Prediction of the Mechanism of Action for Buguzhi in Vitiligo Treatment through Network Pharmacology Analysis: Focusing on the Regulation of Tumor Protein p53
Article information
Abstract
Objectives
This study aimed to predict the mechanism underlying the effects of buguzhi (補骨脂) on vitiligo through network pharmacology analysis and molecular docking.
Methods
The active compounds of buguzhi and its related genes were collected through traditional chinese bank (TCM Bank) and encyclopedia of traditional chinese medicine (ETCM) databases. Vitiligo-related genes were collected using Comparative Toxicogenomics Database (CTD), DisGenet, and Gene Cards. The overlapping genes between buguzhi-related genes and vitiligo-related genes were designated target genes. Protein-protein interaction analysis was performed using the STRING for target genes. The top 10 genes and top 3 compounds with high association in the target gene networks were selected as hub genes and compounds using CytoHubba. Functional enrichment analysis was conducted using an the science and research online plot, categorized by biological process (BP), cellular component (CC), and molecular function (MF). Molecular docking was performed using AutoDockTools.
Results
Fifty-six target genes were collected. Three hub compounds (uvadex, psoralen, and stearic acid) and 10 hub genes (TP53, BCL2, IL1B, TNF, NFKB1, CASP3, ACTB, INS, FOS, and PTGS2) were revealed. The top-ranked hub gene was TP53. Functional enrichment revealed that the hub genes with the highest enrichment scores in the biological process were those that regulate reactive oxygen species metabolism, nuclear membrane in the cellular component, and tumor necrosis factor superfamily binding and cytokine receptor binding in the molecular function. Psoralen and uvadex stably interacted with tumor protein p53 (TP53) with affinity energies of −4.7 and −4.867 kcal/mol.
Conclusions
Buguzhi is predicted to treat vitiligo by regulating p53 to scavenge reactive oxygen species and protect melanocytes from various immune responses induced by oxidative stress, promoting melanogenesis.
Introduction
Vitiligo is a condition characterized by the formation of white macules on various parts of the body, including the lips, extremities, genitals, and trunk. This occurs because of the loss of functional melanocytes in the skin and hair. It is believed that vitiligo is caused by the destruction of melanocytes through a complex pathogenesis involving genetic factors, autoimmune responses, and oxidative stress. With the recent increase in research, vitiligo is now clearly classified as an autoimmune disease. The global prevalence of vitiligo is estimated to be between 0.5% and 1%, with a similar prevalence between men and women1).
In modern medicine, topical corticosteroids and calcineurin inhibitors are considered first-line treatments. Second-line treatments include systemic steroid treatment, narrow-band ultraviolet B, and phototherapy, including both psoralen and ultraviolet A (PUVA). If medications and phototherapy are ineffective, surgical options may be considered, including tissue transplantation to the affected area of vitiligo2). Other treatments include cover-up therapy, which uses cosmetics to hide the lesions, and laser therapy, which uses lasers to stimulate the activity of melanocytes in the skin. However, both first- and second-line treatments use immunosuppressive agents, so side effects must be considered with prolonged administration3). Additionally, the appropriate duration of topical corticosteroid use for vitiligo is not clearly established1). Surgical therapy can be used for small depigmented patches, but it is difficult to use for large or extensive patches2). Furthermore, the treatment of vitiligo is currently considered to be one of the most challenging dermatological problems4) because the disease often recurs without long-term maintenance treatment following repigmentation1).
In modern Korean medicine, there have been reports of vitiligo improvement through treatments such as customized herbal prescriptions, placenta pharmacopuncture, and the topical application of buguzhi5,6). According to Park’s study7) on herbal decoction, honghua (紅花), danggui (當歸), and hanliancho (旱蓮草) were commonly used. Several case reports5,6,8,9) in Korea have indicated that buguzhi (補骨脂) has been applied both topically and orally to improve vitiligo. A main component of buguzhi, psoralen, has been used in PUVA therapy to treat vitiligo; however, studies on buguzhi have mainly focused on the effects of buguzhi on osteoclast differentiation10) and male germ cells11,12). Additionally, while there is an experimental study showing that buguzhi extract increases tyrosinase activity in melanoma11), no network pharmacology analysis or molecular docking studies have been performed to identify the mechanisms of the various components of buguzhi that are relevant to the treatment of vitiligo.
This study report explores the therapeutic mechanisms of buguzhi on vitiligo, which comprises multiple compounds, using a network pharmacology analysis.
Materials and methods
1. Screening of Active Compounds and Related Genes in Buguzhi
The active compounds and related targets of buguzhi were collected using the traditional chinese medicine bank (TCM Bank, http://tcmbank.cn/ (accessed on 30 September 2024))13) and the encyclopedia of traditional chinese medicine (ETCM, http://www.tcmip.cn/ETCM2/front/#1/ (accessed on 30 September 2024)) databases. The drug-like nature of the collected components of buguzhi was predicted using swissADME (http://www.swissadme.ch/ (accessed on 6 October 2024)). The criteria for inclusion as active compounds among all components were defined as those with a drug likeness of 0.55 or higher, fulfilling all of Lipinski’s rule of five and having high gastrointestinal absorption14). Furthermore, genes linked to the active compounds were classified as buguzhi-related genes.
2. Identifying Vitiligo-Related Genes
Genes associated with vitiligo were collected from the DisGenet platform (http://www.disgenet.org/ (accessed on 6 October 2024))15), GeneCards (http://genecards.org/ (accessed on 6 October 2024))16), and the Comparative Toxicogenomics Database (CTD, http://ctdbase.org/ (accessed on 6 October 2024))17), using the search term “vitiligo.” FunRich 3.1.4 (http://funrich.org/) was employed to generate a Venn diagram of genes collected from the three databases, and vitiligo-related genes were defined as those intersecting in two or more databases. Additionally, genes overlapping between buguzhi- and vitiligo-related genes were identified as target genes.
3. Protein-Protein Interaction (PPI) Network Analysis
Cytoscape 3.9.1 (https://cytoscape.org/ (accessed on 7 October 2024)) was used to identify the network between active compounds and buguzhi-related genes and the network between active compounds and target genes. The STRING platform (http://string-db.org/ (accessed on 7 October 2024)) was used to analyze the relationship between target genes. The network edge was represented as a confidence level, and the minimum required interaction score was established at 0.7 (high confidence) or higher.
The CytoHubba tool was used to identify hub genes and compounds from the PPI analysis.
4. Functional Enrichment Analysis
Gene Ontology (GO) analysis of hub genes was performed according to biological process (BP), cellular component (CC), and molecular function (MF), using the science and research online plot platform (https://www.bioinformatics.com.cn/en/ (accessed on 8 October 2024))18).
5. Molecular Docking Analysis
Molecular docking was conducted to predict the binding affinity between the protein with the highest-ranking score, translated from hub genes, and the hub compounds. The 3-dimensional (3D) molecular structures of hub compounds were collected from PubChem (https://pubchem.ncbi.nlm.nih.gov/ (accessed on 10 October 2024)) as structure-data format (SDF) files, and hub gene proteins were collected from protein data bank (PDB, https://www.rcbs.org/ (accessed on 10 October 2024)) as PDB files. If the molecular structure of a hub compound could not be represented in a 3D SDF file owing to its structural characteristics, molecular docking was not performed if it could only be implemented in a two-dimensional file. Autodock Tool (version 4.2.6) was used to verify the binding interaction and calculate the binding energy of the collected ligands and receptor files. The binding molecular models were visualized in 3D using PyMOL software (version 2.5.3) and as 2-dimensional structures using Biovia Discovery Studio Visualizer v17.2, 2021 (BIOVIA, Dassault Systèmes, Waltham, USA).
Results
1. Screening of Active Compounds and Related Genes in Buguzhi
A total of 32 compounds were selected as active compounds of buguzhi with a drug likeness of 0.55 or higher, fulfilling both Lipinski’s rule of five and high GI absorption from TCM Bank and ETCM databases (Table 1). Among these 32 compounds, nine compounds had associated genes identified, and 558 buguzhi-related genes associated with these nine compounds were collected (Fig. 1).
Active compounds of P. corylifolia
558 Buguzhi related genes (blue) and 9 active compounds of buguzhi (green).
Of the 32 active compounds, gene associations were identified for only 9 compounds, while no gene associations were detected for the remaining 23 compounds.
2. Identifying Vitiligo-Related Genes
There were 9, 807, and 10,534 genes associated with vitiligo were collected from DisGenet, GeneCards, and CTD, respectively. Among these, 542 genes that were duplicated in two or more databases were selected as vitiligo-related genes (Fig. 2).
Vitiligo related genes in 3 databases: DisGenet, CTD and Gene Cards.
Defined 542 genes that intersected in two or more databases as vitiligo related genes.
3. PPI Network Analysis
Fifty-six target genes were identified as common genes between vitiligo- and buguzhi-related genes (Fig. 3). The network between these 56 target genes and the eight active compounds was visualized using Cytoscape (Fig. 4). A total of 64 nodes formed 82 edges. Using CytoHubba, the three most highly associated active compounds were identified as stearic acid, uvadex, and psoralen using different ranking methods based on Maximal Clique Centrality, closeness, and degree. These compounds were characterized as hub compounds (Table 2).
56 Target genes
56 genes common between vitiligo related genes and buguzhi related genes were selected as target genes.
Active compounds (green) - target genes (orange) network
64 nodes and 82 edges were formed.
Top 3 hub compounds by cytoHubba
Analyzing PPIs among 56 target genes using the STRING platform, 48 genes (nodes) with an interaction score greater than 0.7 (high confidence) formed 163 edges, while with genes did not form any edge (Fig. 5A). The average node degree of the PPI network was 5.82. Using CytoHubba, the target genes were ranked by degree to select the target genes with the highest degree. Among the 56 target genes, the top 10 highest degree values were TP53, BCL2, IL1B, TNF, NFKB1, CASP3, ACTB, INS, FOS, and PTGS2. Among them, the gene with the highest degree value was TP53 (Fig. 5B).
Protein-protein Interaction (PPI) among 56 target genes
(A) 48 nodes formed 163 edges. (PPI enrichment p-value< 1.0e-16), (B) Top 10 genes generated from cytoHubba plugin in Cytoscape by degree method.
4. Functional Enrichment Analysis
GO Enrichment analysis was performed to comprehensively identify the functions of the 10 hub genes at the BP, MF, and CC levels. In terms of BP, the process with the lowest p-value was the ‘regulation of reactive oxygen species metabolic process,’ with TP53, BCL2, IL1B, TNF, INS, and PTGS2 being involved in this process. The same combination of genes was involved in the ‘regulation of reactive oxygen species metabolic process,’ indicating that 6 out of 10 hub genes were involved in the regulation of redox-related processes. Additionally, TP53, BCL2, TNF, CASP3, INS, and PTGS2 were found to be involved in the intrinsic apoptotic signaling pathway. From the MF perspective, five of the ten genes—TP53, BCL2, TNF, CASP3, and INS—were found to participate in protease binding. Furthermore, these genes were primarily associated with immune responses such as tumor necrosis factor receptor binding, protein phosphatase 2A binding, and cytokine receptor binding. In terms of CC, we found that the expression of TP53, TNF, CASP3, etc. was more likely to be activated in membranes such as the nuclear membrane, membrane raft, and mitochondrial membrane (Fig. 6).
Gene Ontology(GO) enrichment analysis of 10 hub genes by Biological Process (BP), Cellular Component (CC) and Molecular Function (MF) level.
Enrichment score is calculated by −log10(p-value)
5. Molecular Docking Analysis
Molecular docking was intended to be performed between tumor protein p53 (TP53), the highest-ranking protein translated by the hub gene, and the hub compounds uvadex, stearic acid, and psoralen. However, owing to the high flexibility of stearic acid, which precluded accurate modeling in a 3D SDF format, docking between stearic acid and TP53 was not performed. Instead, molecular docking was conducted between TP53 and psoralen, as well as uvadex.
Psoralen and uvadex interacted with TP53 via van der Waals forces with proline at position 177 and glycine at position 244 of the TP53 A chain, as well as pi-cation interactions with arginine at position 174 of the same chain (Fig. 7). The binding affinities for psoralen–TP53 and uvadex–TP53 were −4.7 and −4.867 kcal/mol, respectively. It is widely acknowledged that binding energy below −4.25 kcal/mol suggests a certain binding interaction between the ligand and its receptor. Binding energy represents the likelihood of interaction between the receptor and ligand. A lower binding energy corresponds to a higher affinity between the receptor and ligand, leading to a more stable conformation19). Thus, molecular docking analysis confirmed that both psoralen and uvadex interact stably with TP53.
Molecular docking (A) TP53 (gray) - Psoralen (pink) (B) TP53 (gray) - Uvadex (green)
(A) Affinity energy: −4.7 kcal/mol (B) Affinity energy: −4.867 kcal/mol
Discussion
Vitiligo is referred to in classical texts as baekjeonpoong (白殿風) and baekbakpoong (白駁風). In traditional Korean medicine, the causative factors of vitiligo can be categorized into internal pathogenic factors (內因) and external etiological factors (外因). The external etiological factors involve the invasion of pathogenic qi (邪氣), such as pathogenic wind (風), cold (寒), and dampness (濕), leading to qi-blood disharmony (氣血不和) in the skin. Internal pathogenic factors include conditions such as the seven emotions causing internal damage (七情內傷), Yin deficiency of the liver and kidney pattern (肝腎陰虛), deficiency of the heart and spleen pattern (心脾兩虛), and blood deficiency (血虛), which can lead to qi-blood disharmony (氣血不和) and blood stasis due to qi stagnation (氣滯血瘀). These imbalances prevent the skin from maintaining its luster and result in disturbances within the meridians, ultimately contributing to the development of vitiligo20). Considering these causative factors, traditional Korean medicine has used blood-circulating and blood stasis-resolving medicines (活血祛瘀藥), such as honghua (紅花) and taoren (桃仁), along with tonifying formulas for liver and kidney Yin deficiency (補肝腎陰虛), including danggui (當歸), shudihuang (熟地黃), and buguzhi. These formulas, classified as tonifying or reinforcing medicines (補益藥), have been prescribed to treat vitiligo7).
Based on the use of buguzhi to alleviate vitiligo in several papers, this study aimed to predict the mechanism of buguzhi’s treatment of vitiligo using network pharmacology.
The intersection of buguzhi- and vitiligo-related genes, referred to as target genes (Fig. 3), was analyzed using CytoHubba to identify the components of buguzhi with the highest correlation to these genes. These were designated as hub compounds and genes, respectively. The hub compounds were psoralen, uvadex, and stearic acid (Table 2), and the hub genes were analyzed as TP53, BCL2, IL1B, TNF, NFKB1, CASP3, ACTB, INS, FOS, and PTGS2, with TP53 being the top-ranked hub gene (Fig. 5). Although stearic acid could not be molecularly docked with TP53 owing to its structural characteristics and the inability to implement 3D SDF files, uvadex and psoralen were found to interact with TP53 with stable affinity energies of −4.867 and −4.7 kcal/mol, respectively (Fig. 7).
Melanocytes in patients with vitiligo are more susceptible to oxidative stress than those in the normal population21,22), suggesting that reactive oxygen species (ROS) generated by the oxidative stress response may reduce the stability of tyrosine-related protein-1 (TRP-1), which is involved in melanogenesis and forms toxic melanin intermediates, leading to melanocyte cell death23). Moreover, mitochondria are significant inducers of ROS. It has been demonstrated that patients with vitiligo exhibit increased mitochondrial malate dehydrogenase activity, along with alterations in mitochondrial transmembrane potential and the electron transport chain complex, compared with the healthy control groups. Additionally, changes in the lipid components of the mitochondrial membrane have been observed in these patients23,24). Additionally, the overproduction of ROS triggers an unfolded protein response, melanocytes activate T cells to produce cytokines, and interferon-gamma is elevated in vitiligo lesions. These processes have been shown to inhibit melanin production and promote cell death25), and topical corticosteroids or topical calcineurin inhibitors are prescribed for patients with vitiligo1). In the study of the pathogenesis of vitiligo, the GO analysis of 10 hub genes showed that BP with the highest enrichment score is a process that regulates ROS metabolism, and CCs related to hub genes are related to nuclear membrane and membrane raft (Fig. 6). Therefore, it can be inferred that buguzhi reduces oxidative stress in vitiligo lesions and melanocyte apoptosis. Additionally, the high enrichment scores of cytokine receptor binding and tumor necrosis factor receptor superfamily binding in MF suggest that buguzhi may inhibit ROS-activated immune responses.
TP53 functions as a transcriptional regulator of downstream genes to protect cells from harmful compounds and radiation that cause cellular stress and to promote cellular adaptation. During melanogenesis in the skin, TP53 has been shown to activate genes coding for tyrosinase and TRP-126), and stable expression of TP53 and maintenance of TP53 activity are critical for melanin synthesis. TP53, which ranked the highest among the hub genes, was found to form stable bindings with the hub compounds uvadex and psoralen through molecular docking (Fig. 7). It leads to the prediction that these compounds may stabilize TP53 and thus promote melanogenesis. Uvadex (also known as 8-methoxypsoralen) is a member of the psoralen family, and studies have shown that both psoralen and uvadex are photosensitizers and that exposure to UVA after taking either substance upregulates TP53 and B-cell lymphoma 2–associated X protein by modulating miRNA expression27). It has also been experimentally demonstrated that uvadex promotes melanogenesis by increasing the concentrations of tyrosinase and TRP-1 and acts as a ROS scavenger to protect melanocytes28).
This study suggests the potential of buguzhi, a natural product, to effectively treat vitiligo by regulating the activity of p53 through its major compounds. However, the analysis using network pharmacology is insufficient to fully explain the in vivo mechanisms of buguzhi. Further studies are needed to investigate how the proportions of active compounds vary depending on the extraction method, such as decoction or granule formulation. Although in vitro studies in Korea demonstrated that the buguzhi extract increases melanin production and activates tyrosinase in melanoma cells, no animal studies have been conducted. Additionally, while there are a few case reports (one case, four cases) of vitiligo treatment, no randomized controlled trials have been performed in Korea. Therefore, it is essential to conduct follow-up studies, including animal experiments and eventually randomized controlled trials in humans, to elucidate the precise therapeutic mechanisms and efficacy of buguzhi.
Conclusion
In this study, a network-based system pharmacology analysis was performed to identify the hub compounds of buguzhi (uvadex, psoralen, and stearic acid) and 56 target genes closely associated with vitiligo. From the gene network of these 56 genes, the top 10 hub genes (TP53, BCL2, IL1B, TNF, NFKB1, CASP3, ACTB, INS, FOS, and PTGS2) with the highest degree were selected. GO analysis of these top 10 hub genes revealed that in terms of BP, there was a high enrichment score for the regulation of ROS metabolism; in terms of CC, significant enrichment was found in nuclear membrane and mitochondrial membrane; and in terms of MF, high enrichment scores were observed for cytokine receptor binding, tumor necrosis factor receptor binding, and protease binding. Additionally, it suggest that both uvadex and psoralen are likely to form stable bindings with the top-ranked TP53, with the exception of stearic acid, which was too flexible to form a 3D conformation and thus could not undergo molecular docking.
This study presents the possibility that the major compounds of buguzhi may function as effective treatments for vitiligo by regulating the activity of p53.