Promotion of Hair Regrowth in Androgenetic Alopecia with Supplemented Erzhi Wan: Exploring Its Mechanism Using Network Pharmacology and Molecular Docking

Introduction

Androgenetic alopecia (AGA), also known as male- or female-pattern alopecia, involves the miniaturization of hair follicles resulting in progressive hair thinning and shedding. Male-pattern alopecia primarily manifests as a receding frontal hairline with an M-shaped pattern, while female-pattern alopecia mainly manifests as diffuse hair thinning in a Christmas tree-like pattern on the top of the head. AGA can be accompanied by lighter hair color, higher oil production, and scalp inflammation, among other symptoms.¹ The mechanism underlying AGA involves the shortening of the hair follicle anagen phase, premature entry into the telogen phase, and eventual miniaturization of hair follicles, resulting in slow hair growth and hair loss.²

AGA is a major type of alopecia affecting 60–70% of the population.³ In China, the prevalence of AGA is as high as 21.3% in men and 6.0% in women.⁴ Recently, there has been increasing evidence indicating that AGA, as a chronic progressive disease, not only affects the appearance of patients but also causes psychological disorders.⁵ Hence, early interventions and effective treatments of androgenetic baldness are vital.

To date, only two drugs have been approved by the United States Food and Drug Administration (FDA) and European Medicines Agency for the treatment of AGA: finasteride and minoxidil. However, finasteride is not recommended for women according to the FDA. Moreover, both drugs have side effects and are effective in <50% of patients.³ A variety of other treatments exist, such as dutasteride, low-level laser therapy, stem cell-based therapy, platelet-rich plasma, microneedles, and hair transplants. These treatments mainly focus on improving symptoms, and their effectiveness is intrinsically related to their maintenance.¹ In addition, as these treatments are still under research and require further validation, we should consider their potential limitations regarding their effectiveness and side effects. Alternatively, various traditional Chinese herbs, including their monomers, have been reported to alleviate hair loss.^6–8 Furthermore, since herbs are typically reported to have fewer side effects, they are promising treatments.⁹

In Traditional Chinese Medicine (TCM), hair loss is closely related to kidney and blood deficiencies. Kidney deficiency is a pathological change in the kidney with insufficient essence and impaired function. If the kidney essence and blood production are insufficient, the hair lacks nutrition, resulting in hair fall. Therefore, the TCM treatment of hair loss is based on tonifying the kidneys and nourishing the blood.

SEZW is a Chinese medicinal formula consisting of ErZhi Wan (EZW) plus Cornus officinalis (CO) and Rehmanniae Radix Praeparata (RRP), which have tonifying effects on the kidneys and blood. EZW is a commonly used formula in TCM composed of two Chinese herbs, Ecliptae Herba (EH) and Fructus Ligustri Lucidi (FLL), whose names originate from the specific seasons when the two herbs are harvested: winter and summer solstices, respectively. EH and FLL have similar efficacies in treating AGA and according to historical documents, they can also darken the hair when used in combination. Research has shown that the proliferation, differentiation, and death of follicular melanocytes occur along the hair cycle progresses.¹⁰ Furthermore, follicular melanogenesis includes the melanogenic activity of follicular melanocytes, migration of melanin granules, and pigmentation of the hair shaft.¹¹ Therefore, we hypothesize that EZW not only can deepen hair color but also can promote hair growth. Even when CO, RRP, EH, and FLL are commonly used to treat AGA, the mechanism underlying the function of SEZW in alleviating hair loss remains unclear.

Since the current Western medicines for AGA have limited efficacy and applicability, it is worthwhile to consider TCM as an entry point for research and development of new treatments. In this study, we validated the efficacy of SEZW in the treatment of AGA by constructing an AGA mouse model. Network pharmacology was used to identify potential key targets and signaling pathways to explore the mechanism of action of SEZW in AGA treatment. Finally, the results were validated using molecular docking.

Materials and Methods

Materials

FLL granules (1 g, 10 g/bag), EH granules (1 g, 10 g/bag), RRP granules (4 g, 10 g/bag), and CO granules (1 g, 6 g/bag) were purchased from Zhangjiagang Traditional Chinese Medicine Hospital (Jiangyin Tianjiang Pharmaceutical Co., Ltd., Wuxi, China). Finasteride Tablets were obtained from Hangzhou MSD Pharmaceutical Co. Ltd. (1 mg/tablet, Hangzhou, China). Testosterone propionate injections were bought from Tianjin Jinyao Pharmaceutical Co. (1 mL × 25 mg, Tianjin, China).

One bag each of EH, FLL, RRP, and CO were added to pure water to obtain low (1 g/mL) and high concentration (2 g/mL) treatment solutions. Finasteride was powdered, added to a 0.5% sodium carboxymethylcellulose solution and mixed thoroughly to obtain a 0.1 mg/mL finasteride suspension. The testosterone propionate injection was diluted with injectable corn oil to a concentration of 5 mg/mL. Each solution was prepared weekly and stored at 4 °C. The solutions were warmed to room temperature before being administered.

Animals

Forty 6–8 weeks old males C57BL/6 mice, weighing 18–22 g, were purchased from the Suzhou Hengxingchen Biomedical Co. (Suzhou, China). The experiments were approved by the Animal Ethics Committee of Zhangjiagang TCM Hospital Affiliated to Nanjing University of Chinese Medicine according to guidelines for the ethical review of laboratory animal welfare People’s Republic of China National Standard GB/T 35892‐2018. The 40 mice were fed adaptively with free access to food and water for one week, after which a 2×3 cm area was marked on their dorsal side. The hair in this area was removed with an electric razor, and residual hair was removed with a depilatory cream. The dorsal skin of all mice was pink, suggesting that the hair follicles had entered the telogen phase. All mice except those in the control group were injected subcutaneously with 0.1 mL of 5 mg/mL testosterone propionate on the back every day for 28 days to obtain the AGA-model mice.¹²

Treatments

The 40 mice were randomly divided into five groups of eight mice each: Control, AGA-model, AGA-Positive, SEZW low dose (SEZW-L), and SEZW high dose (SEZW-H) groups. Mice in the AGA-Positive group were treated with 0.1 mL of 0.1 mg/mL finasteride suspension, while mice in the SEZW-L and SEZW-H groups were given 10 g/kg/d and 20 g/kg/d SEZW solution, respectively, via intragastric administration for 28 days. The mice were photographed on days 0, 14, and 28 during the dosing period to record hair growth and score the results (Figure 1A). Two trained technicians blindly measured hair regrowth ratios (%) according to the proportion of dorsal skin that turns black. As hairs enter the telogen phase the skin is pink, while in the anagen phase it is black. The evaluation criteria for hair regrowth were as follows: score 0=no growth observed; 1=up to 20% growth; 2=20–40% growth; 3=40–60% growth; 4=60–80% growth; and 5=80% to full growth.¹³ On day 28 of the experiment, all hair in the previously marked area on the dorsal side was removed using an electric razor. Subsequently, hair was weighed using a balance.

Figure 1 Pharmacodynamic study of SEZW in AGA-model mice. (A) A Schematic diagram of the pharmacodynamic experiment. (B) Dorsal photographs of mice in Control, AGA-model, AGA-Positive, SEZW-L, and SEZW-H groups at day 0, 14, and 28. (C) Changes in hair regrowth scores of the Control, AGA-model, AGA-Positive, SEZW-L, and SEZW-H groups at day 0, 14, and 28, represented as the mean. (D) Regrowth hair weight from the dorsal section of the mice in each of the five groups at day 28, represented as the mean. Abbreviations: SEZW, Supplemented Erzhi Wan; AGA, androgenetic alopecia; SEZW-L; SEZW low dose; SEZW-H; SEZW high dose.

Active Ingredients and Potential Targets Identification

Four Chinese herbs, EH, FLL, CO, and RRP, were searched for in the Traditional Chinese Medicine Database and Analysis Platform (TCMSP, https://tcmsp-e.com/). The active compounds in each herb were screened with the conditions of oral bioavailability (OB) ≥ 30% and drug-like properties (DL) ≥ 0.18. All potential targets corresponding to the ingredients in SEZW were collected. The names of the targets were normalized using the UniProt database (https://www.uniprot.org/). We selected targets that had been reviewed previously and removed duplicates and non-human targets. Finally, the compound-related targets were identified.

Identification of AGA-Related Targets

To obtain AGA-related targets, we used “Androgenetic alopecia” and “Alopecia seborrheic” as keywords to search in five gene databases: GeneCards (https://www.genecards.org/), OMIM (https://omim.org/), DrugBank (https://go.drugbank.com/), PharmGKB (https://www.pharmgkb.org/), and TTD (http://db.idrblab.net/ttd/). On the GeneCards database, genes with scores >0.5 were identified as those closely associated with AGA and were included in the study. Subsequently, we merged the AGA-related targets retrieved from the five databases.

Construction of Protein-Protein Interaction (PPI) Network for Drug-Disease Hub Targets

The Venn package in R was used to determine the overlap between the drug targets and disease-related genes, which were SEZW-AGA common targets. The PPI network was constructed by uploading candidate genes to the STRING database (https://string-db.org/). Subsequently, we imported the obtained results into the Cytoscape3.9.1 software for further analysis. CytoNCA, a Cytoscape plugin, was used to identify potential hub targets based on the analysis of six parameters: betweenness, closeness, degree, eigenvector, Local Average Connectivity-based method, and network. The top three active compounds in terms of the number of targets in the network and OB values were considered major active compounds.

GO and KEGG Enrichment Analyses

GO and KEGG enrichment analyses were performed to explore the potential functions of the candidate targets and crucial signaling pathways using the ClusterProfiler package in R4.2.1. Regarding the GO analysis, functions across the three categories, biological process (BP), cellular component (CC), and molecular function (MF), were considered statistically significant at P<0.05. Regarding the KEGG analysis, terms with P<0.05 were considered potential signaling pathways.

Molecular Docking Technology

The SEZW-AGA hub targets were considered receptor proteins, whereas the major active compounds were considered ligands. We obtained the core receptor protein and ligand structures from the Protein Data Bank (PDB) (http://www.rcsb.org/pdb/home/home.do) and PubChem databases (https://pubchem.ncbi.nlm.nih.gov/), respectively. The receptor proteins were pretreated via dehydration and hydrogenation using the PyMOL (https://pymol.org/2/) and AutoDockTools software (https://autodock.scripps.edu/download-autodock4/). Molecular ligands were converted into 3D structures using ChemOffice software (https://www.chemdraw.com.cn/). Subsequently, the receptor proteins and ligands were docked, and the docking fractions were calculated using AutoDockVina (https://vina.scripps.edu/). The lower the binding energy of the interactions, the better the binding ability between the receptors and ligands.¹⁴ Finally, the receptor-ligand complexes were visualized using PyMoL.

Results

Pharmacodynamic Study of SEZW on AGA-Model Mice

After 28 days of treatment, hair regrowth on the dorsal side of the mice in the AGA-model group was significantly slower than that of the mice in the other groups, indicating that the AGA-model mice had been constructed successfully (Figure 1B). After 2 weeks, hair regeneration reached more than 80% in the control group (Figure 1C), and there was a significant difference in hair regeneration scores between the control and the AGA-model group (P<0.01) (Figure 1C). The hair regeneration scores of mice in both the SEZW-L and SEZW-H groups were significantly higher than those of mice in the AGA-model group (P<0.01) (Figure 1C). Moreover, the mice in the AGA-Positive group showed faster hair growth, and their scores were significantly different from those of the mice in the AGA-model group (P<0.01) (Figure 1C). The hair regeneration scores of the mice in the Control, AGA-Positive, SEZW-L, and SEZW-H groups did not differ significantly (P>0.05) (Figure 1C), and mice in all these groups showed more than 80% hair regrowth after 28 days. The statistically significant difference between the hair scores of mice in the AGA-model and the other groups was maintained at 28 days (P<0.05) (Figure 1C). The results based on the hair weights of the mice supported these differences: The AGA-model mice had the lowest hair weight and the control group had the highest regenerated hair weight (Figure 1D). Compared to the AGA-model group, mice in the AGA-Positive, SEZW-L, and SEZW-H groups showed a significant increase in hair weight (P<0.01) (Figure 1D).

Prediction of the Targets of SEZW

By setting thresholds of OB ≥30% and DL ≥0.18, we identified 10, 13, 20, and 2 active compounds for FLL, EH, CO, and RRP, respectively, from the TCMSP database. The corresponding targets for each active compound were also downloaded from the TCMSP database (Table 1). After deduplication and integration, we obtained 200 molecules targeted by the active compounds present in SEZW.

Table 1 Active compounds and targets selected for SEZW

AGA-Related Target Prediction

We obtained 657, 12, 11, 745, and 0 candidate AGA-related genes from GeneCards, OMIM, DrugBank, PharmGKB, and TTD, respectively. Targets related to AGA in the GeneCards database were sorted and selected based on a relevance score greater than 0.5, which was considered a strong correlation. After removing duplicates, we obtained a final set of 1385 AGA-related genes (Figure 2A).

Figure 2 Venn diagram. (A) Venn diagram showing the AGA-related genes from the GeneCards, OMIM, DrugBank, and PharmGKB databases. (B) Venn diagram showing the targets of the active compounds in Drugs and Disease. Abbreviation: AGA, androgenetic alopecia.

Construction of PPI Networks for Drug-Disease Targets

A total of 59 shared targets of drug compounds and diseases were found (Figure 2B). Based on these, a PPI network consisting of 59 nodes and 592 edges was constructed. Network edges were added based on evidence collected through text-mining, experiments, databases, co-expression, neighborhood, gene fusion, and co-occurrence, with the minimum required interaction score set as “medium confidence” (0.400). We imported the PPI into Cytoscape3.9.1 for further analysis and visualization (Figure 3A). After the first filtring through CytoNCA, 20 targets were identified (Figure 3B). After two filters, we identified numerous crucial targets within the network: AKT1, JUN, VEGFA, HIF1A, TP53, EGF, and PTGS2 (Figure 3C). According to the SEZW-AGA interaction network, quercetin (MOL000098), luteolin (MOL000006), and kaempferol (MOL000422) exhibited the highest degrees of interaction with 59 targets and acted on 45, 27, and 21 targets, respectively (Figure 4). Additionally, the OB values of quercetin, luteolin, and kaempferol were 46.43%, 36.16%, and 41.88%, respectively. Together, these findings suggest that quercetin, luteolin, and kaempferol are the primary active compounds in SEZW.

Figure 3 PPI network including the 59 hub genes and identified hub targets. (A) 59 SEZW-AGA common targets were identified. (B) After the first filtering through CytoNCA, 20 targets were identified. The darker the color, the greater the degree. (C) 7 hub targets were identified after a second filtering stage. Abbreviations: PPI, protein-protein interaction; SEZW, Supplemented Erzhi Wan; AGA, androgenetic alopecia.

Figure 4 SEZW-AGA network. Circles represent the active compounds in SEZW and diamonds represent the SEZW-AGA common targets. Purple, green, blue, and pink represent the target compounds of FLL, EH, CO, and RRP, respectively. Abbreviations: SEZW, Supplemented Erzhi Wan; AGA, androgenetic alopecia; FLL, Fructus Ligustri Lucidi; EH, Ecliptae Herba; CO, Cornus Officinalis; RRP, Rehmanniae Radix Praeparata.

GO and KEGG Enrichment Analyses

GO and KEGG enrichment analyses were conducted, and 1298 BP, 28 CC, 91 MF, and 123 KEGG pathway terms were found to be enriched based on an adjusted P value <0.05. The top 10 terms in each category are listed in Table 2. From these enrichment results, the top five terms of each GO term and the top 10 KEGG pathways were chosen for visualization (Figure 5).

Table 2 GO and KEGG enrichment analysis

Figure 5 Results from GO and KEGG enrichment analyses. (A) Top 5 significant GO enrichment terms in the BP, CC, and MF categories across the 59 common targets. (B) Top 10 KEGG enrichment pathways across the 59 common targets. Abbreviations: GO, Gene Ontology; KEGG, Kyoto Encyclopedia of Genes and Genomes; BP, biological process; CC, cellular component; MF, molecular function.

Molecular Docking Technology

We selected candidate hub targets (AKT1, JUN, VEGFA, HIF1A, TP53, EGF, and PTGS2) as protein receptors and the three major active compounds (quercetin, luteolin, and kaempferol) as ligands for validation using molecular docking. A binding energy of less than −5 kcal/mol was used as the threshold for stable binding. In our study, all binding values were less than −6 kcal/mol, indicating a strong receptor-ligand affinity (Table 3). We selected the top nine stable receptor-ligand complexes for visualization (Figure 6).

Table 3 The molecular docking of the active compounds to the core targets

Figure 6 Results of molecular docking of active compounds and hub targets. Complexes are arranged from the lowest to the highest binding energy score: (A) PTGS2-luteolin. (B) JUN-quercetin. (C) PTGS2-quercetin. (D) PTGS2-kaempferol. (E) JUN-luteolin. (F) JUN-kaempferol. (G) AKT1-quercetin. (H) EGF-quercetin. (I) AKT1-luteolin.

Discussion

Network pharmacology is a new drug design strategy based on rapid systems biology and multidirectional pharmacology developments. Nogales¹⁵ argued that diseases are currently diagnosed by phenotypes aimed at alleviating symptoms rather than by mechanisms and treatments, which often only have minimal transient effects. The approach to drug development has changed with the rise of network pharmacological research. Instead of focusing on a single symptom and target, we used a disease-multitarget-multidrug model. This involves the use of two or more drugs to synergistically target key network proteins, thereby addressing the underlying disease at the root cause. The “treatment based on syndrome differentiation” approach in TCM involves combining various drugs to target the underlying nature of pathological changes; therefore, aligns with the drug-multitarget-multidrug model in network pharmacological research.

Thus, network pharmacology is a valid method to analyze the mechanism of action of SEZW in the treatment of AGA. This treatment strategy is characteristic of the TCM “treatment based on syndrome differentiation” approach, which uses TCM theory to analyze relevant clinical data, clarify the essentiality of diseases, and identify the ‘syndrome”, which can reflect the combination of the cause, location, nature of the disease, and its tendency to develop and change. From this, treatment rules, methods, and prescriptions are formulated.

In this study, we obtained 200 SEZW targets from the TCMSP database and 1385 AGA-associated genes from the GeneCards, OMIM, DrugBank, PharmGKB, and TTD databases. Then, 59 candidate SEZW-AGA targets were identified at the intersection of these lists. The above results were imported into the STRING tool, and a PPI network was constructed with 59 nodes and 592 edges. In addition, we identified seven potential hub targets: AKT1, JUN, VEGFA, HIF1A, TP53, EGF, and PTGS2. Some of these genes have been investigated previously for their relevance in hair growth. For example, VEGFA (vascularization endothelial growth factor A) has been shown to regulate vascularization and vessel size around the hair follicle, thus altering the size of follicles as blood vessels are required to provide nutrients.¹³ In addition, Gaofeng Wang et al¹⁶ found that activation of HIF1A signaling by inducing tissue hypoxia promoted wound-induced hair follicle neogenesis.

Quercetin, luteolin, and kaempferol were identified as the major active compounds in SEZW. They are flavonoids that can be identified in EZW through mass spectrometry.¹⁷ Quercetin has previously been shown to stimulate melanogenesis in mice hair follicle melanocytes and promote hair shaft growth in cultured human hair follicles.^18,19

Subsequently, GO and KEGG enrichment analyses were performed on the 59 candidate targets. These targets were mainly enriched for processes involving the response to oxidative stress, reactive oxygen species, gland development, cellular response to chemical stress, and cellular response to oxidative stress. Among these, oxidative stress, defined as the excess of reactive oxygen species relative to antioxidants, has been linked to neurodegenerative diseases, cardiovascular diseases, diabetes mellitus, and many other pathologies.²⁰ Studies have shown a close relationship between oxidative stress and AGA. For example, Bahta et al²¹ found that the premature senescence of balding dermal papilla cells in vitro is associated with the expression of oxidative stress and DNA damage markers. Upton et al²² further investigated the role of oxidative stress in the pathogenesis of AGA in relation to cell senescence, migration, and the secretion of hair follicle inhibitory factors. Moreover, AGA patients have shown increased oxidative stress in vivo.^23,24 However, few drugs used to treat AGA target the pathological mechanisms of oxidative stress, and those that do require further validation. EZW has been demonstrated to inhibit oxidative stress and regulate metabolism in a diabetic cardiomyopathy-related study.²⁵ Therefore, we hypothesized that the mechanism of action of SEZW in treating AGA may be related to oxidative stress. Experimental research is needed to investigate this further.

The KEGG enrichment analysis identified 123 significantly enriched pathways, including the PI3K-Akt signaling pathway. Akt, which was previously identified as a hub target, is also a key downstream molecule in the PI3k/Akt signaling pathway. This pathway has a significant impact on cancer and neurological, metabolic, and cardiovascular diseases, among others.^26–29 Through activation or inhibition of downstream proteins, PI3K/Akt regulates signal transduction and is involved in numerous biological processes, such as cell proliferation, migration, differentiation, apoptosis, and metabolism.³⁰ Research by Yu Chen³¹ has shown that the PI3K-Akt signaling pathway plays a crucial role in de novo hair follicle regeneration. This provides further theoretical support for exploring the possible involvement of the PI3K/AKT signaling pathway in the pathological process of AGA.

Our study has some limitations. We have demonstrated the promotion of hair growth by SEZW in AGA-model mice; however, large-scale clinical studies need to be conducted to confirm these results.

Conclusion

SEZW promoted hair growth in mice with AGA. Based on network pharmacology, we identified the possible mechanisms of action of SEZW in the treatment of AGA, finding that the response to oxidative stress, gland development, and chemical stress are critical targets. Further, the PI3K/Akt and AGE-RAGE signaling pathways were identified as potential signaling pathways through which SEZW exerts its therapeutic effects. AKT1, JUN, VEGFA, HIF1A, TP53, EGF, and PTGS2 were identified as hub molecules for the efficacy of SEZW in AGA treatment.