], cancer [4], diabetes, atopic dermatitis [5], and dyslipid- emia [6]. A website named Natural products and traditional Chinese medicine (TCM), which contains plentiful active substances, is among the most complete medication resources for drug development [7]. Benzylisoquinoline alka- loids (BIAs) mainly exist in Papaveraceae, Ranunculaceae, Lauraceae, Annonaceae, Me- nispermaceae, and Berberidaceae medicinal plants. BIAs are synthesized by tyrosine and phenylalanine in natural plants, and they are a kind of alkaloid more abundant and with a more complex structure in nature [8]. The chemical structure expression of SNG (13-methyl-[1,3] benzodioxole [5,6-c]-1,3-dioxolo[4,5-i] phenan-. thridinium) (C20H14NO4) is shown in Figure 1A. SNG has been demonstrated to exercise a lar- ge range of pharmacological functions, which include anti-inflammatory, anti-bacterial, regu- lating cardiovascular disease, improving liver function, and so on [9-12]. In the past few de- cades, lots of experts interested in SNG have noted its anti-cancer properties [13-15]. The above studies indicate that SNG can be used as a valuable chemical probe to identify the influ- encial relationship between compounds, genes, and metabolic pathways in biological metabo- lism, and it is also likely to be developed as drugs for corresponding target genes. Getting suitable pharmacological activity compounds from natural products is an essential way to get new drugs [16].. Network pharmacology is a method for design- ing drugs, which includes network construction & analysis, systems biology, pleiotropy, redun- dancy, and connectivity [17]. Therefore, we sys- tematically elucidated the pharmacological. http://www.ijcem.com. Pharmacology of sanguinarine. 13447 Int J Clin Exp Med 2019;12(12):13446-13454. action of SNG with the method of calculation. First, we evaluated the druggability of SHG with the website “Traditional Chinese Medicine Sys- tems Pharmacology Database” (TCMSP, http:// lsp.nwu.edu.cn/tcmsp.php) [18]. Second, a chemical-gene interaction analysis was used to predict the possible target genes [19]. Also, identified target genes were used to study gene ontology and pathway analysis. Last but not least, a drug target network was constructed to systematically review the potential target genes of SNG and its functional mechanism. Figure 1B shows the workflow chart of the prediction and analysis of the SNG target gene.. Materials and methods. Pharmacokinetic characteristics investigated by TCMSP. The TCMSP website (http://lsp.nwu.edu.cn/ tcmsp.php) is an unparalleled forum for Chin- ese herbal medicine pharmacology, which finds the connections between targets, drugs, and diseases [18]. The database collects data from chemical, target, and drug target networks, and related drug target-disease network relation- ships. It also includes the pharmacokinetic properties of natural compounds such as drug similarity, oral bioavailability, the blood-brain barrier, intestinal epithelial permeability, and water solubility [20]. In this paper, the keyword SNG was input into the UISearchBar for study- ing its pharmacokinetic characteristics.. site, we obtained the predicted candidate tar- gets of SNG.. Analysis through the GeneMANIA website. GeneMANIA (http://www.genemania.org) is an excellent and reliable network analysis website. It can be used to find relevant genes which are bound up with a group of import genes [21]. The linked data involves protein-hereditary interactions, pathways, co-expression, co-ori- entation, and protein domain similarity.. Depending on the specified search list, the GeneMANIA can list relevant genes with shared attributes, either function similar to the initial query. It makes use of functional relationship networks to illustrate the relationships between lists, as well as proteomics and genomics data. Selecting the Homo sapiens organism option, we put the list of candidate potential target genes into the query box, which results would be further sided.. Analysis of functional gene pathway. The gestalt (http://www.webgestalt.org/option. php) is a widely used tool of gene set enrich- ment analysis that helps users extract vital information from genes of interest [22]. Web- Gestalt can be used to genuinely comprehend the functions and pathways that enrich the information of responsive genes [23]. The potential candidate targets were entered into the Gestalt tool utilizing the gene ontology (GO). Figure 1. A. The chemical constitution of SNG which acquired from the Pub- Chem data library (CID: 5154, MF: C20H14NO4. +, MW: 332.335 g/mol); B. The workflow of SNG ADME evaluation, the interaction of chemical-gene (CTD), analyses of GO and the KEGG pathway, and the drug network. Abbrevia- tions: ADME evaluation (Absorption, Distribution, Metabolism, and Excre- tion evaluation); CTD (Comparative Toxicogenomics Database); GO (gene ontology); KEGG (Kyoto Encyclopedia of Genes and Genomes).. Appraisal of the target genes. The Comparative Toxicogeno- mics Database (CTD, http:// ctdbase.org/) is an open and searchable database of toxi- cology genome information. It has critical data on protein in- teractions, chemical-gene, ge- ne-disease, and chemical-dis- ease relationships based on peer-reviewed research pap- ers. To date, the CTD website involves 42,060,266 toxico- genomic contacts associated with chemicals, genes, pro- teins, and so on [19]. For spe- cific compounds, CTD can be arranged in descending order according to their interactions, providing the corresponding target genes. On the CTD web-. Pharmacology of sanguinarine. 13448 Int J Clin Exp Med 2019;12(12):13446-13454. Table 1. Pharmacological and molecular properties of SNG name MW AlogP Hdon Hacc OB (%) Caco-2 BBB DL FASA- TPSA RBN HL SNG 332.35 3.47 0 4 37.81 1.26 0.15 0.86 0.3 40.8 0 7.84 Abbreviations: OB, oral bioavailability; Caco-2, Caco-2 permeability; BBB, the blood-brain barrier; DL, drug-likeness.. and the overrepresentation enrichment analy- sis method of the Kyoto Genome Encyclopedia (KEGG) database. GO analysis, as a standard method, can be used for annotating genes or gene products with molecular functions, cellu- lar components, and biological pathways. The information of gene functions and connected high-caliber genomic function can be examined by KEGG [24, 25].. Network construction. For a further understanding of the complicated associations among compounds, targets, and diseases, we constructed and analyzed a three- layer network using the Cytoscape website (https://www.nigms.nih.gov/, v. 3.6.1).. Results. Pharmacokinetics properties of SNG. The dispensing of pharmaceutical mixtures has been described using ADME characteristics. TCMCP offers information on 12 fundamental aspects of ADME-related features, such as human OB, BBB, Caco-2, and Lipinski’s five principles for drug screening and evaluation [18]. TCMSP was used to study the MADE- related characteristics of SNG deeply. It is note- worthy that the OB calculation of SNG is 37.81% (Table 1).. Targets identification of SNG. Following the methods in the “Materials and Methods” section, the potential targets of SNG were predicted through the CTD website [26]. After adopting the threshold of chemical-gene interaction, 50 specific target genes for SNG identified by CTD that were more significant than or equal to 1 and non-human genes were removed (Table 2). The 50 interacting genes selected would be used for further research.. GeneMANIA analysis. Through comparing the relationship of 50 tar- gets and their interacting proteins, 64.59% dis-. played similar co-expressions, 10.84% Path- way, and 10.75% shared protein domains char- acteristics were found. Figure 2 shows some additional results, including Physical Interacti- ons, Genetic Interactions, and Co-Localization.. GO and pathway enrichment analysis. To thoroughly investigate the 50 identified tar- get genes, we used WebGestalt to conduct GO and KEGG enrichment analyses. As shown in Figure 3, biological processes such as GO:00- 65007 (biological regulation), GO:0050896 (response to stimulus), GO:0008152 (metabol- ic process), GO:0007154 (cell communication), GO:0032501 (multicellular organismal pro- cess), GO:0032502 (developmental process), and GO:0016043 (cellular component organi- zation) were included (Figure 3A). The cellular components included GO:0016020 (mem- brane), GO:0005829 (cytosol), GO:0005634 (nucleus), GO:0032991 (protein-containing complex), GO:0031974 (membrane-enclosed lumen), and GO:0005739 (mitochondrion) (Figure 3B). In addition, the 50 identified target genes also prominently affected the molecular functions, such as GO:0005515 (protein bind- ing), GO:0043167 (ion binding), GO:0016787 (hydrolase activity), GO:0030234 (enzyme reg- ulator activity), GO:0003676 (nucleic acid bind- ing), and GO:0016740 (transferase activity) (Figure 3C). These practical terms have a high correlation with liver function improvement, T lymphocytes and B lymphocytes stimulation, and a significantly reduction in serum lactate dehydrogenase levels.. Through pathway analysis, 50 targets were examined that participate in 10 KEGG path- ways, including apoptosis, platinum drug resis- tance, p53 signaling pathways, pathways in cancer, and so on. There was a significant false discovery rate (FDR)-regulated P-value (Figure 4).. Network analysis. According to pathway analyses and the targets of the indicated genes, a complete network of. Pharmacology of sanguinarine. 13449 Int J Clin Exp Med 2019;12(12):13446-13454. Table 2. Potential targets of SNG Num Gene ID Gene symbol Gene name 1 196 AHR aryl hydrocarbon receptor 2 405 ARNT aryl hydrocarbon receptor nuclear translocator 3 581 BAX BCL2 associated X, apoptosis regulator 4 27113 BBC3 BCL2 binding component 3 5 596 BCL2 BCL2 apoptosis regulator 6 79370 BCL2L14 BCL2 like 14 7 637 BID BH3 interacting domain death agonist 8 638 BIK BCL2 interacting killer 9 329 BIRC2 baculoviral IAP repeat-containing 2 10 665 BNIP3L BCL2 interacting protein 3 like 11 59082 CARD18 caspase recruitment domain family member 18 12 84674 CARD6 caspase recruitment domain family member 6 13 834 CASP1 caspase 1 14 843 CASP10 caspase 10 15 836 CASP3 caspase 3 16 837 CASP4 caspase 4 17 838 CASP5 caspase 5 18 841 CASP8 caspase 8 19 842 CASP9 caspase 9 20 9075 CLDN2 claudin 2 21 1365 CLDN3 claudin 3 22 1364 CLDN4 claudin 4 23 7122 CLDN5 claudin 5 24 1543 CYP1A1 cytochrome P450 family 1 subfamily A member 1 25 1545 CYP1B1 cytochrome P450 family 1 subfamily B member 1 26 162989 DEDD2 death effector domain containing 2 27 1958 EGR1 early growth response 1 28 355 FAS Fas cell surface death receptor 29 356 FASLG Fas ligand 30 2940 GSTA3 glutathione S-transferase alpha 3 31 2950 GSTP1 glutathione S-transferase pi 1 32 27306 HPGDS hematopoietic prostaglandin D synthase 33 4050 LTB lymphotoxin beta 34 5594 MAPK1 mitogen-activated protein kinase 1 35 5595 MAPK3 mitogen-activated protein kinase 3 36 5599 MAPK8 mitogen-activated protein kinase 8 37 5601 MAPK9 mitogen-activated protein kinase 9 38 4313 MMP2 matrix metallopeptidase 2 39 4318 MMP9 matrix metallopeptidase 9 40 64332 NFKBIZ NFKB inhibitor zeta 41 22861 NLRP1 NLR family pyrin domain containing 1 42 1728 NQO1 NAD(P)H quinone dehydrogenase 1 43 5366 PMAIP1 phorbol-12-myristate-13-acetate-induced protein 1 44 29108 PYCARD PYD and CARD domain-containing 45 6615 SNAI1 snail family transcriptional repressor 1 46 7124 TNF tumor necrosis factor 47 8795 TNFRSF10B TNF receptor superfamily member 10b 48 7133 TNFRSF1B TNF receptor superfamily member 1B 49 8743 TNFSF10 TNF superfamily member 10 50 331 XIAP X-linked inhibitor of apoptosis. Pharmacology of sanguinarine. 13450 Int J Clin Exp Med 2019;12(12):13446-13454. Figure 2. SNG protein network. Notes: The target protein is represented by black nodes, and different correlations are indicated by the differently colored connections.. the compounds, targets, and diseases was es- tablished using Cytoscape (v. 3.7.1). The com- pounds, diseases, and target interaction net- work have 61 nodes with 201 edges. The green triangle, red circular rectangle, and blue circu- lar graph are used to represent the target genes, SNG and pathway respectively (Figure 5).. Discussion. The lack of pharmacokinetic and toxicity re- search foundations is one of the most signifi- cant reasons for the high cost and long cycle of drug research and development. So, more and more people agree that the specific character- istics of the drug development process should be given priority [27]. Computer analysis can moderate prediction and pharmacokinetic mo- deling, together with metabolic and toxicity endpoints. All this simplifies and speeds up the process of drug research [16, 28].. In 1997, Christopher Lipinksi and his colleagues developed the “Five Rules” (Ro5) because Pfizer used high throughput screening (HTS),. which led to the pursuit of more vibrant, more lipophilic compounds, which often had a lower permeability and solubil- ity [29]. Today, the five rules are commonly regarded as the guidelines for drug optimiza- tion [30]. In Table 1, the phar- macokinetic characteristics of SNG reached these require- ments, indicating that SNG is the right candidate for drug research.. Target gene identification and screening is the essential work of drug research. There are more active compounds or drugs that have been proved to interact with a variety of genes or proteins [31-35]. For this purpose, many kinds of target gene recognition methods ha- ve made significant progress and are widely used. Table 1 shows that 50 potential tar- gets for SNG have been identi-. fied with the method of calculation. The analy- sis results of GeneMANIA revealed that the target proteins and their interacting proteins may have the same or similar functions, and showed the information about the co-location, co-expression, and sharing of protein domains with interaction effects. We identified that SNG played an anti-inflammatory role to improve liver function. SNG has been acknowledged as an anticancer drug candidate [36]. Qi, Xiao-Yi et al. reported SNG could destroy the liver func- tions of Oncomelania hupensis by reducing glu- cogen content and changing the activity of some essential enzymes in snail livers [36]. The administration of SNG can regulate the immune-related genes of goldfish, which can affect their ability to resist bacterial pathogens to a certain extent [37]. The above results are consistent with the results of our GO and KEGG analysis.. The drug-target network uncovered that SNG has a variety of targets, which further indicates its numerous pharmacological activities (Fig- ure 5). Adhami et al. have also shown that the mitochondrial pathway and Bcl-2 family pro-. Pharmacology of sanguinarine. 13451 Int J Clin Exp Med 2019;12(12):13446-13454. Figure 4. KEGG enrichment pathway analysis of potential target genes.. teins were also involved in the SNG-mediated apoptosis of immortalized keratinocytes [38]. SNG leads apoptosis of human osteosarcoma cells via the extrinsic and intrinsic pathways [39], and it also activates the pathways of poly- cyclic aromatic hydrocarbon-related metabo- lism in human oral keratinocytes and tissues [40]. Multi-target drugs are more effective in treating complex diseases, such as cancer, and are less susceptible to adaptive resistance. Thus, SNG may be a valuable plant resource for. future drug research as a chemical component, lead compound, or active ingredient.. In conclusion, we need to point out that SNG is an active ingredient or potential compound derived from plants, which can be used to develop safe and efficient multi-target antican- cer drugs. We provide a new perspective and challenge for the study and are looking forward to the future drug development and clinical application of SNG.. Figure 3. GO maps of the assumed target genes. Notes: Biological process categories (A). Cellular component cat- egories (B). Molecular function categories (C).. Pharmacology of sanguinarine. 13452 Int J Clin Exp Med 2019;12(12):13446-13454. Disclosure of conflict of interest. None.. Address correspondence to: Qiang Li, Institute of Tobacco Control & Health Sciences, Agronomy College, Hunan Agricultural University, Changsha 410128, Hunan Province, P. R. China. Tel: +86- 0731-84635356; E-mail: zqiangli@126.com. References. [1] Decker M. Hybrid molecules incorporating nat- ural products: applications in cancer therapy, neurodegenerative disorders and beyond. Curr Med Chem 2011; 18: 1464-1475.. [2] Ignasimuthu K, Prakash R, Murthy PS and Sub- ban N. Enhanced bioaccessibility of green tea polyphenols and lipophilic activity of EGCG oc-. taacetate on gram-negative bacteria. Lwt-Food Science and Technology 2019; 105: 103-109.. [3] Basso AMM, De Castro RJA, de Castro TB, Gui- maraes HI, Polez VLP, Carbonero ER, Pomin VH, Hoffmann C, Grossi-de-Sa MF, Tavares AH and Bocca AL. Immunomodulatory activity of beta-glucan-containing exopolysaccharides from auricularia auricular in phagocytes and mice infected with cryptococcus neoformans. Med Mycol 2019; [Epub ahead of print].. [4] Wang C, Huang Q, Liang CL, Zhang YW, Deng DH, Yu Y, Chen DB, Yang HJ and Yu XF. Effect of cimicifuga racemosa on menopausal syn- drome caused by LHRH-a in breast cancer. J Ethnopharmacol 2019; 238: 111840.. [5] Abbas G, Al Harrasi A, Hussain H, Hamaed A and Supuran CT. The management of diabetes mellitus-imperative role of natural products against dipeptidyl peptidase-4, alpha-glucosi-. Figure 5. SNG-target-pathway network.. Pharmacology of sanguinarine. 13453 Int J Clin Exp Med 2019;12(12):13446-13454. dase and sodium-dependent glucose co-trans- porter 2 (SGLT2). Bioorg Chem 2019; 86: 305- 315.. [6] Lubrano V, Pingitore A, Traghella I, Storti S, Parri S, Berti S, Ndreu R, Andrenelli A, Palmieri C, Iervasi G, Mastorci F and Vassalle C. Emerg- ing biomarkers of oxidative stress in acute and stable coronary artery disease: levels and de- terminants. Antioxidants (Basel) 2019; 8.. [7] Ren L, Zheng X, Liu J, Li W, Fu W, Tang Q, Wang J and Du G. Network pharmacology study of traditional Chinese medicines for stroke treat- ment and effective constituents screening. J Ethnopharmacol 2019; 242: 112044.. [8] Vavricka CJ, Yoshida T, Kuriya Y, Takahashi S, Ogawa T, Ono F, Agari K, Kiyota H, Li JY, Ishii J, Tsuge K, Minami H, Araki M, Hasunuma T and Kondo A. Mechanism-based tuning of insect 3,4-dihydroxyphenylacetaldehyde synthase for synthetic bioproduction of benzylisoquinoline alkaloids (vol 10, 2015, 2019). Nat Commun 2019; 10: 1.. [9] Singh N and Sharma B. Toxicological effects of berberine and sanguinarine. Front Mol Biosci 2018; 5: 21.. [10] Meng YY, Liu Y, Hu ZF, Zhang Y, Ni J, Ma ZG, Liao HH, Wu QQ and Tang QZ. Sanguinarine at- tenuates lipopolysaccharide-induced inflam- mation and apoptosis by inhibiting the TLR4/ NF-kappa B pathway in H9c2 cardiomyocytes. Curr Med Sci 2018; 38: 204-211.. [11] Ma Y, Chu J, Ma J, Ning L, Zhou K and Fang X. Sanguinarine protects against ovariectomy-in- duced osteoporosis in mice. Mol Med Rep 2017; 16: 288-294.. [12] Balestrini L, Di Donfrancesco A, Rossi L, Mar- racci S, Isolani ME, Bianucci AM and Batistoni R. The natural compound sanguinarine per- turbs the regenerative capabilities of planari- ans. Int J Dev Biol 2017; 61: 43-52.. [13] Hammerová J, Uldrijan S, Táborská E and Slaninová I. Benzo[c]phenanthridine alkaloids exhibit strong anti-proliferative activity in ma- lignant melanoma cells regardless of their p53 status. J Dermatol Sci 2011; 62: 22-35.. [14] Kalogris C, Garulli C, Pietrella L, Gambini V, Pucciarelli S, Lucci C, Tilio M, Zabaleta ME, Bartolacci C, Andreani C, Giangrossi M, Iezzi M, Belletti B, Marchini C and Amici A. Sanguin- arine suppresses basal-like breast cancer growth through dihydrofolate reductase inhibi- tion. Biochem Pharmacol 2014; 90: 226-234.. [15] Gu S, Yang XC, Xiang XY, Wu Y, Zhang Y, Yan XY, Xue YN, Sun LK and Shao GG. Sanguinarine- induced apoptosis in lung adenocarcinoma cells is dependent on reactive oxygen species production and endoplasmic reticulum stress. Oncol Rep 2015; 34: 913-919.. [16] Bi YH, Zhang LH, Chen SJ and Ling QZ. Antitu- mor mechanisms of curcumae rhizoma based. on network pharmacology. Evid Based Comple- ment Alternat Med 2018; 2018: 4509892.. [17] Hopkins AL. Network pharmacology. Nat Bio- technol 2007; 25: 1110-1111.. [18] Ru J, Li P, Wang J, Zhou W, Li B, Huang C, Li P, Guo Z, Tao W, Yang Y, Xu X, Li Y, Wang Y and Yang L. TCMSP: a database of systems phar- macology for drug discovery from herbal medi- cines. J Cheminform 2014; 6: 13.. [19] Davis AP, Wiegers TC, King BL, Wiegers J, Gron- din CJ, Sciaky D, Johnson RJ and Mattingly CJ. Generating gene ontology-disease inferences to explore mechanisms of human disease at the comparative toxicogenomics database. PLoS One 2016; 11: e0155530.. [20] Pei T, Zheng C, Huang C, Chen X, Guo Z, Fu Y, Liu J and Wang Y. Systematic understanding the mechanisms of vitiligo pathogenesis and its treatment by Qubaibabuqi formula. J Ethno- pharmacol 2016; 190: 272-287.. [21] Warde-Farley D, Donaldson SL, Comes O, Zu- beri K, Badrawi R, Chao P, Franz M, Grouios C, Kazi F, Lopes CT, Maitland A, Mostafavi S, Mon- tojo J, Shao Q, Wright G, Bader GD and Morris Q. The GeneMANIA prediction server: biologi- cal network integration for gene prioritization and predicting gene function. Nucleic Acids Res 2010; 38: W214-220.. [22] Zhang B, Kirov S and Snoddy J. WebGestalt: an integrated system for exploring gene sets in various biological contexts. Nucleic Acids Res 2005; 33: W741-748.. [23] Liao Y, Wang J, Jaehnig EJ, Shi Z and Zhang B. WebGestalt 2019: gene set analysis toolkit with revamped UIs and APIs. Nucleic Acids Res 2019; 47: W199-W205.. [24] The Gene Ontology Consortium. Expansion of the gene ontology knowledgebase and re- sources. Nucleic Acids Res 2017; 45: D331- D338.. [25] Kanehisa M, Furumichi M, Tanabe M, Sato Y and Morishima K. KEGG: new perspectives on genomes, pathways, diseases and drugs. Nu- cleic Acids Res 2017; 45: D353-D361.. [26] Davis AP, Grondin CJ, Johnson RJ, Sciaky D, King BL, McMorran R, Wiegers J, Wiegers TC and Mattingly CJ. The comparative toxicoge- nomics database: update 2017. Nucleic Acids Res 2017; 45: D972-D978.. [27] Lipinski CA, Lombardo F, Dominy BW and Fee- ney PJ. Experimental and computational ap- proaches to estimate solubility and permeabil- ity in drug discovery and development settings. Adv Drug Deliv Rev 2001; 46: 3-26.. [28] Yang C. Analysis of the action mechanism of Fang Ji Huang Qi decoction in treating rheuma- toid arthritis by network pharmacology. Tradi- tional Medicine Research 2018; 3: 286-294.. [29] Lipinski CA, Lombardo F, Dominy BW and Fee- ney PJ. Experimental and computational ap-. Pharmacology of sanguinarine. 13454 Int J Clin Exp Med 2019;12(12):13446-13454. proaches to estimate solubility and permeabil- ity in drug discovery and development settings. Adv Drug Deliv Rev 2001; 46: 3-26.. [30] Leeson PD. Molecular inflation, attrition and the rule of five. Adv Drug Deliv Rev 2016; 101: 22-33.. [31] Schenone M, Dančík V, Wagner BK and Clem- ons PA. Target identification and mechanism of action in chemical biology and drug discovery. Nat Chem Biol 2013; 9: 232-40.. [32] Terstappen GC, Schlupen C, Raggiaschi R and Gaviraghi G. Target deconvolution strategies in drug discovery. Nat Rev Drug Discov 2007; 6: 891-903.. [33] Wang K, Yang T, Wu Q, Zhao X, Nice EC and Huang C. Chemistry-based functional pro- teomics for drug target deconvolution. Expert Rev Proteomics 2012; 9: 293-310.. [34] Futamura Y, Muroi M and Osada H. Target identification of small molecules based on chemical biology approaches. Mol Biosyst 2013; 9: 897-914.. [35] Jung HJ and Kwon HJ. Target deconvolution of bioactive small molecules: the heart of chemi- cal biology and drug discovery. Arch Pharm Res 2015; 38: 1627-1641.. [36] Qi XY, Liang SC, Ge GB, Liu Y, Dong PP, Zhang JW, Wang AX, Hou J, Zhu LL, Yang L and Tu CX. Inhibitory effects of sanguinarine on human liver cytochrome P450 enzymes. Food Chem Toxicol 2013; 56: 392-397.. [37] Zhang C, Ling F, Chi C and Wang GX. Effects of praziquantel and sanguinarine on expression of immune genes and susceptibility to aeromo- nas hydrophila in goldfish (carassius auratus) infected with dactylogyrus intermedius. Fish Shellfish Immunol 2013; 35: 1301-1308.. [38] Adhami VM, Aziz MH, Mukhtar H and Ahmad N. Activation of prodeath Bcl-2 family proteins and mitochondrial apoptosis pathway by san- guinarine in immortalized human HaCaT kera- tinocytes. Clin Cancer Res 2003; 9: 3176- 3182.. [39] Park H, Bergeron E, Senta H, Guillemette K, Beauvais S, Blouin R, Sirois J and Faucheux N. Sanguinarine induces apoptosis of human os- teosarcoma cells through the extrinsic and in- trinsic pathways. Biochem Biophys Res Com- mun 2010; 399: 446-451.. [40] Karp JM, Rodrigo KA, Pei P, Pavlick MD, Ander- sen JD, McTigue DJ, Fields HW and Mallery SR. Sanguinarine activates polycyclic aromatic hy- drocarbon associated metabolic pathways in human oral keratinocytes and tissues. Toxicol Lett 2005; 158: 50-60.

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