Diabetic retinopathy (DR) and diabetic cataract (DC) are two closely related microvascular complications of diabetes. , a plant from the Araliaceae family and genus Panax, is widely used in traditional Chinese medicine (TCM) due to its antioxidant, anti-inflammatory, and blood circulation-promoting properties. Recent studies suggest that drugs possessing anti-inflammatory, antioxidant, and blood circulation-promoting characteristics may have unexpected benefits in treating diabetic microvascular complications. This study employs network pharmacology to investigate the mechanisms by which can treat DR and DC as comorbidities. The study aims to explore the active components and biological mechanisms of in treating these comorbidities using network pharmacology and molecular docking. Components of were identified through literature reviews and database queries. Active components were selected based on drug-like principles, and their targets were predicted using the principle of similarity. Disease-related genes were collected from OMIM and GeneCards and scored. Venn analysis identified target nodes, followed by protein-protein interaction (PPI) network analysis, gene ontology (GO) analysis, and KEGG pathway analysis. Topological algorithms analyzed the PPI network, and key nodes combined with other analysis results were utilized to construct a -active component-gene-phenotype network using Cytoscape 3.9.1. Molecular docking on key genes, integrated with biological background, determined potential therapeutic targets against the diseases. contains eight active components and 234 potential gene targets. Network analysis showed that can repair microvascular damage by influencing disease-related signaling pathways. Molecular docking indicated that four key targets (SRC, JAK2, IGF1R, and EGFR) effectively bind to the active components of . These findings provide insights into the molecular-level action of against these diseases. Overall, this study enhances our understanding of the potential of in treating DR and DC as comorbidities and establishes a foundation for further research.

To explore the potential mechanism of Gegen Qinlian decoction (GGQL) in the treatment of COVID-19 comorbid with diabetes mellitus (DM) through network pharmacology and molecular docking, and to provide theoretical guidance for clinical transformation research. Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform was used to screen the active compounds and targets of GGQL, the targets of COVID-19 comorbid with DM were searched based on Genecards database. Protein-protein interaction network was constructed using String data platform for the intersection of compounds and disease targets, the Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analysis of the intersection targets was performed using DAVID database. Cytoscape software was used to construct the "compound target-pathway (C-T-P)" of GGQL in the treatment of COVID-19 comorbid with DM, the molecular docking platform was used to complete the simulated docking of key compounds and targets. We obtained 141 compounds from GGQL, revealed 127 bioactive compounds and 283 potential targets of GGQL. Quercetin, kaempferol and formononetin in GGQL play a role by modulating the targets (including AR, GSK3B, DPP4, F2, and NOS3). GGQL might affect diverse signaling pathways related to the pathogenesis of coronavirus disease - COVID-19, AGE-RAGE signaling pathway in diabetic complications, IL-17 signaling pathway, human cytomegalovirus infection and Th17 cell differentiation. Meanwhile, molecular docking showed that the selected GGQL core active components had strong binding activity with the key targets. This study revealed that GGQL play a role in the treatment of COVID-19 comorbid with DM through multi-component, multi-target and multi-pathway mode of action, which provided good theoretical basis for further verification research.

OBJECTIVE:The present study aimed to explore the mechanisms underlying the comorbidity of epilepsy and migraine, identify potential common targets for drug intervention, and provide insight into new avenues for disease prevention and treatment using an integrated bioinformatic and network pharmacology approach. METHODS:Disease targets in epilepsy and migraine were screened using the DisGeNET database to identify intersecting gene targets. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEEG) enrichment analyses were then performed using the WebGestalt database. Furthermore, the STRING database was used to construct a protein-protein interaction (PPI) network, and Cytoscape software was used to analyze the protein molecular signals at the intersection of epilepsy and migraine. The Drugbank database was used to identify common targets for antiepileptic drugs in epilepsy and migraine to further analyze the disease-gene-target-drug interaction network. Finally, molecular docking simulations were performed to verify the hypothesis that migraine and epilepsy share common diseases and drug targets. RESULTS:A total of 178 common targets for epilepsy and migraine were identified using the DisGeNET database, and the 24 genes most related to the diseases were screened using the Score_gda gene scoring system. GO enrichment analysis indicated that common targets were mainly enriched in biological processes and molecular functions, including membrane potential regulation, inorganic ion transmembrane transport, axonal signaling, and ion channel activity. KEGG pathway enrichment analysis indicated that the mechanism of action might be related to neuroactive ligand receptors, AGE-RAGE, cAMP, and VEGF signaling pathways. The PPI network construction and analysis results showed that the PPI grid had 23 central nodes and 24 connected edges, with an average node degree of 2.09 and an average clustering coefficient of 0.384. The 10 genes with potentially important roles in epilepsy and migraine were CACNA1A, KCNQ2, KCNA1, SCN1A, PRRT2, SCN8A, KCNQ3, SCN2A, GRIN2A, and GABRG2. Drugbank database results indicated that antiepileptic drugs, including lamotrigine, topiramate, valproic acid, carbamazepine, gabapentin, and perampanel, also had common targets with migraine. The three most important targets exhibited strong binding affinity with drugs in the molecular docking simulations. CONCLUSION:Our systematic and comprehensive analyses of disease-gene-target-drug interaction networks identified several biological processes and molecular functions common to migraine and epilepsy, most of which were related to neuroactive ligand-receptor interactions. These data provide a new theoretical basis and reference for the clinical treatment of comorbid epilepsy and migraine and may aid in the development of novel pharmacological strategies.

BACKGROUND:Numerous studies have demonstrated a correlation between asthma and irritable bowel syndrome (IBS). The Chinese herbal compound Shaoyao Gancao Tang (SYGCT) has been found to have therapeutic effects on both asthma and IBS, but the underlying mechanisms are not yet fully understood. This study aims to explore the key components, key targets, and potential mechanisms of SYGCT in treating asthma with IBS by using network pharmacology, molecular docking techniques and molecular dynamics simulation. METHODS:The major chemical components and potential target genes of SYGCT were screened by bioinformatics. The key targets of Asthma-IBS comorbidity were identified based on network modules. The intersection of the drug targets and disease targets was identified as the potential targets of SYGCT in treating asthma-IBS. Gene Ontology functional annotation and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis were performed to identify the biological processes and signaling pathways involved in these potential targets. A protein-protein interaction network was constructed to identify hub targets, while a drug-compound-target topological network was built to screen key compounds. Molecular docking was used to verify the affinity between the hub targets and key compounds. Molecular dynamics analysis was utilized to assess the binding stability of these interactions. RESULTS:Network pharmacology analysis revealed that the therapeutic effect of SYGCT on asthma-IBS involved multiple biological processes and signaling pathways. It may exert therapeutic effects primarily through signaling pathways such as IL-17, TNF, and Th17 cell differentiation. The possible targets of SYGCT in the treatment of asthma-IBS could be IL6, TNF, JUN, PTGS2, STAT3, IL1B, CASP3, NFKBIA, IL10, and PPARG. Molecular docking verification showed that the predicted targets had good binding affinity with the compounds, among which PTGS2, CASP3, and PPARG had higher binding energy. Molecular dynamics simulation revealed that PTGS2, CASP3, and PPARG proteins had good stability and high binding strength with the compounds 2-[(3R)-8,8-dimethyl-3,4-dihydro-2H-pyrano[6,5-f]chromen-3-yl]-5-methoxyphenol and shinpterocarpin. CONCLUSION:SYGCT plays a therapeutic role in asthma and IBS through multiple targets and pathways, providing a theoretical basis for explaining the mechanism and clinical application of SYGCT in treating different diseases with the same treatment in asthma and IBS.

Yinxing Mihuan Oral Solution (YMOS) is a Chinese patent medicine for treating coronary heart disease combined anxiety (CHDCA), but the molecular mechanism of its treatment is still unclear. This article aims to understand the molecular mechanism, optimize clinical drug use, and guide new drug development. Using the Swiss Target Prediction database, we obtained the main chemical composition of YMOS. Then we used network pharmacology to identify their potential targets. Network construction, coupled with protein-protein interaction and enrichment analysis was used to identify representative components and core targets. Finally, molecular docking simulation was conducted to further refine the drug-target interaction. Forty-two active chemicals were found in YMOS and 91 target genes related to CHDCA. The treatment effect was found to be associated with 1908 biological processes and 160 pathways, as revealed by the outcomes of the enrichment analysis. The potential therapeutic mechanisms of the drug are closely related to its antioxidant, anti-inflammatory, and vascular function regulation pathways, and the main core targets include albumin, tumor necrosis factor, TP53, AKT serine/threonine kinase 1, interleukin 1 beta, and vascular endothelial growth factor A. The potential molecular mechanisms of YMOS in CHDCA treatment were identified using network pharmacology and molecular docking approaches. The results reveal the systemic biological implications of YMOS. This study has systematically uncovered the molecular mechanism of YMOS for the first time, offering fresh insights for evidence-based clinical applications.

This study utilized network pharmacology and docking analyses to explore a groundbreaking therapeutic approach for managing the neuropathic pain and depressive disorder (NP/DD) comorbidity. Schisandra chinensis (SC), a common Chinese medicine, has demonstrated numerous beneficial effects in treating neuropsychological disorders. The main objective of this study was to identify potential bioactive components of SC and investigate their interactions with relevant target genes associated with NP/DD. To gain insights into the underlying molecular mechanisms, GO and KEGG analyses were conducted. Furthermore, molecular docking analysis was employed to validate the therapeutic relevance of SC's active ingredients. Seven bioactive components of SC, namely Longikaurin A, Deoxyharringtonine, Angeloylgomisin O, Schisandrin B, Gomisin A, Gomisin G, and Gomisin R, exhibited effectiveness in the treatment of NP/DD. From this list, the first five components were selected for further analysis. The analyses revealed a complex network of interactions between the targets of SC and NP/DD, providing valuable information about the molecular mechanisms involved in the treatment of NP/DD with SC. SC components demonstrated the ability to regulate pathways involving tumor necrosis factor (TNF), vascular endothelial growth factor (VEGF), and other growth hormones (GH). Overall, this study contributes to our understanding of the molecular mechanisms underlying the effects of SC in treating NP/DD. Further investigation is necessary to explore the therapeutic potential of SC as a viable strategy for NP/DD comorbidity. These findings lay a solid foundation for future research endeavors in this field, holding potential implications for the development of novel therapeutic interventions targeting NP/DD.

Endometrial cancer (EC) is a common gynecological malignancy for which polycystic ovarian syndrome (PCOS) has been identified as a significant risk factor. Quercetin, a widely distributed natural flavonoid, has demonstrated potential therapeutic effects in managing both PCOS and EC. However, the specific molecular targets of quercetin in the context of PCOS comorbid with EC (PCOS-EC) remain poorly defined. This study aims to elucidate the therapeutic potential of quercetin for treating PCOS-EC using network pharmacology, molecular dynamics simulations, and in vitro assays. The intersection of 379 PCOS-EC-associated targets with 361 quercetin targets identified 47 potential therapeutic targets of quercetin for PCOS-EC. Gene Ontology enrichment analysis revealed the biological functions, while Kyoto Encyclopedia of Genes and Genomes identified the pathways potentially involved in quercetin's effects against PCOS-EC. Protein-protein interaction network analysis highlighted six overlapping targets, namely, ACTB, AKT1, EGFR, ESR1, PTGS2, and TP53. Molecular docking and molecular dynamics simulations indicated that quercetin bound with high affinity to the hub genes, with AKT1 emerging as a central target. In vitro experiments confirmed that quercetin treatment significantly downregulated AKT expression in EC cells. These findings elucidate potential targets and molecular mechanisms through which quercetin exerts its therapeutic effects.

BACKGROUND:Guanxinning tablet (GXNT), a Chinese patent medicine, is composed of salvia miltiorrhiza bunge and ligusticum striatum DC, which may play the role of endothelial protection through many pathways. We aimed to explore the molecular mechanisms of GXNT against atherosclerosis (AS) through network pharmacology and molecular docking verification. METHODS:The active ingredients and their potential targets of GXNT were obtained in traditional Chinese medicine systems pharmacology database and analysis platform and bioinformatics analysis tool for molecular mechanism of traditional Chinese medicine databases. DrugBank, TTD, DisGeNET, OMIM, and GeneCards databases were used to screen the targets of AS. The intersection targets gene ontology and Kyoto encyclopedia of genes and genomes enrichment analysis were performed in DAVID database. GXNT-AS protein-protein interaction network, ingredient-target network and herb-target-pathway network were constructed by Cytoscape. Finally, we used AutoDock for molecular docking. RESULTS:We screened 65 active ingredients of GXNT and 70 GXNT-AS intersection targets. The key targets of protein-protein interaction network were AKT1, JUN, STAT3, TNF, TP53, IL6, EGFR, MAPK14, RELA, and CASP3. The Kyoto encyclopedia of genes and genomes pathway enrichment analysis showed that pathways in cancer, lipid and atherosclerosis, and PI3K-Akt signaling pathway were the main pathways. The ingredient-target network showed that the key ingredients were luteolin, tanshinone IIA, myricanone, dihydrotanshinlactone, dan-shexinkum d, 2-isopropyl-8-methylphenanthrene-3,4-dione, miltionone I, deoxyneocryptotanshinone, Isotanshinone II and 4-methylenemiltirone. The results of molecular docking showed that tanshinone IIA, dihydrotanshinlactone, dan-shexinkum d, 2-isopropyl-8-methylphenanthrene-3,4-dione, miltionone I, deoxyneocryptotanshinone, Isotanshinone II and 4-methylenemiltirone all had good binding interactions with AKT1, EGFR and MAPK14. CONCLUSION:The results of network pharmacology and molecular docking showed that the multiple ingredients within GXNT may confer protective effects on the vascular endothelium against AS through multitarget and multichannel mechanisms. AKT1, EGFR and MAPK14 were the core potential targets of GXNT against AS.

BACKGROUND:Non-small cell lung cancer (NSCLC) is a leading cause of cancer-related burden and deaths, thus effective treatment strategies with lower side effects for NSCLC are urgently needed. To systematically analyze the mechanism of Bai He Gu Jin Tang (BHGJT) against NSCLC by network pharmacology and molecular docking. METHODS:The active compounds of BHGJT were obtained by searching the Bioinformatics Analysis Tool for Molecular Mechanism of Traditional Chinese Medicine and Encyclopaedia of Traditional Chinese Medicine. Search tool for interactions of chemicals was used for acquiring the targets of BHGJT. The component-target network was mapped by Cytoscape. NSCLC-related genes were obtained by searching Genecards, DrugBank and Therapeutic Target Database. The protein-protein interaction network of intersection targets was established based on Search Tool for Recurring Instances of Neighboring Genes (STRING), and further, the therapeutic core targets were selected by topological parameters. The hub targets were transmitted to Database for Annotation, Visualization and Integrated Discovery for gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. Finally, AutoDock Vina and MglTools were employed for molecular docking validation. RESULTS:Two hundred fifty-six compounds and 237 putative targets of BHGJT-related active compounds as well as 1721potential targets of NSCLC were retrieved. Network analysis showed that 8 active compounds of BHGJT including kaempferol, quercetin, luteolin, isorhamnetin, beta-sitosterol, stigmasterol, mairin and liquiritigenin as well as 15 hub targets such as AKR1B10 and AKR1C2 contribute to the treatment of BHGJT against NSCLC. GO functional enrichment analysis shows that BHGJT could regulate many biological processes, such as apoptotic process. Three modules of the endocrine related pathways including the inflammation, hypoxia related pathways as well as the other cancer related pathways based on Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis might explain the biological mechanisms of BHGJT in treating BHGJT. The results of molecular docking verified that AKR1B10 and AKR1C2 had the strongest binding activity with the 8 key compounds of NSCLC. CONCLUSION:Our study reveals the mechanism of BHGJT in treating NSCLC involving multiple components, multiple targets and multiple pathways. The present study laid an initial foundation for the subsequent research and clinical application of BHGJT and its active compounds against NSCLC.

Inflammatory bowel disease (IBD) is a persistent, non-specific inflammation affecting the intestines. Psoriasis is a long-lasting inflammatory disorder of the skin. There is a comorbidity correlation between IBD and psoriasis, but the specific pathogenesis of the comorbidity is unclear. In this study, we analyzed datasets sourced from the Gene Expression Omnibus (GEO) database, and identified shared genes of IBD and psoriasis through differential expression analysis and weighted gene co-expression network analysis (WGCNA). Then three machine learning algorithms were applied to identify shared diagnostic genes. Next, the validation of shared diagnostic genes was evaluated with ROC curves, with the AUC determined. Subsequently, single sample gene set enrichment analysis (ssGSEA) and immune infiltration analysis were conducted. Furthermore, we obtained potential drugs such as securinine in the Drug Signature Database (DsigDB) and 7 traditional Chinese medicines in the Coremine database, which might have therapeutic effects on the comorbidity of IBD and psoriasis. Finally, we confirmed the expression of the shared diagnostic gene in colitis and psoriasis mice tissues through RT-PCR, Western blot and immunohistochemistry (IHC) methods. The results showed that AQP9 had the highest diagnostic value for two diseases. AQP9 had AUC values of 93.681% for UC, 89.629% for CD,and 78.689% for psoriasis in the internal validation datasets. In the external validation datasets, AQP9 had AUC values of 90.394% for UC, 93.909% for CD,and 82.906% for psoriasis. Immune infiltration analysis and ssGSEA revealed that AQP9 might impact the disease process of IBD and psoriasis by participating in the NF-kappaB signaling pathway, and modulating immune cell differentiation. Furthermore, the expression levels of AQP9 were consistently validated, showing upregulation in IBD and downregulation in psoriasis, compared to the control group. This study revealed the shared diagnostic genes and potential mechanisms of the comorbidity of IBD and psoriasis, providing new directions for future research on exploring the comorbidity mechanisms and treatment targets.

Patients with colonic adenocarcinoma (COAD) are at relatively high risk of SARS-CoV-2 infection. However, there is a lack of medical strategies to treat COVID-19/COAD comorbidity. Puerarin, a natural product, is a known antiviral, antitumor, and immunomodulatory effect. Therefore, we hypothesised that puerarin could be used to treat COVID-19/COAD patients. Based on network pharmacology and bioinformatics analysis, the potential targets and pharmacological mechanisms of puerarin in COVID-19/COAD were identified. By intersecting therapeutic target genes for puerarin, COVID-19-related genes and COAD-related genes, 42 target genes of puerarin that could potentially treat COVID-19/COAD comorbidity were obtained. By using the 42 potential target genes to construct the protein-protein interaction (PPI) network, we obtained five core target genes, namely RELA, BCL2, JUN, FOS, and MAPK1. The results of bioinformatics analysis revealed that puerarin could be able to treat COVID-19/COAD comorbidity through apoptosis, antiviral, antioxidant, NF-κB signaling pathway, MAPK signaling pathway, IL-17 signaling pathway, TNF signaling pathway, and HIF-1 signaling pathway etc. This study found that puerarin has the potential to treat COVID-19/COAD patients and that the therapeutic target genes obtained in the study may provide clues for the treatment of COVID19/COAD comorbidity.

Background:Ankylosing spondylitis (AS) and inflammatory bowel disease (IBD) are prevalent autoimmune disorders that often co-occur, posing significant treatment challenges. This investigation adopts a multidisciplinary strategy, integrating bioinformatics, network pharmacology, molecular docking, and Mendelian randomization, to elucidate the relationship between AS and IBD and to investigate the potential mechanisms of traditional Chinese medicine formulations, represented by Qiangji Jianpi (QJJP) decoction, in treating these comorbid conditions. Methods:We utilized databases to pinpoint common targets among AS, IBD, and QJJP decoction's active compounds through intersection analysis. Through Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses, we mapped a network in Cytoscape, isolating critical targets. Molecular docking with AutoDock validated the affinity between targets and compounds. ROC analysis and dataset validation assessed diagnostic performance, while Gene Set Enrichment Analysis (GSEA) offered pathway insights. Mendelian randomization explored the AS-IBD causal relationship. Results:Screening identified 105 targets for QJJP decoction, 414 for AS, and 2420 for IBD, with 85 overlapping. These targets predominantly participate in organismal responses and DNA transcription factor binding, with a significant cellular presence in the endoplasmic reticulum and vesicle lumen. Molecular docking, facilitated by Cytoscape, confirmed IL1A, IFNG, TGFB1, and EDN1 as critical targets, with IFNG demonstrating diagnostic potential through GEO dataset validation. The integration of GSEA with network pharmacology highlighted the therapeutic significance of the relaxin, osteoclast differentiation, HIF-1, and AGE-RAGE signaling pathways in QJJP decoction's action. Mendelian randomization analysis indicated a positive causal relationship between IBD and AS, pinpointing rs2193041 as a key SNP influencing IFNG. Conclusion:Based on the principle of "treating different diseases with the same method" in traditional Chinese medicine theory, we explored the intricate mechanisms through which QJJP decoction addresses AS and IBD comorbidity. Our research spotlighted the pivotal role of the IFNG gene. IFNG emerges not only as a key therapeutic target but also assumes significance as a potential diagnostic biomarker through its genetic underpinnings. This investigation establishes a solid base for subsequent experimental inquiries. Our findings introduce novel approaches for incorporating traditional Chinese medicine into the treatment of AS-IBD comorbidity, setting the stage for groundbreaking research directions.

Background:Although previous clinical studies and animal experiments have demonstrated the efficacy of Gegen Qinlian Decoction (GQD) in treating Type 2 Diabetes Mellitus (T2DM) and Ulcerative Colitis (UC), the underlying mechanisms of its therapeutic effects remain elusive. Purpose:This study aims to investigate the shared pathogenic mechanisms between T2DM and UC and elucidate the mechanisms through which GQD modulates these diseases using bioinformatics approaches. Methods:Data for this study were sourced from the Gene Expression Omnibus (GEO) database. Targets of GQD were identified using PharmMapper and SwissTargetPrediction, while targets associated with T2DM and UC were compiled from the DrugBank, GeneCards, Therapeutic Target Database (TTD), DisGeNET databases, and differentially expressed genes (DEGs). Our analysis encompassed six approaches: weighted gene co-expression network analysis (WGCNA), immune infiltration analysis, single-cell sequencing analysis, machine learning, DEG analysis, and network pharmacology. Results:Through GO and KEGG analysis of weighted gene co-expression network analysis (WGCNA) modular genes and DEGs intersection, we found that the co-morbidity between T2DM and UC is primarily associated with immune-inflammatory pathways, including IL-17, TNF, chemokine, and toll-like receptor signaling pathways. Immune infiltration analysis supported these findings. Three distinct machine learning studies identified IGFBP3 as a biomarker for GQD in treating T2DM, while BACE2, EPHB4, and EPHA2 emerged as biomarkers for GQD in UC treatment. Network pharmacology revealed that GQD treatment for T2DM and UC mainly targets immune-inflammatory pathways like Toll-like receptor, IL-17, TNF, MAPK, and PI3K-Akt signaling pathways. Conclusion:This study provides insights into the shared pathogenesis of T2DM and UC and clarifies the regulatory mechanisms of GQD on these conditions. It also proposes novel targets and therapeutic strategies for individuals suffering from T2DM and UC.

The Yizhiqinxin formula (YZQX) has been used to treat Alzheimer's disease (AD) or major depression disorder (MDD). However, its specific underlying mechanisms and therapeutic targets remain unclear. The ingredients and putative targets of YZQX were screened using the TCMSP and Drugbank databases. Next, the GEO database was used to retrieve relevant differentially expressed genes (DEGs) in AD or MDD and normal tissues. The PPI network was established, merged, and further screened to identify the main ingredients and core targets of YZQX against AD and MDD comorbidities. We performed enrichment analysis of core targets to identify biological processes and pathways. Finally, AutoDock software was used to validate the binding affinity between the crucial targets of direct action and their corresponding ingredients. A total of 43 ingredients were identified from YZQX, of which 43 were screened to yield 504 targets. By establishing the PPI network, 92 targets were regarded as targets of YZQX against AD and MDD comorbidities in the core network. Promising targets (, , , , , , , , , , and ) and signaling pathways (PI3K-Akt signaling pathway, ubiquitin-mediated proteolysis, MAPK signaling pathway, etc.) were filtered and refined to elucidate the underlying mechanism of YZQX against AD and MDD comorbidities. Molecular docking confirmed the ingredients of YZQX (quercetin and kaempferol) could bind well to multiple crucial targets. The ingredients of YZQX, such as quercetin and kaempferol, might treat AD and MDD comorbidities by acting on multiple targets and pathways.