DOI: 10.57760/sciencedb.35699
title: Under the category of traditional Chinese medicine's analogical thinking, the protein-protein interaction network of "treating skin with skin", the pathway map of enrichment analysis, and the complex network diagram of "core drug-component-target-pathway"
title: 中医类象思维下“以皮治皮”的蛋白互作网络、富集分析通路图 、“核心药物-成分-靶点-通路”复杂网络图

description: The intersection of targets corresponding to 15 high-frequency drugs and high-frequency traditional Chinese medicines (TCMs) with disease-specific targets yielded a total of 397 targets. Among them, the intersection of targets from six core bark TCMs and disease targets yielded 212 "drug-disease" intersecting targets, accounting for 53.4% of the total intersecting targets between high-frequency drugs, high-frequency TCMs, and diseases. This fully demonstrates the significant role of the six core bark TCMs in the treatment of Alzheimer's Disease (AD). The intersecting target genes selected from the intersection of AD and core prescription drug components were imported into the String platform, with the species selected as Homo sapiens. This resulted in the construction of a protein-protein interaction (PPI) network. Using the CentiScaPe 2.2 component of Cytoscape 3.10.1 software, relevant parameters of the intersecting targets were calculated. Core targets were selected based on the criteria of degree ≥26.437, betweenness centrality ≥247.136, and closeness centrality ≥0.002 (all values rounded to three decimal places). The 212 intersecting targets were analyzed using the String platform, with the species selected as Homo sapiens, to obtain the PPI network diagram. The network analysis results showed that the network, under the system's default medium confidence level (0.4), contained 212 nodes (representing protein molecules) and 2,723 edges (representing interactions between proteins), with an average node degree of 25.9 and an average local clustering coefficient of 0.554. In the graph, nodes represent proteins, and edges represent relationships between proteins. The more edges between two nodes, the darker the color, indicating a greater correlation between their interactions. Subsequently, a biological pathway enrichment analysis was conducted, and the most representative human (hsa) biological species metabolic pathways among the enriched pathway results were analyzed based on their P values, Count values, etc. Finally, using Cytoscape 3.10.1 software, a "core drug-component-target-pathway" complex network diagram was generated to complete the visual analysis. Further analysis of the KEGG-hsa05200-organism-specific pathway (ORG) anchors gene and target information to specific biological functional pathways, facilitating the exploration of the association between core functions and diseases and enabling further interpretation from "gene list" to "functional mechanism". The analysis results of KEGG-hsa05200 (Figure 12) indicate that there is a significant relationship between multiple genes and positive regulation of phosphorylation between the cytoplasm and the nucleus, which is closely related to the cAMP signaling pathway, PI3K-Akt signaling pathway, and MAPK signaling pathway. The downstream processes within the nucleus are mostly indirectly regulating various processes such as cell cycle, apoptosis, and autophagy. The KEGG-hsa05200-ORG diagram integrates core signaling axes such as PI3K-Akt, MAPK, NF-κB, and JAK-STAT. These pathways are not only the main downstream transmission pathways of IL-6, TNF, and IL-1β, but also the core regulatory network for keratinocyte activation, immune cell infiltration, and inflammation persistence in AD. IL-6 regulates immune imbalance in AD through the hsa05200 core branch JAK2-STAT3 pathway; TNF-α activates the NF-κβ and MAPK pathways in hsa05200 by binding to Tumor Necrosis Factor Receptor 1/2 (TNFR1/2), upregulating Matrix Metalloproteinases (MMPs) and Cyclooxygenase-2 (COX-2), which can amplify the dominant immune response in AD, disrupt the skin barrier, and promote the release of inflammatory mediators; IL-1β, as a core immune factor, activates the NF-κβ and p38-MAPK signaling pathways in hsa05200 through the MyD88-dependent pathway, inducing keratinocytes to secrete secondary inflammatory factors such as IL-6. The disease name of AD, six high-frequency core traditional Chinese medicine (TCM) dermatological drugs, and their corresponding 46 main active ingredients, 781 gene targets, top 20 enriched analysis pathways, and core targets on each pathway were imported into Cytoscape 3.10.1 to construct a biological information network, as shown in Figure 13. In this network diagram, the node degree value represents the number of lines connected to the node in the network. The higher the degree value, the higher the correlation and the more prominent the key role. The red circular target in the figure represents the disease AD, the yellow diamond target represents the core composition of dermatological drugs, the peripheral green irregular target represents the main active ingredients of the drugs, and the blue square target represents the target genes. The results showed that the network contained a total of 854 nodes and 1,911 edges, with a network centralization index of 0.182 and a characteristic path length of 3.985. In the visualization results, the red circular targets represent the disease AD, the yellow diamond targets represent the core skin drug components, the peripheral green irregular targets represent the main active ingredients of the drugs, and the blue square targets represent the target genes. The relationships between nodes are closely connected. The node degree value represents the number of lines connected to the node in the network. The larger the degree value, the higher the correlation and the more prominent the key role. According to the CentiScaPe 2.2 platform-assisted calculation, the degree threshold of this network is 4.475, the betweenness centrality threshold is 2,546.473, and the closeness centrality threshold is 2.975. The top three degree values are all drug components, namely vitamin E (159), vitamin B (134), and trigonelline (111).
description: The intersection of targets corresponding to 15 high-frequency drugs and high-frequency traditional Chinese medicines (TCMs) with disease-specific targets yielded a total of 397 targets. Among them, the intersection of targets from six core bark TCMs and disease targets yielded 212 "drug-disease" intersecting targets, accounting for 53.4% of the total intersecting targets between high-frequency drugs, high-frequency TCMs, and diseases. This fully demonstrates the significant role of the six core bark TCMs in the treatment of Alzheimer's Disease (AD). The intersecting target genes selected from the intersection of AD and core prescription drug components were imported into the String platform, with the species selected as Homo sapiens. This resulted in the construction of a protein-protein interaction (PPI) network. Using the CentiScaPe 2.2 component of Cytoscape 3.10.1 software, relevant parameters of the intersecting targets were calculated. Core targets were selected based on the criteria of degree ≥26.437, betweenness centrality ≥247.136, and closeness centrality ≥0.002 (all values rounded to three decimal places). The 212 intersecting targets were analyzed using the String platform, with the species selected as Homo sapiens, to obtain the PPI network diagram. The network analysis results showed that the network, under the system's default medium confidence level (0.4), contained 212 nodes (representing protein molecules) and 2,723 edges (representing interactions between proteins), with an average node degree of 25.9 and an average local clustering coefficient of 0.554. In the graph, nodes represent proteins, and edges represent relationships between proteins. The more edges between two nodes, the darker the color, indicating a greater correlation between their interactions. Subsequently, a biological pathway enrichment analysis was conducted, and the most representative human (hsa) biological species metabolic pathways among the enriched pathway results were analyzed based on their P values, Count values, etc. Finally, using Cytoscape 3.10.1 software, a "core drug-component-target-pathway" complex network diagram was generated to complete the visual analysis. Further analysis of the KEGG-hsa05200-organism-specific pathway (ORG) anchors gene and target information to specific biological functional pathways, facilitating the exploration of the association between core functions and diseases and enabling further interpretation from "gene list" to "functional mechanism". The analysis results of KEGG-hsa05200 (Figure 12) indicate that there is a significant relationship between multiple genes and positive regulation of phosphorylation between the cytoplasm and the nucleus, which is closely related to the cAMP signaling pathway, PI3K-Akt signaling pathway, and MAPK signaling pathway. The downstream processes within the nucleus are mostly indirectly regulating various processes such as cell cycle, apoptosis, and autophagy. The KEGG-hsa05200-ORG diagram integrates core signaling axes such as PI3K-Akt, MAPK, NF-κB, and JAK-STAT. These pathways are not only the main downstream transmission pathways of IL-6, TNF, and IL-1β, but also the core regulatory network for keratinocyte activation, immune cell infiltration, and inflammation persistence in AD. IL-6 regulates immune imbalance in AD through the hsa05200 core branch JAK2-STAT3 pathway; TNF-α activates the NF-κβ and MAPK pathways in hsa05200 by binding to Tumor Necrosis Factor Receptor 1/2 (TNFR1/2), upregulating Matrix Metalloproteinases (MMPs) and Cyclooxygenase-2 (COX-2), which can amplify the dominant immune response in AD, disrupt the skin barrier, and promote the release of inflammatory mediators; IL-1β, as a core immune factor, activates the NF-κβ and p38-MAPK signaling pathways in hsa05200 through the MyD88-dependent pathway, inducing keratinocytes to secrete secondary inflammatory factors such as IL-6. The disease name of AD, six high-frequency core traditional Chinese medicine (TCM) dermatological drugs, and their corresponding 46 main active ingredients, 781 gene targets, top 20 enriched analysis pathways, and core targets on each pathway were imported into Cytoscape 3.10.1 to construct a biological information network, as shown in Figure 13. In this network diagram, the node degree value represents the number of lines connected to the node in the network. The higher the degree value, the higher the correlation and the more prominent the key role. The red circular target in the figure represents the disease AD, the yellow diamond target represents the core composition of dermatological drugs, the peripheral green irregular target represents the main active ingredients of the drugs, and the blue square target represents the target genes. The results showed that the network contained a total of 854 nodes and 1,911 edges, with a network centralization index of 0.182 and a characteristic path length of 3.985. In the visualization results, the red circular targets represent the disease AD, the yellow diamond targets represent the core skin drug components, the peripheral green irregular targets represent the main active ingredients of the drugs, and the blue square targets represent the target genes. The relationships between nodes are closely connected. The node degree value represents the number of lines connected to the node in the network. The larger the degree value, the higher the correlation and the more prominent the key role. According to the CentiScaPe 2.2 platform-assisted calculation, the degree threshold of this network is 4.475, the betweenness centrality threshold is 2,546.473, and the closeness centrality threshold is 2.975. The top three degree values are all drug components, namely vitamin E (159), vitamin B (134), and trigonelline (111).