Elucidation of the mechanisms underlying the anti- cholecystitis effect of the Tibetan medicine “Dida” using Network pharmacology

Purpose: To study the mechanism involved in the anti-cholecystitis effect the Tibetan medicine “Dida”, using network pharmacology-integrated molecular docking simulations Methods: In this investigation, the bioactive compounds of Dida were collected, network pharmacology methods to predict their targets, and networks were constructed through GO and KEGG pathway analyses. The potential binding between the bioactive compounds and the targets were demonstrated using molecular docking simulations. Results: A total of 12 bioactive compounds and 50 key targets of Dida were identified. Two networks, namely, protein-protein interaction (PPI) network of cholecystitis targets, and compound-target-pathway network, were established. Network analysis showed that 10 targets (GAPDH, AKT1, CASP3, EGFR, TNF, MAPK3, MAPK1, HSP90AA1, STAT3, and BCL2L1) may be the therapeutic targets of Dida in cholecystitis. Analysis of the KEGG pathway indicated that the anti-cholecystitis effect of Dida may its regulation of a few crucial pathways, such as apoptosis, as well as toll-like receptor, T cell receptor, NOD-like receptor, and MAPK signaling pathways. Furthermore, molecular docking simulation revealed that CASP3, CAPDH, HSP90AA1, MAPK3, MAPK1, and STAT3 had well-characterized interactions with the corresponding compounds. Conclusion: The mechanism underlying the anti-cholecystitis effect of Dida was successfully predicted and verified using a combination of network pharmacology and molecular docking simulation. This provides a firm basis for the experimental verification of the use of Dida in the treatment of cholecystitis, and enhances its rational application in clinical medication.


INTRODUCTION
Cholecystitis, a common disease of the digestive system, often causes severe inflammation of the gallbladder and serious health problems [1]. Based on clinical manifestation and clinical course, cholecystitis may be acute or chronic, with cholelithiasis as one of the most common etiologies [2]. Current treatment strategies for cholecystitis include supportive care (intravenous hydration, pain control, antibiotic administration, and correction of electrolytes); gallbladder drainage, cholecystectomy, and cholecystostomy [3]. The commonly used treatment strategies are antibiotics and cholecystectomy. When antibiotics are used for therapy, pain usually recurs and persists, and infection or sepsis is likely to occur because the gallbladder is not drained [4]. Similarly, cholecystectomy poses many risks, including organ infection, bile duct injury, and increased mortality [5]. In the traditional Tibetan medical theory, cholecystitis belongs to the category of ChiBa, and its pathogenesis is caused by disorders in three roots and seven elements in the body and thermal evil attacking the gallbladder [6].
Traditional Tibetan medicine (TTM), known for the law of compound compatibility in treatments based on syndrome differentiation, plays a positive role in the prevention, treatment and rehabilitation of cholecystitis in China, due to its synergistic effect and minimal side effects [7]. The Tibetan medicine "Dida" is an original multibase medicinal material that is often used to treat cholecystitis with a single medicine or compound prescription [8].
Drug use in major Tibetan hospitals has revealed that Swertia chirayita (Roxb. ex Flem.) Karst. is the most commonly used basic variety of Dida [9]. Dida containsa variety of chemical components, primarily xanthones, iridoid glycosides, flavonoids, and triterpenoids. It also has a series of pharmacological effects, such as anti-inflammatory, bacteriostatic, anti-tumor, antilipid, anti-liver injury, anti-oxidation, hypoglycemic and anti-mutation [10]. Although TTM has demonstrated the therapeutic effects of Dida on cholecystitis, the underlying molecular mechanism has not been fully elucidated.
Traditional Tibetan medicine (TTM), a multicomponent, multi-target, multi-pathway treatment, achieves its unique therapeutic effect by acting on the molecular biological network of the human system [11]. Thus, it is difficult to unravel the mechanism of action of TTM. However, the novel technique of network pharmacology has contributed exciting solutions and unique ideas for enhancing the scientific interpretation of the mechanisms involved in the actions of drugs. Network pharmacology integrates systems biology, molecular dynamics and other multidisciplinary techniques to construct and integrate a multi-layer network of "disease -phenotype -gene -drug", which effectively illustrates the interaction between disease and drug, and it has been widely used in research on the mechanism of Tibetan medicine [12]. Molecular docking is a method of matching a ligand (drug) to a target molecule (receptor) by producing various components in different directions. The binding capacity between the ligand and the receptor is expressed as docking score, and a large negative docking score equates to a good direction of fit [13].
In this study, the molecular mechanism underlying the use of the Tibetan medicine Dida in the treatment of cholecystitis was analyzed and predicted via the combination of network pharmacology method and molecular docking simulation. The flowchart details are shown in Figure 1.

Construction of database of candidate compounds
Swertia chirayita (SC) is a representative species of Dida. Compound data information on SC was established by screening the Traditional Chinese Medicine Systems Pharmacology Database (http://lsp.nwu.edu.cn/tcmsp.php), the TCM Database@Taiwan (http://tcm.cmu.edu.tw/zh-tw/), and related literature [21]. When acquiring the main potential compounds, the following screening criteria were used: oral bioavailability (OB) ≥30%, and druglikeness (DL) ≥0.18. On the basis of the absorption, distribution, metabolism, and excretion (ADME) parameters in TCMSP and cholecystitis values obtained from previous work [9], the chemical components that met these criteria were selected as candidate compounds for further analyses.

Target prediction for bioactive compounds
The candidate compounds in the PubChem database (https://pubchem.ncbi.nlm.nih.gov/) that were converted into the standard canonical SMILES format and imported from the Swiss Target Prediction (http://www.swisstargetpredic tion.ch/) platform were set to "Homo sapiens" to predict the potential target active compounds.

Protein-protein interaction data
Protein-Protein Interaction (PPI) data were extracted on the STRING database (https://string-db.org/). STRING defines a reasonable confidence range for PPI data scores (low confidence: <0.4, medium confidence: 0.4 to 0.7, and high confidence: >0.7). After the intersection of disease target and drug target was noted, cholecystitis-related targets were entered into the STRING database (the confidence score was set above 0.7) for PPI prediction. The visualization of the PPI networks was conducted on Cytoscape 3.7.0 software.

Gene ontology (GO) and pathway analyses
Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses provide gene expression data and overall system visual information of core pivot genes. In the screening of potential common targets for this study, GO and KEGG pathway analyses were conducted so as to predict the mechanism of action of Dida in treating cholecystitis using the DAVID v6.8.

Network construction
Two networks were constructed using Cytoscape 3.7.0 software. A PPI network cholecystitis targets was constructed by connecting and analyzing the connectivity, proximity, and centrality between cholecystitis-related targets and the human proteins. A compound-targetpathway network was created by linking compounds, corresponding targets, and pathways. In a complex associative network, nodes and edges express the direction and magnitude of compounds/entities and their cross forces, respectively. A high degree value equates to a prominent node status.

Molecular docking simulation
Molecular docking simulation was performed on the selected targets and corresponding compounds using Maestro version 11.5 from the Schrodinger software suite. The lowest/minimum energy conformation was used for molecular docking via the default parameters. Docking score is the absolute value of the experimental dissociation, relative to the inhibition constant (pKd/pKi), usually ranging from 0 to 10 (low to high combination force) [13].

Identification of the bioactive compounds
Ten potential compounds (OB ≥ 30 %, DL ≥ 0.18) in Dida were identified after ADME screening. In addition to these 10 compounds, 2 compounds (i.e., gentiopicroside and swertiamarin) with low OB were classified as bioactive components and they have been shown to be effective in the treatment of cholecystitis through extensive experiments [14]. In total, 12 active components from Dida were selected for further analysis. The relevant data are shown in Table 1 and Figure 2.

Targets identification and PPI network
The determination of the key targets and the analysis of PPI network involves the following three steps: In the first step, 463 potential targets were obtained through the prediction of 12 active compounds using the Swiss Target Prediction platform; Secondly, 387 cholecystitis-related targets were retrieved from GeneCards, CTD, and OMIM databases; Finally, 50 targets closely related to the prevention and treatment of cholecystitis were obtained by accurately mapping the potential targets obtained in the previous two steps ( Table 2).

PPI network of target genes
The PPI relationship of 50 target genes was accurately analyzed with STRING big data tool. At the same time, the PPI relational network graph established with Cytoscape 3.7.0 contained 48 nodes and 866 edges, when the comprehensive score was set to >0.4. The nodes in the network represented the targets, the edges represented the relationship between the targets, and the free degrees indicated the target screening criteria (Figure 3). Based on the degree of freedom ranking, 10 target genes with the highest degree connectivity were identified as the hub targets, which might play a crucial role in cholecystitis progression were GAPDH, AKT1, CASP3, EGFR, TNF, MAPK3, MAPK1, HSP90AA1, STAT3, and BCL2L1.

GO and KEGG pathway analyses
To investigate the potential molecular mechanisms involved in the anti-cholecystitis effect of Dida, DAVID database was used for GO and KEGG enrichment analysis of 50 candidate targets. The GO evaluation results were illustrated using biological process (BP), cell component (CC), and molecular function (MF) terms. A preliminary GO analysis revealed the top 10 enriched conditions in the BP (e.g., the primary metabolic process, regulation of biological process, regulation of cellular process, and cell differentiation), CC (e.g., organelle, intracellular organelle lumen, and nucleoplasm), and MF (e.g., protein binding, nucleotide binding, and hydrolase activity) categories (Figure 4). Subsequently, a total of 29 pathways were obtained (p < 0.05) and 9 major pathways associated with cholecystitis were identified ( Figure 5).Finally, through the review of relevant literature, it was found that apoptosis, NOD-like receptor signaling pathway, toll-like receptor signaling pathway, T cell receptor signaling pathway, MAPK signaling pathway and other signaling pathways may interact with each other and result in an anti-cholecystitis effect.

Network construction and analysis
A compound-target-pathway Network of Dida for the treatment of cholecystitis was constructed ( Figure 6). The network was composed of 91 nodes and 728 edges, showing the correlation and intersection among 12 chemical components, 50 targets and 29 pathways. The mechanism underlying the anti-cholecystitis effect of Tibetan medicine Dida was initially revealed through the analysis of the network.

DISCUSSION
Cholecystitis is a common surgical disease that was first discovered in humans 3500 years ago [26]. Although surgical and drug treatments are crucial, their clinical effect is not ideal for the treatment of cholecystitis. Therefore, it is necessary to develop treatment methods for cholecystitis from the mechanism of the disease and integrate different medical systems from a comprehensive perspective [3]. Traditional Tibetan medicine (TTM) focuses on the stability of the entire body by balancing the three humors (nyes pa), namely, wind (rlung), bile (mkhris pa), and phlegm (bad kan) in the treatment of complex cholecystitis [15]. Dida, the preferred Tibetan medicine for treatment of cholecystitis, has a definite curative effect and it is widely used and recognized. It can be traced back to Tibetan medicine books such as Yue Wang's Classical Medicinal Book (Somaratsa), the four medical tantras (rGyud-bzhi) and Jing Zhu Materia Medica (Shel Gong Shel Phreng) [6,8].   The network consisted of 91 nodes and 728 edges, including 12 active compounds, 50 potential protein targets, and 29 pathway interactions. The corresponding relationship is as follows: Green circle correspond to compound; Red rectangle correspond to potential target; Blue diamond correspond to pathway  However, the development of TTMs was restricted by the unclear qualitative and quantitative characteristics of drug components and the complex target and mechanism of action. Network pharmacology has provided an innovative method for investigating the pharmacological mechanisms of TTMs.
In this study, the pharmacologic mechanism involved in the use of Tibetan medicine Dida for treatment of cholecystitis was preliminarily obtained through the organic combination of network pharmacology and molecular docking simulation. The results revealed that 12 representative compounds and 50 targets involving 29 pathways were associated with the anti-cholecystitis effect of Dida. Through pathway enrichment, it was determined that the mechanism could involve mutual antagonism and mutual synergism of multiple pathways, such as apoptosis, NOD-like receptor signaling pathway, toll-like receptor signaling pathway, T cell receptor signaling pathway, and MAPK signaling pathway. In addition, the degree of crosscomparison between genes was high according to the PPI system analysis of cholecystitis targets, and GAPDH, AKT1, CASP3, EGFR, TNF, MAPK3, MAPK1, HSP90AA1, STAT3, and BCL2L1 were identified as the central genes.
Glyceraldehyde 3-phosphate dehydrogenase (GAPDH) is an energy metabolism-related enzyme. Several studies have indicated that GAPDH regulates the immune function and exert anti-inflammatory effects. It has been reported that the anti-inflammatory effect of GADPH was regulated by downregulating aerobic glycolysis in activated myeloid cells and lymphocytes [16]. Protein kinase (AKT1), a member of the Akt family, is expressed in macrophages which participate in various biological processes, such as metabolism, proliferation, and cell survival. Protein kinase (AKT1) activation leads to the production of large amounts of pro-inflammatory cytokines which play a crucial role in inflammatory responses [17]. Caspase-3 (CASP3), a key enzyme in the process of apoptosis, belongs to the caspase family, which activation and inflammation occur simultaneously and in different tissues [18]. Epidermal growth factor receptor (EGFR) is considered to be a key pathway for GPCRs signaling. Thus, there may be a mechanism linking chronic inflammation to a variety of diseases, especially cancer. Studies have shown that EGFR expression is increased in chronic cholecystitis and gallbladder carcinoma, suggesting that inflammation has a certain relationship with EGFR expression [19]. Tumor necrosis factor alpha (TNFα), a proinflammatory cytokine and an apoptosis-inducing factor, can be used as a drug for the treatment of inflammatory diseases via the pathogenesis of various inflammatory diseases of the liver and gallbladder. The increase in supersaturated bile and hydrophobic bile acids in guinea pigs with gallstone disease enhanced the release of TNFα and trigger the TNF-α/Caspase8/ Caspase3 cascade to induce apoptosis [20].
Mitogen-activated protein kinases (MAP kinases) are highly conserved serine/threonine protein kinases that function in a variety of essential cellular processes, including proliferation, differentiation, motility, apoptosis, and survival. One of the MAP kinases, similar to MAPK3, is a major member of the MAPK family and plays a crucial role in the MAPK/ERK cascade. Previous reports have confirmed that ERK/MAPK pathway is activated in gallbladder cancer, resulting in promotion cell proliferation and invasion. [21]. Heat shock protein HSP 90-alpha 1 (HSP90AA1), a significant class of heat shock proteins, belongs to the HSP90 family. Extracellular HSP90AA1 induces inflammation by activating NF-kB and STAT3 transcriptional programs (including pro-inflammatory cytokines IL-6 and IL-8) [22].
Signal transducer and activator of transcription 3 (STAT3), a transcription factor involved in immune and inflammatory responses, is rapidly activated by various cytokines, growth factors, and hepatocyte growth factors [23]. The Bcl-2like protein 1 (BCL2L1), a member of the family of Bcl-2 proteins, is a crucial apoptosis-regulating gene that participates in the regulation of mitochondrial apoptosis pathways by controlling the release of pro-apoptotic factors in mitochondria [23]. In this network, a high degree of target involved various inflammatory processes, among which was cholecystitis. However, only a few studies on cholecystitis are available, and other unreported targets need to be confirmed via further experiments.
In the compound-target-pathway network, the enrichment of 29 pathways was associated with Dida in the treatment of cholecystitis, and also with the classical inflammatory pathways, such as apoptosis, NOD-like receptor signaling pathway, toll-like receptor signaling pathway, T cell receptor signaling pathway, and MAPK signaling pathway. Apoptosis was activated in gangrenous cholecystitis cells, leading to the inhibition of cell viability. These results indicate that the mechanism involved in the use of Dida for cholecystitis may improve cell survival by regulating the apoptosis pathway [24]. (The NOD-like receptors) and toll-like receptors (TLRs), which are the members of pattern recognition receptors (PRRs), have been associated with human diseases such as infections, cancer, and inflammatory disorders [25]. The MAPK signaling pathway has a handin-hand relationship with the occurrence of various underlying diseases, such as inflammation and tumors, and it is fundamental in the pathogenesis of gallbladder cancer and cholecystitis [21]. In summary, the above classical inflammatory pathways are predictive pathway for Dida intervention in cholecystitis, and require further cellular experiments and animal validation.

CONCLUSION
In this study, network pharmacology method has been successfully used to investigate the complex network relationships among multiple components, multiple targets and multiple pathways, and to predict the mechanism underlying the anti-cholecystitis effect of Dida. Molecular docking supports the application of bioactive compounds in Dida in the treatment of cholecystitis. However, the results of these in silico methods need to be verified via in vitro and in vivo experiments.