30 September 2022: Original Paper
Network Pharmacology-Based Exploration of the Therapeutic Mechanisms of in Renal Ischemia/Reperfusion
Jiajun Dong1BCEF, Mingyang Cao2BCEF, Hui Yu3BCEF, Yang Dong24AD, Conghui Han124AG*DOI: 10.12659/AOT.937469
Ann Transplant 2022; 27:e937469
Abstract
BACKGROUND: Cordyceps cicadae is beneficial in treating renal diseases, especially in inhibiting renal ischemia/reperfusion injury (IRI). The aim of this study was to systematically analyze and predict the potential mechanism of Cordyceps cicadae in renal IRI therapy using network pharmacology.
MATERIAL AND METHODS: Cordycepin, adenosine, and cordycepic acid are the 3 major medicinal ingredients in Cordyceps cicadae. Based on network pharmacology, the 3D structure of the 3 compounds were obtained, and then the common targets between these compounds and renal IRI were analyzed and determined. We used the ingredient-target (I-T), protein–protein interaction (PPI) networks, the enrichment analysis of Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) to find the possible pharmacological mechanism of Cordyceps cicadae in treating renal IRI.
RESULTS: Through target fishing and analysis, the 3 active ingredients of Cordyceps cicadae shared 81 target genes with renal IRI. I-T network showed that adenosine had the highest degree, and 5 genes were associated with the 3 active ingredients. PPI network analysis showed that ALB, GAPDH, CASP3, MAPK1, FN1, and IL-10 play a pivotal role. The enrichment analysis of GO and KEGG showed that Cordyceps cicadae can treat renal IRI through MAPK, cAMP, PPAR, Rap1, and HIF-1 signaling pathways.
CONCLUSIONS: Cordyceps cicadae exerts its therapeutic effect on renal IRI via multiple targets and pathways. Nevertheless, further experimentation is needed to verify this. The method of network pharmacology provides an effective method of determining the comprehensive action mechanism of Traditional Chinese Medicine (TCM).
Keywords: Cordyceps cicadae, Forecasting, Molecular Mechanisms of Pharmacological Action, Reperfusion Injury, systems biology, Adenosine, Caspase 3, Cordyceps, Humans, Interleukin-10, Ischemia, Kidney Diseases, Network Pharmacology, peroxisome proliferator-activated receptors, Reperfusion
Background
Ischemia reperfusion injury (IRI) refers to a pathological condition in which tissue or organ damage is aggravated instead of alleviated when the tissue or organ regains perfusion or oxygen supply after ischemia [1]. Clinically, renal IRI occurs most commonly following traumatic shock, sepsis, partial nephrectomy, post-partum hemorrhage, and other major surgical procedures [2]. Surprisingly, the probability of IRI in kidney transplant patients is almost 100% [3]. Although the mechanism by which renal IRI occurs is unclear, it is thought to result from apoptosis, necrosis, oxygen free radicals, inflammation, mitochondrial damage, and ferroptosis [4–6]. One of the key factors is the inflammatory cascade induced by immune cells infiltration [7]. Renal ischemia causes significant tissue hypoxia, which triggers the recruitment of immune cells such as dendritic cells (DC cells), neutrophils, macrophages, and natural killer T (NKT) cells to the injured tissues and the release of pro-inflammatory factors [8]. When blood perfusion is restored later, the inflammatory response is further exacerbated, resulting in progressive aggravation of renal damage [9].
Currently, there is still no satisfactory treatment for IRI. On the one hand, new treatments are effective but have limited clinical applications due to insufficient clinical evidence and serious complications [10,11]. On the other hand, the lack of expertise in renal transplantation pathology has affected the evaluation of the IRI caused by transplanted kidneys to some extent [12], although the application of artificial intelligence is expected to improve such events [13,14]. As a traditional form of treatment, pharmacotherapy has always been the focus of research, but despite this, there are no specific drugs available for treating renal IRI [15,16]. Traditional Chinese Medicine (TCM) treatment has the characteristics of holistic management, multi-targets, multi-pathways, and multi-links, and has become the primary source for the exploration of new drugs by researchers. There are a variety of TCMs that can treat kidney failure, such as
Network pharmacology is a method for network analysis of biological systems based on the theory of systems biology. At present, network pharmacology, as a new and advanced analytical technique, is widely used in pharmacological research, with its superior reliability and efficiency, and is the current research frontier of TCM [24]. Network pharmacology integrates the ideas of systems biology and multidirectional pharmacology to analyze the mechanism of action of drugs by constructing complex drug-ingredient–target-disease networks, enabling pharmacological research to shift from the traditional search for a single target to comprehensive network analysis [25]. The complex chemical composition and multi-target and multi-level pharmacological effects of Chinese herbs are naturally compatible with network pharmacology. In this study, we comprehensively analyzed the mechanism of action of
The purpose of this study was to comprehensively uncover the active ingredients, distinct targets, and accurate molecular mechanism of
Material and Methods
:
With reference to published articles, cordycepin, adenosine, and cordycepic acid were considered likely to be the 3 key active ingredients of Cordyceps cicadae that exert therapeutic effects by targeting diverse proteins. Subsequently, a crucial step was to identify the molecular targets that could disclose the pharmacological mechanisms of Cordyceps cicadae. In this study, using the 3D structural data of the 3 ingredients (Figure 1) obtained in PubChem (PubChem: https://pubchem.ncbi.nlm.nih.gov/), the target prediction was completed based on the PhammerMap database (PhammerMap: http://lilab-ecust.cn/pharmmapper/) and the SwissTargetPrediction database (SwissTargetPrediction: http://www.swisstargetprediction.ch/). Due to the irregular description of the identified candidate targets, the UniProtKB database (UniProtKB: www.uniprot.org/) [26] was used to standardize the candidate targets under the category of “Homo sapiens”. Finally, the unified candidate targets and their gene symbols were obtained from the database.
IDENTIFYING THE TARGETS OF RENAL IR:
The target genes related to renal IR were screened from GeneCards (http://www.genecards.org/). This human gene database is user-friendly, integrative, and searchable. Integrative information in relation to all annotated human diseases, proteins, and genes is available from this database [27]. The database encompasses diverse resources from 125 databases, including NCBI, HGNC, UniProtKB, and ENSEMBL, as well as multitudinous other relevant databases [28]. It is highly reliable in terms of data reliability. Using GeneCards, the information about related targets can be easily retrieved by keyword search, and we identified 1497 renal IR-related targets using the keywords “kidney ischemia reperfusion” and “renal ischemia reperfusion”.
CONSTRUCTING THE INGREDIENT–TARGET (I-T) NETWORK:
To better understand and analyze the molecular mechanism, the visualization software Cytoscape 3.7.2 was used in this study to construct an I-T network. The candidate ingredients targets and renal IR targets were retrieved to obtain the related targets shared with them. The ingredients and the shared targets were then used to map the I-T interaction network using the software. An attribute circle layout algorithm was used when building the network. To arrange each node reasonably and achieve clearer and understandable visualization effect, users can set each node and symbol with appropriate geometric position and set the network topology with personalized graphics and colors through Cytoscape [29]. The importance of every target and ingredient can be estimated by the 2 most critical parameters, degree and betweenness centrality, of the topology. Consequently, the ingredients and targets of Cordyceps cicadae exerting the core effect against renal IR were analyzed and identified.
CONSTRUCTING THE PROTEIN–PROTEIN INTERACTION (PPI) NETWORK:
It is difficult to individually identify specific proteins functions; the proteins mostly constitute macromolecular complexes by interacting with each other in intracellular biochemical processes to complete biological functions. Exploring protein–protein interactions is essential to reveal pharmacodynamic mechanisms, optimize drug efficacy, and reduce adverse effects. To systematically clarify the protein–protein interactions, the relevant targets were retrieved using Search Tool for the Retrieval of Interacting Genes/Proteins (STRING; Version 11.0; https://string-db.org/) to construct the PPI network. The STRING database is generally applied to retrieve and construct PPI networks, and its results are derived from experimental research data, literature mining, bioinformatics predictive analysis, and other relevant databases [30]. With STRING’s inherent scoring criteria, the higher the score setting, the higher the reliability of the predicted PPI results. Hence, the lowest score was set at a confidence of 0.4 to guarantee the reliability of the prediction results. The proteins isolated were removed from the network. Finally, the PPI network was the output, and statistical analyses of the PPIs were conducted. The proteins in the network are represented by nodes, while the edges indicate the association among proteins.
GO AND KEGG ENRICHMENT ANALYSIS:
GO analysis is a common approach to describe and annotate the biological processes, cellular components, and molecular functions of genes and gene products [31]. The KEGG is a useful resource that helps to systematically analyze gene functions and related advanced genome functions information [32,33]. In the study, we mainly explored the biological effects of Cordyceps cicadae and realized enrichment analysis by using 3 packages of R software (version “3.6”): (1) “DOSE”, an R package that explores the similarities in diseases and gene functions from a disease perspective by computing semantic similarity involving genes and disease ontology terms [34]; (2) “clusterProfiler”, an R package that mainly functions to compare biological themes and the enrichment analyses of gene clusters [35]; and (3) “pathview”, the R package that can visualize as well as integrate data according to the known pathways [36].
Results
TARGET IDENTIFICATION AND ANALYSIS:
After previous target fishing, it was forecast that 288 targets interacted with the 3 active compounds identified in Cordyceps cicadae. Using keywords retrieval, 1497 genes with relevant to the pathogenesis and progression of renal IR were screened by GeneCards database. By combining the active compounds targets of Cordyceps cicadae with renal IR-related targets, 81 targets shared among them were identified to be potential targets for treating renal IR (Figure 2A), and the details are presented in Supplementary Table 1. From the perspective of network topology, the key targets of the network are regarded as the cores, so the 81 targets determined in this study could be considered as the effective targets for Cordyceps cicadae in the treatment of renal IR.
I-T NETWORK CONSTRUCTION AND ANALYSIS:
To comprehend the relationships between the active components in Cordyceps cicadae and their potential targets common to renal IR, we constructed an I-T network of interactions between ingredients and targets, where every one of the ingredients was connected to its potential targets. The targets, interactions, and active ingredients presented in Figure 2B refer to the 3 active ingredients of Cordyceps cicadae respectively mapped to 81 potential targets. The ingredients and targets are indicated by yellow nodes and green nodes, respectively. And the interactions among the nodes are represented by the edges. The degree of an ingredient node is usually considered to reflect its potential value in drugs. The I-T network analysis showed that adenosine had the highest degree (degree=50), followed by cordycepic acid (degree=36) and cordycepin (degree=13), suggesting the priority of their potential value. Moreover, out of the 81 potential target genes, a total of 8 genes (IL-10, TGM3, MAOA, SMURF2, DPP4, CA2, CA1, and CA9) were linked to 2 ingredients, and 5 genes (TGM2, ERBB4, PTGIS, IGF1R, and SIRT3) were linked to 3 ingredients, indicating that these genes might be crucial in repairing renal IR.
PPI NETWORK CONSTRUCTION AND ANALYSIS:
To better analyze and understand the therapeutic mechanism of Cordyceps cicadae, the PPI network of the targets for the treatment of renal IR was constructed. The confidence level was set above 0.4, and the proteins independent of the network were removed. Then, 75 proteins with 377 relationships were obtained by PPI network analysis (Figure 3A). The priority of key proteins was analyzed by the degree of nodes output by the STRING database. Among them, the ALB value (degree=43) was the highest, followed by GAPDH (degree=39), CASP3 (degree=28), MAPK1 (degree=28), FN1 (degree=27), and IL-10 (degree=27), indicating that these proteins might act as bridges to other nodes in the PPI network (Figure 3B).
GENE ONTOLOGY FUNCTIONAL ENRICHMENT ANALYSIS:
To verify whether the 81 shared targets are associated with renal IR, GO functional enrichment analysis was carried out with R software 3.60, and the associated biological processes were clarified using the “DOSE” and “clusterProfiler” packages. Figure 4A displays the first 30 most significantly enriched GO terms, including biological processes (BP), molecular function (MF), and cellular component (CC) (P value ≤0.01). Supplementary Table 2 provides the P values, q-values, and counts of the remarkable enrichment items in BP, CC, and MF. The results indicate that the development of renal IR is regulated by many specific biological activities, including those involved in adenosine receptor signaling pathway (GO: 0001973), regulation of inflammatory response (GO: 0050727), regulation of body fluid levels (GO: 0050878), and response to hypoxia (GO: 0001666). Figure 4B presents the first 8 most significantly enriched GO terms in a circle-plot style. Among them, combined with the previous research results of our team [37], we focused on the adenosine receptor signaling pathway (GO: 0001973) and present the possible regulatory mechanism in Figure 5.
KEGG ENRICHMENT ANALYSIS OF PATHWAYS:
The pathways correlated to Cordyceps cicadae were obtained using the KEGG pathway enrichment analysis via R software 3.6.0. The significant pathways were enriched, and their corresponding P values were computed (calibrated by the Bonferroni method, the pathways with P values ≤0.01 were regarded as remarkable enrichment items). After sorting the P values, the first 30 pathways were shown in Figure 6A. Supplementary Table 3 provides the P values, q-values, and counts of the prominent enrichment pathways. The results indicated that multiple pathways participated in the process of renal IR, such as the cAMP signaling pathway (hsa04024), MAPK signaling pathway (hsa04010), PPAR signaling pathway (hsa03320), HIF-1 signaling pathway (hsa04066), and Rap1 signaling pathway (hsa04015). Figure 6B presents the first 8 most significantly enriched KEGG pathways in a circle-plot style.
Discussion
Renal IRI often occurs after recovery from renal ischemia, usually in septicemia, hypovolemic shock, and kidney transplantation [2]. In kidney transplant patients, IRI can lead to delayed graft function and cause a variety of long-term and short-term complications, thereby shortening the long-term survival rate of patients and bringing a heavy financial and medical burden to families and society [6,38]. Clinically, anti-oxidation, anti-inflammatory, inhibiting apoptosis, and improving renal perfusion are usually used for treatment. However, there is currently no treatment plan to completely avoid renal reperfusion injury. In China,
Cordycepin, adenosine, and cordycepic acid are the most important potential components of
With the results of I-T network analysis, 5 genes (TGM2, ERBB4, PTGIS, IGF1R, and SIRT3) were noted to be linked to the 3 active compounds identified, which indicated that these 3 components of
PPI network analysis showed that the protein node ALB had the highest value (degree=43), followed by GAPDH (degree=39), CASP3 (degree=28), MAPK1 (degree=28), FN1 (degree=27), and IL-10 (degree=27), indicating that these proteins might act as bridges connecting to other nodes in the PPI network (Figure 3B). In a related study, NO produced by IRI induced GAPDHS-nitrosylation at cysteine 150, which binds GAPDH to Siah1 (an E3 ubiquitinase), binds, promoting nuclear transformation of GAPDH, and then causing apoptosis [70]. Another study demonstrated that pre-silencing of GAPDH in cardiomyocyte IR by siRNA increased the autophagy in injured cells and the level of oxidative protective factors such as superoxide dismutase (SOD) and glutathione, and decreased the production of ROS, thereby alleviating the damage of cells and tissue caused by IRI [71]. CASP3 is a key protease involved in the caspase-dependent apoptosis pathway. It has been found that the expression of caspase-3 in renal IR increases significantly [72]. Deletion of the CASP3 gene can increase the levels of urinary cystatin C and serum creatinine and the increase the score of renal tubular injury in the early stage of AKI, and promote the death of renal tubular epithelial cells, while in long-term studies, it decreased the expression of α-smooth muscle actin and collagen deposition in peri-tubular capillaries, thus attenuating the degree of renal fibrosis [73]. Animal studies of renal fibrosis found that the expression of fibronectin 1 (FN1) generally increases with the increase of renal fibrosis [74]. Mitogen-activated protein kinases (MAPKs), including extracellular signal-regulated kinases 1 and 2 (ERK1/2), the c-Jun N-terminal kinases (JNK), and p38 mitogen-activated protein kinases (p38-MAPK), participate in proliferation and differentiation in the process of renal growth and development, and also exert an important role in a variety of renal injuries such as inflammation, apoptosis, and fibrosis [75]. During IRI, ERK2 (MAPK1) can minimize H2O2-induced cell damage [76] and contribute to the healing of damaged renal tubular epithelial cells [77]. However, other scholars have found that decreasing the expression of ERK2 in mouse kidneys clearly diminished IRI and the production of associated inflammatory factors during renal IRI [78]. Interleukin (IL)-10 is a classic anti-inflammatory cytokine that can inhibit the production of various inflammation-related factors such as IL-1, TNF-α, IL-6, and IL-8 [79–82]. Meanwhile, in an animal study, the mRNA expression of IL-1, IL-6, TNF-α, and IL-18 was increased in mouse models of IL-10 gene knockout in the early stage of AKI [83]. Another study found that during the repair process of renal IRI, the expression of IL-10 increased, while the deletion of IL-10 gene increased the expression of pro-inflammatory factors such as TNF-α and IL-6, resulting in aggravated renal tissue injury [84]. In addition, increased expression of IL-10 has been confirmed to be effective in treatment of renal IRI [85,86].
The results of GO classification indicated that
According to the results of KEGG analysis, MAPK (hsa04010), cAMP (hsa04024), PPAR (hsa03320), Rap1 (hsa04015), and HIF-1 (hsa04066) signaling pathways are the primary pathways of
There are some deficiencies in the current research. First, the bioactive components actually absorbed by patients with renal IR may differ from those identified. Second, suppressor target genes and activated genes are difficult to distinguish. Furthermore, not all predictions were experimentally verified. Therefore, further research is needed to validate this TCM therapy.
Conclusions
The strategy of network pharmacology gives a new prediction method to mine the evidence of TCMs treatment mechanisms from an integrative point of view. Through target fishing and I-T network analysis, 3 active components of
Figures






Tables
Supplementary Table 1. Information of Cordyceps cicadae and Renal IR-related targets. By combining the related targets of active ingredients of Cordyceps cicadae and the disease related targets, 81 overlapping targets were selected as the key targets in the treatment of renal IRI.

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