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25 August 2026

38 Pages

Network Pharmacology-Based Exploration of Complementary Molecular Mechanisms of Heat-Clearing (Scutellariae Radix, Coptidis Rhizoma) and Blood-Tonifying Herbs (Angelicae Sinensis Radix, Paeoniae Radix Alba) in Cold Hypersensitivity in Hands and Feet

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1
Department of Korean Medicine, College of Korean Medicine, Sangji University, Wonju-si 26339, Republic of Korea
2
Department of Korean Language & Literature, College of Humanities, Sogang University, Seoul 04107, Republic of Korea
3
Department of Herbology, College of Korean Medicine, Sangji University, Wonju-si 26339, Republic of Korea
*
Author to whom correspondence should be addressed.
Life2026, 16(9), 1406;https://doi.org/10.3390/life16091406
This article belongs to the Special Issue Therapeutic Effects of Natural Products on Human Diseases—3rd Edition
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Abstract

Cold hypersensitivity in hands and feet (CHHF) affects 20–52% of East Asian populations, is more prevalent in women, and is managed with vasodilators in Western medicine or herbal therapies in traditional East Asian medicine. This study was conducted to compare the pharmacological characteristics of two heat-clearing (HCHs, Scutellariae Radix and Coptidis Rhizoma) and two blood-tonifying (BTHs, Angelicae Sinensis Radix and Paeoniae Radix Alba) herbs used for CHHF. Candidate herbs were selected based on herbology classifications, PubMed searches, and the Korean Medicine Clinical Practice Guideline for CHHF. A total of 61 active compounds and 323 corresponding protein targets with CHHF were retrieved from the traditional Chinese medicine systems pharmacology database and analysis platform (TCMSP), standardized via UniProt, and intersected with CHHF-related genes from GeneCards. Protein–protein interaction networks were constructed, core targets identified, and functional enrichment analyses performed using Reactome databases. A total of 166 herb–CHHF common targets were identified, including 24 shared across all four herbs. HCHs were primarily enriched in hemostasis-, immune-, and signaling-related pathways, whereas BTHs were associated with immune regulation, metabolism, and neuronal modulation. Notably, Scutellariae Radix and Paeoniae Radix Alba showed substantial overlap in enriched pathways. These findings suggest that HCHs and BTHs may be associated with distinct yet potentially relevant molecular mechanisms in CHHF. However, because the present analysis was conducted at the single-herb level, these findings cannot be directly generalized to the clinical use of multi-herb formulas and should be interpreted as hypothesis-generating.

1. Introduction

Cold hypersensitivity is a condition in which specific parts of the body feel unusually cold and painful, even at temperatures that would not normally provoke such sensations, making it difficult to maintain daily activities [1]. Cold hypersensitivity primarily arises from impaired blood circulation and reduced heat production, but it can also be induced by a wide range of underlying factors. Common contributors include decreased physical strength due to gastrointestinal disturbance, anemia, hypotension, capillary constriction caused by dysautonomia, pelvic congestion, and disturbances in body fluid metabolism. Various disorders—such as Raynaud’s phenomenon (RP), peripheral neuritis, polyneuropathy, and carpal tunnel syndrome—can also elicit cold hypersensitivity. CHHF is generally defined as a subjective sensation of coldness in the hands or feet, and it may present as coldness limited to the hands, to the feet, or involving both the hands and feet [2]. This condition is commonly observed in approximately 20–52% of East Asian populations, and a twin-based genetic study conducted in Korea reported a female-to-male ratio of 3:2 in CHHF prevalence, indicating increased rates among women [3]. According to the Clinical Practice Guideline of Korean Medicine for Cold Hypersensitivity in Hands and Feet (hereafter CPG of CHHF), this condition is not classified as an independent disease entity. CHHF is defined as a clinical category that includes primary RP and other peripheral cold-related disorders, while excluding secondary RP caused by identifiable underlying diseases [1]. Therefore, CHHF is not synonymous with RP but represents a broader clinical spectrum, within which primary RP is considered a subtype. Although research articles and reviews related to CHHF have been steadily increasing, a clear and universally accepted definition of CHHF has not yet been established [4].
In Western medicine, CHHF is regarded as one of the representative clinical manifestations of RP, and most patients with CHHF are prescribed antihypertensive or vasodilatory agents [4]. Traditional East Asian medicine—including Traditional Chinese Medicine (TCM), KM, and Japanese Kampo Medicine—interprets “Cold (冷)” as a major pathogen [4]. From the perspective of Yin–Yang theory, depletion of Yang-qi and predominance of Yin-qi result in a decline in body temperature [4]. Consequently, traditional East Asian medical systems emphasize a holistic and individualized approach aimed at restoring the balance of Yin and Yang as a central therapeutic strategy for CHHF [4]. In Korean Medicine (KM), cold hypersensitivity is understood to result from disruptions in the circulation of qi and blood or deficiencies of qi, blood, and yang due to pathological patterns such as spleen-yang deficiency, kidney-yang deficiency, blood stasis, blood deficiency, qi deficiency, or water poisoning [2]. Previous studies have suggested that herbal medicines rooted in traditional East Asian medicine have the potential to serve as safe and effective treatment options for CHHF [4].
Unlike conventional pharmaceuticals, which typically contain a single active ingredient designed to target a specific molecular pathway, herbal medicines consist of multiple bioactive compounds and are known to modulate various biological targets simultaneously [5]. In other words, the pharmacologically active compounds of medicinal herbs exert broad therapeutic effects through various pathways, while showing minimal adverse reactions in the human body [6]. Herbal medicines are categorized into several groups, among which Heat-Clearing Herbs (淸熱藥, HCHs) represent one major category. Most herbs within this group possess a cold nature (寒性) and function to eliminate heat, drain pathogenic fire (火), dry dampness, cool the blood, and detoxify harmful substances. Their primary therapeutic action is to dispel internal heat. In this context, the concept of “heat” or “fire” corresponds to fever associated with inflammatory conditions [7]. Accordingly, HCHs are currently recognized and utilized for their anti-inflammatory and inflammation-modulating properties.
According to the study by Chang et al. [8], the pathogenesis of CHHF may involve increased sympathetic activity and exaggerated dysfunction of endothelial cells (ECs). A study has reported that herbal medicines exert effects such as modulation of sympathetic nervous system activity [9]. While CHHF has traditionally been classified as a cold pattern (寒證) and treated mainly with warming methods (溫法) using interior-warming herbs [2], modern pharmacological studies on representative HCHs and their constituents have suggested modulation of sympathetic activity, along with anti-inflammatory and vascular effects [10]. Traditionally, HCHs have been used to drain (瀉) pathogenic “heat (熱)” from the body. Accordingly, this study explored the potential mechanisms underlying HCHs using a network pharmacology approach grounded in these conceptual perspectives.
In RP, CHHF is attributed to recurrent and reversible excessive vasoconstriction of peripheral vessels, impaired blood flow, and endothelial dysfunction [10].
Endothelial dysfunction involves key vasoconstrictive mediators such as endothelin-1, angiotensin II, and angiopoietin-2. Endothelin-1 is a major endothelium-derived vasoconstrictor, and patients with RP exhibit reduced endothelium-dependent vasodilation, which contributes to digital ischemia [10]. The expression of these vasoconstrictors has been reported to be upregulated by pro-inflammatory cytokines, including tumor necrosis factor-α (TNF-α) and interferon-γ (IFN-γ) [11]. This suggests that CHHF is closely related not only to vascular dysfunction but also to inflammatory responses.
The pathophysiology of endothelial dysfunction is further associated with p38 mitogen-activated protein kinase (p38 MAPK) activation [12].
Recent studies suggest that microvascular stabilization mechanisms, including endothelial cell (EC)–pericyte interactions, play an important role in maintaining peripheral blood flow. CXCR3–CXCL11 signaling has been implicated in regulating EC proliferation and pericyte recruitment [13].
In addition, dysautonomia-related CHHF has been associated with sympathetic overactivity, in which α2-adrenergic receptors (α2-ARs), particularly the α2A-AR subtype, mediate rapid vasoconstriction in cutaneous vessels [8,14,15].
Herbal medicines consist of complex mixtures of compounds that act on multiple pathological targets and pathways. Conventional pharmacological approaches therefore have limitations in elucidating their mechanisms of action [16]. In 2013, Shao Li proposed the concept of “network pharmacology,” offering a new strategy for uncovering the mechanistic basis of herbal formulas [17]. Network analysis and network pharmacology utilize database mining and bioinformatic computation to analyze and simulate human protein–protein interaction (PPI) networks, thereby revealing the complex interaction patterns between drugs and diseases [18].
Network pharmacology has increasingly been applied to investigate the mechanisms underlying the therapeutic effects of herbal medicines in various diseases [19], and this approach is particularly suited to herbal medicine research because it enables the systematic analysis of multiple components, pathways, and targets [19,20].

2. Materials and Methods

Herbs were chosen by literature screening (PubMed, National Clearinghouse for Korean Medicine (NCKM)). Herb compounds and targets (TCMSP) were standardized (UniProt) and intersected with CHHF targets (GeneCards) using Venny 2.1. Protein–protein interaction (PPI) networks (search tool for the retrieval of interacting genes/proteins (STRING)), core-gene analysis (Cytoscape network centrality analysis (CytoNCA 2.1.6)), visualization (Cytoscape 3.10.3), and pathway enrichment analysis (Reactome) were performed. The overall workflow of the network pharmacology and pathway enrichment analyses is illustrated in Figure 1.
Figure 1. Schematic workflow of the network pharmacology and pathway analysis.

2.1. Selection of Herbal Medicines for Analysis

2.1.1. Selection of Heat-Clearing Herbs: PubMed

In this study, herbal medicines classified as “Heat-Clearing Herbs” in Herbology [21] were selected as the target group for analysis. Candidate herbs were identified through a literature search of the PubMed database (https://pubmed.ncbi.nlm.nih.gov/ (accessed on 2 August 2025)). Searches were conducted by combining the English names of the herbs with clinical and pathophysiological terms related to CHHF, including “primary Raynaud’s phenomenon”, “peripheral mechanism”, “increased vasoconstriction”, “sensitive to cold”, and “hot flushes” using the OR operator.
This search strategy was based on the fact that CHHF is not typically reported as an independent disease entity but rather described under various diagnoses or clinical/pathophysiological terms such as primary RP or other specified peripheral vascular disorders.
Accordingly, key symptoms associated with CHHF were identified through a review of the relevant academic literature, and these were used as search terms. Based on the search outcomes, the two most frequently appearing herbs were selected as the final target herbs for this study.

2.1.2. Selection of Commonly Used Herbal Medicines for CHHF: Clinical Practice Guideline of Korean Medicine—CHHF Figures, Tables, and Schemes

Clinical practice guidelines (CPGs) are evidence-based documents developed through systematic and scientific processes to assist healthcare providers and patients in making informed decisions throughout medical care [2].
To identify herbal medicines commonly used in clinical practice for CHHF, we collected prescriptions recommended in the Clinical Practice Guideline of Korean Medicine for Cold Hypersensitivity in Hands and Feet (hereafter CPG of CHHF). The CPG of CHHF is available from the NCKM (https://nikom.or.kr/nckm/index.do (accessed on 2 August 2025)). Prescriptions with an evidence-based recommendation grade of C or higher, or a consensus-based recommendation grade of GPP, were included.
Subsequently, all constituent herbs from the prescriptions listed in the CPG of CHHF were extracted. The names of herbal medicines were standardized based on Herbology [21]. According to this text, “Peony root (芍藥, Paeoniae Radix)” is not listed as an independent item; instead, it is categorized either as White Peony root (白芍藥, Paeniae Radix Alba) under blood-tonifying herbs (補血藥, BTHs) or as Red Peony root (赤芍藥, Paeoniae Radix Rubra) under heat-clearing and blood-cooling herbs (淸熱凉血藥). For each prescription, the source was therefore reviewed to determine whether Peony root referred to White or Red Peony root.
Additionally, because “Red Poria (赤茯苓; in Korea, the light reddish portion beneath the outer peel (皮層) is referred to as 赤茯苓)” is not listed separately in the Herbology table of contents, it was integrated into “Poria (茯苓, Poria Sclerotium).” Although Korean Red Ginseng (紅蔘, Ginseng Radix Rubra, steamed and dried ginseng prepared after removing the fine rootlets (鬚根) of Ginseng Radix) is not listed as a separate item in Herbology, it was not merged with Ginseng (人蔘), as the CPG of CHHF identifies “Korean Red Ginseng granule” as distinct from Ginseng used in other prescriptions.
The standardized herbal names were then sorted by frequency, and the top two herbs were selected as the final study targets. Licorice (甘草, Glycyrrhizae Radix et Rhizoma) was excluded because it is used extremely broadly as a harmonizing herb (調和諸藥); it appears in 70 out of the 113 prescriptions in the Shanghanlun (傷寒論) [22].

2.2. Collection of Active Compounds and Target Gene/Protein Data: TCMSP

Data on the active compounds and target gene/protein information of the selected herbal medicines were collected through searches in the TCMSP (https://www.tcmsp-e.com/ (accessed on 2 August 2025)). TCMSP is a systems pharmacology platform that provides information about herbal ingredients, their corresponding molecular targets, and associated diseases. It contains data on 499 herbs, 29,384 compounds, and 3311 target proteins, as well as 12 key ADME (absorption, distribution, metabolism, and excretion) characteristics that describe the pharmacokinetic properties of each compound [23].
According to previous research, approximately one-third of studies using TCMSP apply compound-selection criteria of oral bioavailability (OB) ≥ 30% and drug-likeness (DL) ≥ 0.18 [24]. In the present study, active compounds were therefore selected based on these same criteria.
Next, the “Target Name” corresponding to each active compound was collected from the TCMSP database. To standardize protein names for the target proteins associated with the active compounds, each Target Name obtained from TCMSP was searched in the UniProt database (Database of Protein Sequences, https://www.uniprot.org/ (accessed on 2 August 2025)). Only entries with a status of “Reviewed (Swiss-Prot)” and classified under “Human” in the Popular Organisms’ category were included. From the resulting matches, proteins whose Protein Names exactly corresponded to the queried Target Name were selected, and their Entry (UniProt ID) and Gene Names were retrieved.

2.3. Collection of Target Gene/Protein Data for CHHF: GeneCards

Target genes associated with CHHF were collected by searching the human gene database GeneCards (https://www.genecards.org/ (accessed on 2 August 2025)) using the keyword “cold hypersensitivity in hands and feet.” Protein entries without UniProt IDs and duplicated data were excluded from the dataset.

2.4. Network Pharmacology Analysis

2.4.1. Collection of Common Herb–CHHF Target Proteins: Venny, Cytoscape

To identify the common target proteins shared between each herbal medicine and CHHF, Venny 2.1.0 (https://bioinfogp.cnb.csic.es/tools/venny/ (accessed on 15 August 2025)) was first employed. All datasets were entered in UniProt ID format.
The overlapping target proteins between each herb and CHHF were then re-entered into Venny to examine the distribution and intersection patterns of proteins commonly targeted by the four herbs—Scutellariae Radix (黃芩), Coptidis Rhizoma (黃連), Angelicae Sinensis Radix (當歸), and Paeoniae Radix Alba (白芍藥).
The resulting common-target protein network was visualized using Cytoscape 3.10.3, an open-source software platform designed for analyzing, integrating, and visualizing biological interaction networks.

2.4.2. Protein–Protein Interaction (PPI) Network Analysis: STRING

Based on the common target proteins identified between each herbal medicine and CHHF using Venny 2.1.0, a PPI network analysis was conducted to explore the potential pharmacological mechanisms of the selected herbs.
The common target proteins were entered into the STRING 12.0 database (https://www.string-db.org/ (accessed on 27 August 2025)) in UniProt ID format to generate the PPI network. During this process, the organism was restricted to Homo sapiens, and the confidence threshold was set at a confidence score ≥ 0.7 (high confidence). All other parameters were maintained at their default settings.

2.4.3. Extraction of Core Genes

The structural characteristics of the PPI network were analyzed using PPI analysis results. The CytoNCA 2.1.6 plugin in Cytoscape 3.10.3 was used to calculate the topological properties of each node. Four key centrality parameters—betweenness (BC), closeness (CC), degree (DC), and eigenvector centrality (EC)—were applied.
The topological indices for each node were exported from Cytoscape as a table; then, Python 3.12 was used to determine and extract the core genes. Following the approach commonly used in previous network pharmacology studies [25,26,27,28,29], genes exceeding the median value across all four centrality indices (BC, CC, DC, and EC) were defined as core genes. Because each index reflects a distinct aspect of node importance within the network, this intersection-based approach was intended to minimize bias arising from reliance on a single index and to select only nodes that were consistently important across multiple topological criteria. The selection criteria for core genes for each herbal medicine are summarized in Table 1.
Table 1. Centrality measures used for the selection of core genes in herbal medicine.

2.4.4. Pathway Enrichment Analysis: Reactome (Home–Reactome Pathway Database)

To explore the molecular interaction pathways involved in the pathophysiology of CHHF, the common target proteins shared between each herbal medicine and CHHF—identified previously using Venny 2.1.0—were entered into the Reactome database (version 93; https://reactome.org/ (accessed on 25 August 2025)). Reactome is an open-source, open-access pathway database that provides biologically curated pathway information constructed through expert manual annotation and peer review [30].
For each herbal medicine, the common target proteins associated with CHHF were uploaded to Reactome in UniProt ID format to perform biological pathway enrichment analysis. From the resulting output, only the pathway identifier, pathway name, and false discovery rate (FDR) values of entities were extracted. The pathway identifier was used to classify each pathway according to its higher-level category.
After compiling the pathway names and FDR values of entities for all four herbs, only pathways with FDR values of entities < 0.05 were retained. The Reactome database contains 29 top-level pathway categories, among which five categories were selected for analysis based on their relevance to the known pathophysiology of CHHF.
In patients with RP, abnormalities in the coagulation system—such as platelet activation, increased blood viscosity, and microthrombus formation—have been observed [31], and these factors can be considered to be associated with the impaired blood flow observed in CHHF, which represents a clinical manifestation of RP. In addition, it has been reported that immune responses may partially contribute to the pathophysiology of RP [10]. Cold-induced vasoconstriction is mediated by redox signaling in vascular smooth muscle cells (VSMCs), during which mitochondrial ROS stimulate the RhoA/Rho kinase signaling pathway. This activation subsequently promotes the translocation of α2C-adrenergic receptors (α2C-ARs) to the cell surface, leading to vasoconstriction, a mechanism closely associated with CHHF [32].
Additionally, from a neurogenic perspective, exposure to cold or stress increases sympathetic nervous system activity, resulting in the release of norepinephrine, which activates postsynaptic α-adrenergic receptors on vascular smooth muscle and induces vasoconstriction, ultimately contributing to CHHF [33].
Repeated cycles of ischemia–reperfusion in RP have also been shown to generate excessive ROS, causing metabolic stress in affected tissues [33]. Based on these cumulative findings, five top-level pathway categories highly relevant to CHHF pathophysiology—Hemostasis, Immune System, Signal Transduction, Neuronal System, and Metabolism—were selected as the focus of the present analysis.

3. Results

3.1. Selection of Herbal Medicines

3.1.1. Selection of Heat-Clearing Herbs (淸熱藥): PubMed Search

According to the 『Herbology』 [21], a total of 52 herbal medicines are classified under the category of “heat-clearing herbs.” Each of these herbs was searched in PubMed using the following query: “(Herb name) AND ((primary Raynaud’s phenomenon) OR (peripheral mechanism) OR (increased vasoconstriction) OR (sensitivity to cold) OR (hot flushes)).”
The number of publications retrieved for each herb was summarized (Table 2), and Scutellariae Radix and Coptidis Rhizoma were ultimately selected as the target herbs for this study.
Table 2. Frequency of PubMed hits for candidate HCHs.

3.1.2. Selection of Commonly Used Herbal Medicines for CHHF

Based on the CPG of CHHF, a total of twelve prescriptions are recommended (with evidence-based recommendation grade ≥ C or consensus-based grade GPP) [2].
The first-line prescriptions include Dangguisayeoktang (當歸四逆湯), Dangguisayeokgaosuyusaengangtang (當歸四逆加吳茱萸生薑湯), Ongyeongtang (溫經湯), Korean Red Ginseng (紅蔘) granules, Gyejibokryeonghwan (桂枝茯苓丸), and Dangguijakyaksan (當歸芍藥散) [2].
In addition, Yijungtang (理中湯), Bojungigkitang (補中益氣湯), Sipjeondaebotang (十全大補湯), Ojeoksan (五積散), Palmijihwanghwan (八味地黃丸), and Gyejitang (桂枝湯) are recommended for use according to syndrome differentiation, based on formal expert consensus [2].
An analysis of these twelve prescriptions identified 37 constituent herbs. When sorted by frequency of occurrence, Licorice (甘草, Glycyrrhizae Radix et Rhizoma), White Peony root (白芍藥, Paeoniae Radix Alba), and Angelica gigas root (當歸, Angelicae Gigantis Radix) appeared in seven of the formulas. Considering the harmonizing property of Licorice (調和諸藥), it was excluded from the study. Consequently, Paeoniae Radix Alba and Angelicae Gigantis Radix were selected as the final target herbs.

3.2. Collection of Active Compounds and Target Proteins: TCMSP

Active compounds were retrieved from the TCMSP based on the criteria of OB ≥ 30% and DL ≥ 0.18.
The corresponding target genes and proteins related to these active compounds were also collected, and the results are summarized in Table 3. The active compounds are also listed in Table A1, Table A2, Table A3 and Table A4. Their biological activities and key findings are reported in Table A5.
Table 3. Active compounds and predicted protein targets of selected herbs from TCMSP.
In the case of Angelicae Gigantis Radix (Angelica gigas root, Danggui), the Korean Pharmacopoeia defines it as the root of Angelica gigas Nakai (Korean Danggui), whereas the Chinese Pharmacopoeia defines Danggui as the root of Angelica sinensis (Oliv.) Diels (Chinese Danggui). As only Chinese Danggui is available in the TCMSP database, the pharmacognostic name Angelicae Sinensis Radix was used in this study.
Subsequently, UniProt IDs of the target proteins were collected.
For several proteins that could not be precisely identified in the UniProt database, their UniProt IDs were determined through consensus among three independent researchers (Table 4).
Table 4. UniProt search results and final determination of IDs for proteins with ambiguous matches.

3.3. Collection of Target Proteins Related to CHHF: GeneCards

Target genes and proteins associated with CHHF in hands and feet were retrieved from the GeneCards database using the search term “cold hypersensitivity in hands and feet.”
Following the exclusion of entries without UniProt IDs and the removal of duplicates, a total of 2588 unique target proteins were finalized for further analysis starting from an initial pool of 2750 identified proteins.

3.4. Network Pharmacology Analysis

3.4.1. Identification of Common Target Proteins Between Herbal Medicines and CHHF: Venny

Common target proteins shared between the selected herbal medicines and CHHF were identified using Venny 2.1.0.
As a result, 84, 138, 66, and 35 overlapping target proteins were identified for Scutellariae Radix, Coptidis Rhizoma, Paeoniae Radix Alba, and Angelicae Sinensis Radix, respectively (Figure 2 and Table 5).
Figure 2. Venn diagrams showing overlapping targets between CHHF and selected herbs.
Table 5. Number of herb-derived targets and overlapping targets with CHHF.
The common target proteins shared between the herbal medicines and CHHF were reanalyzed using Venny, and the distribution and overlapping patterns of target proteins among the four herbal medicines were visualized with Cytoscape (Figure 3). Overlapping target proteins between CHHF and the four selected herbs are also listed in Table A6.
Figure 3. Network of overlapping targets between CHHF and four selected herbs visualized by Cytoscape. Green hexagons: four herbal medicines—Scutellariae Radix, Coptidis Rhizoma, Angelicae Sinensis Radix, and Paeoniae Radix Alba; Light blue squares: targets unique to a single herb; Pink squares: proteins targeted by two herbs; Yellow squares: proteins commonly targeted by three herbs; Purple squares: proteins shared by all four herbs.
In the network diagram, four green hexagons represent the four herbal medicines—Scutellariae Radix, Coptidis Rhizoma, Angelicae Sinensis Radix, and Paeoniae Radix Alba. Light blue squares indicate targets unique to a single herb, while pink squares represent proteins targeted by two. Yellow squares denote proteins commonly targeted by three herbs, and purple squares correspond to proteins shared by all four.
A total of 166 target proteins were identified from the four herbs, of which 85 were targeted by at least two herbs. In contrast, 81 proteins were uniquely targeted by a single herb, with Coptidis Rhizoma accounting for the largest proportion (61 unique targets). Notably, Angelicae Sinensis Radix had no unique targets. A total of 16 proteins were co-targeted exclusively by the two HCHs (Scutellariae Radix and Coptidis Rhizoma), whereas no targets were shared solely by the two BTHs (Angelicae Sinensis Radix and Paeoniae Radix Alba). A total of 18 proteins were co-targeted by Scutellariae Radix, Coptidis Rhizoma, and Paeoniae Radix Alba, and 24 were found to be common targets of all four herbs.

3.4.2. Protein–Protein Interaction (PPI) Network Analysis: STRING

The common target genes and proteins of the four herbs identified through Venny 2.1.0 were entered into the STRING 12.0 database to construct individual PPI networks for each herb (Figure 4).
Figure 4. Visualization of the common target genes and proteins of the four herbs (Scutellariae Radix, Coptidis Rhizoma, Angelicae Sinensis Radix, and Paeoniae Radix Alba). STRING 12.0 software was used to create the PPI network.
Among them, Coptidis Rhizoma exhibited the highest average node degree (16.5), indicating the most extensive PPI compared to the other herbs. In contrast, Angelicae Sinensis Radix showed the lowest average node degree (3.2), suggesting relatively limited interactions. Scutellariae Radix and Paeoniae Radix Alba displayed intermediate levels, with average node degrees of 10.6 and 7.03, respectively (Table 6).
Table 6. Number of nodes and core genes of selected herbs based on centrality measures.

3.4.3. Identification of Core Genes

Nodes with BC, CC, DC, and EC values higher than the median were defined as core genes.
The numbers of core genes identified for each herbal medicine are summarized in Table 6, and the corresponding protein interaction networks constructed based on these core genes are illustrated in Figure 5. Overlapping core genes between CHHF and the four selected herbs are also listed in Table A7.
Figure 5. Network of overlapping core genes between CHHF and four selected herbs (Scutellariae Radix, Coptidis Rhizoma, Angelicae Sinensis Radix, and Paeoniae Radix Alba) visualized by Cytoscape. Green hexagons: four herbal medicines—Scutellariae Radix, Coptidis Rhizoma, Angelicae Sinensis Radix, and Paeoniae Radix Alba; Light blue squares: targets unique to a single herb; Pink squares: proteins targeted by two herbs; Yellow squares: proteins commonly targeted by three herbs; Purple squares: proteins shared by all four herbs.

3.4.4. Pathway Enrichment Analysis: Reactome

The common target genes and proteins between each herbal medicine and CHHF were input into the Reactome Pathway Database (Home–Reactome Pathway Database) in UniProt ID format.
Among the biological pathways identified, only those with FDR values of entities < 0.05 were retained, resulting in 494 pathways belonging to 19 supercategories.
Of these, 233 pathways corresponding to the five major supercategories considered most relevant to CHHF—Hemostasis, Immune System, Signal Transduction, Neuronal System, and Metabolism—were selected for further analysis.
The number of pathways significantly associated with CHHF for each herbal medicine was as follows: Scutellariae Radix (153), Coptidis Rhizoma (188), Angelicae Sinensis Radix (44), and Paeoniae Radix Alba (144).
The number of pathways in each supercategory for each herb is summarized in Table 7, and the detailed distribution of enriched pathways is presented in Figure 6A–C.
Table 7. Pathway enrichment results of common targets between CHHF and selected herbs based on Reactome analysis.
Figure 6. Differences in molecular pathways among SR, CR, ASR, and PRA. SR: Scutellariae Radix; CR: Coptidis Rhizoma; ASR: Angelicae Sinensis Radix; PRA: Paeoniae Radix Alba. (A) Hemostasis, immune system-related molecular pathways. (B) Metabolism, neuronal system-related molecular pathways. (C) Signal transduction-related molecular pathways.
Comparison of shared pathways among the four herbs revealed that Scutellariae Radix and Coptidis Rhizoma shared 119 pathways; Scutellariae Radix and Angelicae Sinensis Radix, 44 pathways; Scutellariae Radix and Paeoniae Radix Alba, 116 pathways; Coptidis Rhizoma and Angelicae Sinensis Radix, 34 pathways; Coptidis Rhizoma and Paeoniae Radix Alba, 12 pathways; and Angelicae Sinensis Radix and Paeoniae Radix Alba, 36 pathways.
Notably, among the 116 pathways shared by Scutellariae Radix and Paeoniae Radix Alba, approximately 76% of those of the former and 80% of those of the latter overlapped, indicating a close mechanistic association between these two herbs in CHHF treatment.
All 44 pathways identified for Angelicae Sinensis Radix were shared with Scutellariae Radix, suggesting that the mechanisms of the former are largely encompassed within those of the latter.
A total of 34 pathways were found to be common to all four herbs.
When examined by supercategory, the number of significant pathways related to Hemostasis was nine for Scutellariae Radix, nine for Coptidis Rhizoma, four for Paeoniae Radix Alba, and null for Angelicae Sinensis Radix.
Among these, pathways directly associated with platelet activation and aggregation, integrin signaling, and fibrin clot formation were observed exclusively for Scutellariae Radix and Coptidis Rhizoma.
This finding suggests that Scutellariae Radix, while sharing mechanistic similarities with Paeoniae Radix Alba, also exhibits unique pathways related to blood coagulation and hemostasis in conjunction with Coptidis Rhizoma.
Regarding the proportions of pathways in the Immune System and Signal Transduction categories, Coptidis Rhizoma accounted for 76%, Paeoniae Radix Alba for 73%, Scutellariae Radix for 66%, and Angelicae Sinensis Radix for 55%.
Among them, Angelicae Sinensis Radix showed the lowest proportion of Immune System-related pathways (14%) but exhibited the highest proportions of Metabolism (27%) and Neuronal System (18%) pathways, indicating its relative emphasis on metabolic and neuroregulatory mechanisms compared with the other herbs.

4. Discussion

KM has played a significant role in health management and disease treatment across East Asia for over two millennia. Herbal medicine has been widely utilized for the prevention and treatment of various diseases, and its therapeutic effects are documented extensively in the classical medical literature [34].
In this study, two HCHs (Scutellariae Radix and Coptidis Rhizoma) were investigated using network pharmacology to explore their therapeutic potential for CHHF, in comparison with two BTHs (Angelicae Sinensis Radix and Paeoniae Radix Alba), which are traditionally used to treat this condition. By integrating target protein data from TCMSP and GeneCards and visualizing the interaction networks using Venny and Cytoscape, potential target proteins associated with CHHF were identified for each herb.
Among the 81 proteins uniquely targeted by individual herbs, 61 were specific to Coptidis Rhizoma, while Angelicae Sinensis Radix had no unique targets. This difference may largely reflect disparities in the number of target proteins collected for each herb. Nevertheless, the fact that 18 of the 85 overlapping proteins were shared among Scutellariae Radix, Coptidis Rhizoma, and Paeoniae Radix Alba is significant, as it suggests that their common pharmacological effects are not solely determined by their classical categories (heat-clearing vs. blood-tonifying) but may also be influenced by their intrinsic properties and flavors (性味).
From the perspective of traditional herbal properties, Scutellariae Radix and Coptidis Rhizoma are both characterized as bitter and cold (苦寒), whereas the BTHs differ: Angelicae Sinensis Radix is warm and sweet–pungent (溫, 甘辛), while Paeoniae Radix Alba is slightly cold and bitter–sour (微寒, 苦酸), more similar to the HCHs [21]. This similarity in properties and flavors may partially explain the overlap in target protein distributions among these herbs.
At the pathway level, database-derived enrichment showed substantial overlap between Scutellariae Radix and Paeoniae Radix Alba. Targets associated with the HCHs also showed prominent representation in hemostasis- and coagulation-related pathways, including platelet activation, signaling and aggregation, integrin signaling, and fibrin clot formation. Because pathway enrichment reflects the statistical distribution of associated targets rather than direct pathway activity, these findings should be interpreted as candidate pathway associations rather than demonstrated pharmacological effects.
In the present Reactome analysis, targets associated with Scutellariae Radix, Coptidis Rhizoma, and Paeoniae Radix Alba were enriched in MAPK-related signaling pathways. This represents a pathway-enrichment finding based on database-derived target associations and does not indicate activation or inhibition of MAPK signaling by these herbs.
Previous studies have implicated p38 MAPK signaling in vascular responses to inflammatory cytokines and oxidative stress, including altered nitric oxide (NO) availability, endothelin-1 expression, reactive oxygen species (ROS) accumulation, and responses of VSMCs and ECs [12]. These mechanisms are biologically relevant to endothelial dysfunction and sustained peripheral vasoconstriction, features that are also relevant to CHHF and RP.
Taken together, the overlap between the predicted herb-associated targets and MAPK-related pathways raises the hypothesis that MAPK-associated vascular stress responses may contribute to the biological relevance of these herbs to CHHF. However, the present network pharmacology analysis cannot establish whether these herbs activate, inhibit, or otherwise modulate MAPK signaling, and this proposed relationship requires experimental validation.
In addition, Coptidis Rhizoma was found to be enriched in the signal transduction pathway, including targets associated with CXCL11 signaling. It is established that CXCR3–CXCL11 signaling contributes to vascular stabilization by suppressing excessive endothelial cell proliferation and promoting pericyte recruitment [13]. Given that microvascular instability and reduced peripheral blood flow are key pathological features of CHHF, this raises the hypothesis that Coptidis Rhizoma may exert vascular-stabilizing effects via CXCL11-associated signaling, warranting further experimental validation. Accordingly, not only vasodilation but also vascular structural stability and the suppression of aberrant EC proliferation may represent an important, previously underexplored therapeutic factor in CHHF management.
Moreover, in the pathophysiological mechanisms underlying dysautonomia-related CHHF, the role of α2-ARs has been highlighted as a key contributor [8]. It is established that cutaneous vasculature is more sensitive to α2-ARs than to α1-adrenergic receptors (α1-ARs), that the α2A-AR subtype mediates rapid cutaneous vasoconstriction in response to sympathetic stimulation, and that α2C-ARs, although normally quiescent, translocate to the cell membrane upon cold stimulation and rapidly amplify the contractile response [14,15,35]. In the present network pharmacology analysis, ADRA2C (encoding α2C-AR) was identified as a target of Coptidis Rhizoma, while ADRA2A (encoding α2A-AR) was identified as a shared target of Scutellariae Radix and Angelicae Sinensis Radix; Scutellariae Radix was additionally classified into the platelet activation, signaling, and aggregation pathway via ADRA2A. These findings raise the hypothesis that Coptidis Rhizoma and Scutellariae Radix are associated with α2-AR-mediated, cold-induced vasoconstrictive mechanisms—and, for Scutellariae Radix, concurrently with platelet activation—representing a candidate mechanism underlying the cold hypersensitivity and vasospasm observed in CHHF and RP.
The HCHs showed the highest proportions of pathways related to the immune system and signal transduction, including those involving nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB), Janus kinase–signal transducer and activator of transcription (JAK-STAT), interleukin-4 and interleukin-13 (IL-4/13), and IFN-γ signaling, suggesting potential relevance to anti-inflammatory and cytokine-modulating processes. Notably, the identification of inflammatory cytokine targets such as TNF-α, IFN-γ, interleukin-16 (IL-16), and members of the interleukin-1 (IL-1) family in the present study is consistent with previous reports indicating that angiopoietin-2 (Ang-2) destabilizes ECs in the pathophysiology of RP, thereby rendering them more susceptible to inflammatory cytokine stimulation and inducing endothelial cell apoptosis, which ultimately exacerbates microvascular damage and ischemia [10]. Conversely, the BTHs exhibited distinct patterns. Paeoniae Radix Alba showed the highest proportion of immune system-related pathways (38%), with enriched targets involved in TNF signaling, TIR-domain-containing adapter-including interferon-β-mediated cell death (TRIF-mediated cell death), and IκB kinase (IKK) recruitment, suggesting a potential association with TNF-mediated inflammation and apoptosis. In contrast, Angelicae Sinensis Radix showed the lowest proportion of immune pathways (14%) but the highest representation in metabolic (27%) and neuronal (18%) pathways, indicating a relatively higher representation of pathways related to energy metabolism and mitochondrial function, suggesting a potential association with blood flow regulation.
These results suggest that HCHs and BTHs exhibit distinct but partially overlapping molecular profiles associated with CHHF, with HCHs showing greater representation of inflammation-, cytokine-, and hemostasis-related pathways, whereas BTHs showed associations with metabolic, neurovascular, and TNF-related pathways.
The term 淸熱藥 (HCHs) derives from the Chinese characters “淸” (to clear) and “熱” (heat), literally meaning “to clear heat.” In traditional theory, “heat” refers not only to fever but also to pathological states resembling inflammation. Many HCHs have been reported to have anti-inflammatory effects via multi-target mechanisms, providing an important pharmacological rationale for their traditional indications [35].
Traditionally, CHHF in KM has been categorized as cold pattern (寒證), including upper body heat and lower body cold (上熱下寒) or systemic coldness. However, the present study aimed to reinterpret CHHF from a new perspective. Conditions such as RP are characterized by excessive vasoconstriction or circulatory impairment of peripheral vessels triggered by cold exposure or emotional stress, often followed by reactive hyperemia accompanied by pain or redness. This pattern suggests that CHHF cannot be fully explained by the cold pattern alone.
Given that vascular constriction and reperfusion can elicit inflammatory responses in patients with CHHF [3,36], the anti-inflammatory effects of HCHs may alleviate these pathological reactions, thereby contributing to their therapeutic efficacy.
This study has several limitations.
Firstly, the scope of herbal selection was limited to four representative herbs, and the PubMed-based selection of HCHs yielded a relatively limited dataset. This may have excluded other potentially relevant herbs, particularly given the scarcity of previous studies investigating HCHs for CHHF. Further studies encompassing a broader range of herbal categories are warranted.
Secondly, although Angelicae Gigantis Radix is commonly used in Korean clinical practice, data for this herb were unavailable in the TCMSP database. Therefore, Angelicae Sinensis Radix, which is traditionally used as a BTH in Chinese medicine, was included in the present network pharmacology analysis. However, as these two herbs are botanically and chemically distinct, the findings derived from Angelicae Sinensis Radix cannot be directly generalized to Angelicae Gigantis Radix used in Korean clinical practice. Accordingly, this substitution represents a limitation of the present study, and future studies using species-specific phytochemical and target data for Angelicae Gigantis Radix are warranted.
Thirdly, the compound–target and disease-associated gene datasets were derived from TCMSP and GeneCards, respectively. TCMSP integrates herbal ingredients, ADME-related properties, and compound–target information, while GeneCards consolidates gene-centered information from diverse biomedical sources; these features enable systematic data retrieval and an internally consistent analytical workflow [37,38]. However, TCMSP includes both experimentally validated and SysDT-predicted compound–target associations and may not fully capture recently reported or poorly characterized constituents [37,39,40]. Likewise, GeneCards relevance scores integrate heterogeneous, source-dependent evidence and may preferentially prioritize well-studied genes [38,41]. In addition, active compounds were selected using predefined thresholds of OB ≥ 30% and DL ≥ 0.18. Although these thresholds were adopted based on their widespread use in previous network pharmacology studies, thereby facilitating comparability with earlier research, different cutoff values could alter the number and composition of the selected compounds and exclude pharmacologically relevant constituents. These database- and threshold-dependent factors may subsequently influence the PPI and pathway-enrichment results. Future studies incorporating cross-database analyses, alternative screening criteria, and sensitivity analyses are warranted to assess the robustness of the findings.
Fourthly, the present study analyzed individual herbs rather than multi-herb formulas commonly used in clinical practice. Although this approach was selected to facilitate direct comparison between heat-clearing and blood-tonifying herb categories, it does not fully reflect the complexity of actual herbal prescriptions. Therefore, the findings should not be directly generalized to the therapeutic effects of multi-herb formulas.
Fifthly, this study was based solely on literature-derived network pharmacology analysis, including target prediction and pathway enrichment, without experimental or clinical validation. As pathway enrichment reflects the statistical distribution of predicted targets across biological pathways rather than a direct measurement of pathway activation or inhibition, the biological mechanisms proposed in this study should be interpreted as hypothesis-generating rather than confirmatory. Nonetheless, this analysis provides meaningful preliminary evidence supporting the potential relevance of HCHs to CHHF-related pathways, warranting further experimental and clinical investigation to validate the proposed mechanisms.
This study is the first to explore the therapeutic potential of HCHs (Scutellariae Radix and Coptidis Rhizoma) by comparing them with traditionally used BTHs (Angelicae Sinensis Radix and Paeoniae Radix Alba) for CHHF treatment. The principal novelty of this study lies in extending the conventional therapeutic perspective on CHHF beyond the herbal categories traditionally associated with its treatment: CHHF has generally been interpreted within a cold-related pathological framework in KM, and blood-tonifying or warming therapeutic approaches have consequently occupied a central role in its clinical management, whereas HCHs, traditionally characterized by their heat-clearing actions and predominantly cold nature, have received relatively little attention as potential therapeutic candidates for CHHF. By directly comparing representative HCHs with clinically relevant BTHs within the specific context of CHHF, the present study identified HCH-associated molecular pathways related to hemostasis, inflammatory signaling, and vascular regulation, together with both distinct and overlapping pathway profiles relative to BTHs, revealing novel mechanisms of Scutellariae Radix and Coptidis Rhizoma not explained by the classical actions of BTHs and providing new insights into the pharmacological basis of CHHF treatment. Therefore, the originality of this study lies in its pathway-based comparative approach to investigating the counterintuitive possibility that HCHs may also have molecular relevance to a condition conventionally approached through blood-tonifying and warming strategies. This category-level comparison broadens the pharmacological perspective on CHHF and provides a hypothesis-generating basis for further investigation of HCHs as potentially complementary therapeutic candidates.
Furthermore, by integrating compound–target interaction data from public databases and applying network pharmacology analysis, this study revalidated traditional empirical knowledge of herbal efficacy through modern bioinformatics approaches. This integration bridges the gap between traditional concepts and molecular-level mechanisms, highlighting the importance of combining empirical and mechanistic evidence in future KM research.

5. Conclusions

Network pharmacology analysis was conducted on two HCHs (Scutellariae Radix and Coptidis Rhizoma) and two BTHs (Angelicae Sinensis Radix and Paeoniae Radix Alba) commonly prescribed for CHHF in KM.
The results demonstrated that Scutellariae Radix and Paeoniae Radix Alba shared a substantial number of signaling pathways, while the former uniquely contained additional pathways related to hemostasis and coagulation.
Overall, the predicted targets of HCHs showed greater representation in inflammation-, cytokine-, and hemostasis-related pathways, whereas those of BTHs showed greater representation in pathways potentially associated with blood flow and microcirculation.
Although this study demonstrated the potential binding affinity between active compounds and predicted protein targets, a limitation of this work is that molecular docking and dynamics simulations were not performed to evaluate the dynamic stability of the ligand-receptor complexes. Moreover, this study has limitations regarding the interpretation of computational predictions, screening thresholds, and discussion of database limitations.
These findings are hypothesis-generating and suggest that HCHs such as Scutellariae Radix and Coptidis Rhizoma may be associated with biological pathways relevant to CHHF; however, their therapeutic effects and clinical applicability require further wet-lab experimental and clinical validation.

Author Contributions

Conceptualization, Y.-C.L. and E.L.; methodology, E.L. and Y.K.; software, H.S.K.; validation, H.K., H.S.K. and J.Y.; formal analysis, J.S. and H.K.; investigation, E.L., Y.K., J.S., H.K. and J.Y.; resources, Y.K.; data curation, E.L., Y.K., J.S., H.K., J.Y. and H.S.K.; writing—original draft preparation, E.L., Y.K. and J.S.; writing—review and editing, Y.-C.L., E.L., Y.K., J.S., H.K. and J.Y.; visualization, E.L., Y.K., J.S.; supervision, Y.-C.L.; project administration, Y.-C.L., E.L., Y.K. and J.S.; funding acquisition, Y.-C.L. and E.L. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Data Availability Statement

The original contributions presented in this study are included in the article. Further inquiries can be directed to the corresponding authors. The raw data were derived from the following resources available in the public domain: TCMSP ((https://www.tcmsp-e.com/ (accessed on 2 August 2025)), GeneCards (https://www.genecards.org/ (accessed on 2 August 2025)), UniProt (https://www.uniprot.org/ (accessed on 2 August 2025)), STRING (https://string-db.org/ (accessed on 27 August 2025)), and Reactome (https://reactome.org/ (version 93; accessed on 25 August 2025).

Acknowledgments

During the preparation of this manuscript, the authors used ChatGPT 5.2 for the purposes of correcting the English. The authors have reviewed and edited the output and take full responsibility for the content of this publication.

Conflicts of Interest

The authors declare no conflicts of interest.

Abbreviations

The following abbreviations are used in this manuscript:
RPRaynaud’s phenomenon
KMKorean medicine
CHHFCold hypersensitivity in hands and feet
TCMTraditional Chinese medicine
HCHsHeat clearing herbs
ECsEndothelial cells
TNF-αTumor necrosis factor-α
IFN-γInterferon-γ
P38 MAPKP38 mitogen-activated protein kinase
VSMCsVascular smooth muscle cells
NONitric oxide
ROSReactive oxygen species
α2-ARsα2-adrenergic receptors
α1-ARsα1-adrenergic receptors
α2A-ARα2A-adrenergic receptors
α2C-ARα2C-adrenergic receptors
NCKMNational Clinical Practice Guidelines for Korean Medicine
TCMSPTraditional Chinese Medicine Systems Pharmacology Database and Analysis Platform
PPIProtein–protein interaction
STRINGSearch tool for the retrieval of interacting genes/proteins
CytoNCACytoscape network centrality analysis
CPG of CHHFClinical practice guideline of Korean medicine for cold hypersensitivity in hands and feet
ADMEAbsorption, distribution, metabolism, excretion
BCBetweenness centrality
CCCloseness centrality
DCDegree centrality
ECEigenvector centrality
CPGClinical practice guideline
BTHsBlood tonifying herbs
FDRFalse discovery rate
SRScutellariae Radix
CRCoptidis Rhizoma
ASRAngelicae Sinensis Radix
PRAPaeoniae Radix Alba
ADRA2CAdrenoceptor Alpha 2C
NF-κBNuclear factor kappa-light-chain-enhancer of activated B cells
JAK-STATJanus kinase–signal transducer and activator of transcription
IL-4/13Interleukin-4 and Interleukin-13
IL-16Interleukin-16
IL-1Interleukin-1
TRIF-mediated cell deathTIR-domain-containing adapter-inducing interferon-β-mediated cell death
IKKIκB kinase

Appendix A

Appendix A.1

The active compounds listed in Table A1, Table A2, Table A3 and Table A4 were retrieved from the TCMSP ((https://www.tcmsp-e.com/ (accessed on 2 August 2025)) and the PubChem database (https://pubchem.ncbi.nlm.nih.gov (accessed on 2 August 2025)). For compounds not available in TCMSP or requiring structural confirmation, chemical information including PubChem CID, molecular formula, molecular weight, and canonical structure was obtained from PubChem. Structural data were cross-validated to ensure consistency between databases. Duplicated entries were removed, and compounds lacking definitive structural or molecular information were excluded. Their biological activities and key findings from the PubMed database (https://pubmed.ncbi.nlm.nih.gov (accessed on 2 August 2025)) are reported in Table A5.
Table A1. Active compounds of Scutellariae Radix.
Table A2. Active compounds of Coptidis Rhizoma.
Table A3. Active compounds of Angelicae Sinensis Radix.
Table A4. Active compounds of Paeoniae Radix Alba.
Table A5. The important pharmacological activities and key findings of selected active compounds related to CHHF.
Table A6. Overlapping target proteins between CHHF and four selected herbs visualized by Cytoscape.
Table A7. Overlapping core genes between CHHF and four selected herbs visualized by Cytoscape.

Appendix A.2

Overlapping and unique target proteins between CHHF-related targets and the four selected herbs were identified using Venny 2.1.0. Targets were classified into herb-specific and shared target groups and visualized using Cytoscape.

Appendix A.3

Overlapping and unique core genes between CHHF-related targets and the four selected herbs were identified using Venny 2.1.0. Targets were classified into herb-specific and shared target groups and visualized using Cytoscape.

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