Reynoutria japonica consisted of emodin-8-ß-D-glucoside ameliorates Dermatophagoides farinae extract-induced atopic dermatitis-like skin inflammation in mice by inhibiting JAK/STAT signaling.

Atopic dermatitis (AD) is a chronic inflammatory skin disease characterized by skin barrier dysfunction and chronic inflammatory responses. Reynoutria japonica, known as Huzhang in traditional Chinese Medicine, can enhance blood circulation to eliminate wind pathogens and terminate coughing. Despite pharmacological evidence supporting the efficacy of R. japonica in suppressing edema-induced skin inflammation or connective tissue diseases, its pharmaceutical potential for treating AD-like skin inflammation remains unexplored. This study investigated the possible effects of R. japonica ethanol extract (RJE) on Dermatophagoides farinae extract (DfE)-induced AD-like skin inflammation in NC/Nga mice. To elucidate the underlying mechanisms by which RJE inhibits skin inflammation, we examined the effect of RJE on IFN-γ/TNF-α-induced signal transducer and activator of transcription (STAT) signaling in human epidermal keratinocytes (HEKs) and human dermal fibroblasts (HDFs). Our findings revealed that RJE mitigates DfE-induced AD-like symptoms and skin barrier disruptions in mouse skin lesions. Moreover, RJE attenuated DfE-induced mast cell infiltration and serum levels of inflammatory cytokines (IL-1α, IL-1ß, IL-6, IL-23, IFN-γ, TNF-α, and GM-CSF). RJE also inhibited IFN-γ/TNF-α-induced chemokine levels and STAT3 phosphorylation in HEKs and HDFs. Virtual binding analysis of the RJE components suggested that emodin-8-ß-D-glucoside binds to Janus kinase (JAK) 1/2, thereby suppressing STAT signaling, which was confirmed by Western blot analysis. In conclusion, our results suggest that RJE may alleviate DfE-induced skin barrier dysfunction by inhibiting JAK/STAT signaling and the proinflammatory immune response through the suppression of inflammatory mediators in AD-like skin disease. These findings suggest that RJE has potential as an effective therapy for AD management.

Effect of Poria cocos Terpenes: Verifying Modes of Action Using Molecular Docking, Drug-Induced Transcriptomes, and Diffusion Network Analyses.

We characterized the therapeutic biological modes of action of several terpenes in Poria cocos F.A Wolf (PC) and proposed a broad therapeutic mode of action for PC. Molecular docking and drug-induced transcriptome analysis were performed to confirm the pharmacological mechanism of PC terpene, and a new analysis method, namely diffusion network analysis, was proposed to verify the mechanism of action against Alzheimer's disease. We confirmed that the compound that exists only in PC has a unique mechanism through statistical-based docking analysis. Also, docking and transcriptomic analysis results could reflect results in clinical practice when used complementarily. The detailed pharmacological mechanism of PC was confirmed by constructing and analyzing the Alzheimer's disease diffusion network, and the antioxidant activity based on microglial cells was verified. In this study, we used two bioinformatics approaches to reveal PC's broad mode of action while also using diffusion networks to identify its detailed pharmacological mechanisms of action. The results of this study provide evidence that future pharmacological mechanism analysis should simultaneously consider complementary docking and transcriptomics and suggest diffusion network analysis, a new method to derive pharmacological mechanisms based on natural complex compounds.

Jakyak-gamcho-tang, a decoction of Paeoniae Radix and Glycyrrhizae Radix et Rhizoma, ameliorates dexamethasone-induced muscle atrophy and muscle dysfunction.

BACKGROUND: Although chronic treatment with glucocorticoids, such as dexamethasone, is frequently associated with muscle atrophy, effective and safe therapeutics for treating muscle atrophy remain elusive. Jakyak-gamcho-tang (JGT), a decoction of Paeoniae Radix and Glycyrrhizae Radix et Rhizoma, has long been used to relieve muscle tension and control muscle cramp-related pain. However, the effects of JGT on glucocorticoid-induced muscle atrophy are yet to be comprehensively clarified. PURPOSE: The objective of the current study was to validate the protective effect of JGT in dexamethasone-induced muscle atrophy models and elucidate its underlying mechanism through integrated in silico - in vitro - in vivo studies. STUDY DESIGN AND METHODS: Differential gene expression was preliminarily analyzed using the RNA-seq data to determine the effects of JGT on C2C12 myotubes. The protective effects of JGT were further validated in dexamethasone-treated C2C12 myotubes by assessing cell viability, myotube integrity, and mitochondrial function or in C57BL/6 N male mice with dexamethasone-induced muscle atrophy by evaluating muscle mass and physical performance. Transcriptomic pathway analysis was also performed to elucidate the underlying mechanism. RESULTS: Based on preliminary gene set enrichment analysis using the RNA-seq data, JGT regulated various pathways related to muscle differentiation and regeneration. Dexamethasone-treated C2C12 myotubes and muscle tissues of atrophic mice displayed substantial muscle protein degradation and muscle loss, respectively, which was efficiently alleviated by JGT treatment. Importantly, JGT-mediated protective effects were associated with observations such as preservation of mitochondrial function, upregulation of myogenic signaling pathways, including protein kinase B/mammalian target of rapamycin/forkhead box O3, inhibition of ubiquitin-mediated muscle protein breakdown, and downregulation of inflammatory and apoptotic pathways induced by dexamethasone. CONCLUSION: To the best of our knowledge, this is the first report to demonstrate that JGT could be a potential pharmaceutical candidate to prevent muscle atrophy induced by chronic glucocorticoid treatment, highlighting its known effects for relieving muscle spasms and pain. Moreover, transcriptomic pathway analysis can be employed as an efficient in silico tool to predict novel pharmacological candidates and elucidate molecular mechanisms underlying the effects of herbal medications comprising diverse biologically active ingredients.

Comparative study of the mechanism of natural compounds with similar structures using docking and transcriptome data for improving in silico herbal medicine experimentations.

Natural products have successfully treated several diseases using a multi-component, multi-target mechanism. However, a precise mechanism of action (MOA) has not been identified. Systems pharmacology methods have been used to overcome these challenges. However, there is a limitation as those similar mechanisms of similar components cannot be identified. In this study, comparisons of physicochemical descriptors, molecular docking analysis and RNA-seq analysis were performed to compare the MOA of similar compounds and to confirm the changes observed when similar compounds were mixed and used. Various analyses have confirmed that compounds with similar structures share similar MOA. We propose an advanced method for in silico experiments in herbal medicine research based on the results. Our study has three novel findings. First, an advanced network pharmacology research method was suggested by partially presenting a solution to the difficulty in identifying multi-component mechanisms. Second, a new natural product analysis method was proposed using large-scale molecular docking analysis. Finally, various biological data and analysis methods were used, such as in silico system pharmacology, docking analysis and drug response RNA-seq. The results of this study are meaningful in that they suggest an analysis strategy that can improve existing systems pharmacology research analysis methods by showing that natural product-derived compounds with the same scaffold have the same mechanism.

Veronica persica Ethanol Extract Ameliorates Dinitrochlorobenzene-Induced Atopic Dermatitis-like Skin Inflammation in Mice, Likely by Inducing Nrf2/HO-1 Signaling.

Atopic dermatitis (AD) is chronic allergic contact dermatitis with immune dysregulation. Veronica persica has pharmacological activity that prevents asthmatic inflammation by ameliorating inflammatory cell activation. However, the potential effects of the ethanol extract of V. persica (EEVP) on AD remain elusive. This study evaluated the activity and underlying molecular pathway of EEVP in two AD models: dinitrochlorobenzene (DNCB)-induced mice and interferon (IFN)-γ/tumor necrosis factor (TNF)-α-stimulated human HaCaT keratinocytes. EEVP attenuated the DNCB-induced increase in serum immunoglobulin E and histamine levels, mast cell counts in toluidine-blue-stained dorsal skin, inflammatory cytokine (IFN-γ, interleukin [IL]-4, IL-5, and IL-13) levels in cultured splenocytes, and the mRNA expression of IL6, IL13, IL31 receptor, CCR-3, and TNFα in dorsal tissue. Additionally, EEVP inhibited the IFN-γ/TNF-α-induced mRNA expression of IL6, IL13, and CXCL10 in HaCaT cells. Furthermore, EEVP restored the IFN-γ/TNF-α-induced downregulation of heme oxygenase (HO)-1 in HaCaT cells by inducing nuclear factor erythroid 2-related factor 2 (Nrf2) expression. A molecular docking analysis demonstrated that EEVP components have a strong affinity to the Kelch-like ECH-associated protein 1 Kelch domain. In summary, EEVP inhibits inflammatory AD by attenuating immune cell activation and inducing the Nrf2/HO-1 signaling pathway in skin keratinocytes.

Gene expression profiling of nasal inflammation induced by diesel particles using an in vivo system.

Korean diesel particulate matter 20 (KDP20) is a pollutant comprising a complex mixture of carbon and chemical irritants. Although particulate matter and nasal inflammation are strongly associated, the underlying molecular mechanism based on systematic transcriptome analysis remains unknown. In this study, genome-wide gene expression profiles of mouse nasal tissues were determined following exposure to KDP20 for 5 and 10 days and compared with those of the control (n = 4/group). We identified 758 significant differentially expressed genes (DEGs) and classified them as 5-day-specific, 10-day-specific, and common among groups based on their expression patterns. The terms "regulation of alpha-beta T cell differentiation," "macrophage differentiation," and "cell adhesion mediated by integrin" were significantly enriched in each group. Receiver operating characteristic analysis revealed six genes as potential predictive biomarkers. The differential expression of these six genes was validated using quantitative RT-PCR (n = 3/group). Furthermore, a possible mechanism for nasal inflammation was suggested through the binding analysis between metal ions and genes. The genes identified in this study may play important roles in regulating the mechanism of nasal inflammation induced by diesel particles, especially immune cell regulation, and may function as markers for diesel particle-induced nasal inflammation.

Systematic transcriptome analysis reveals molecular mechanisms and indications of bupleuri radix.

Pharmacogenomic analysis based on drug transcriptomic signatures is widely used to identify mechanisms of action and pharmacological indications. Despite accumulating reports on the efficacy of medicinal herbs, related transcriptome-level analyses are lacking. The aim of the present study was to elucidate the underlying molecular mechanisms of action of Bupleuri Radix (BR), a widely used herbal medicine, through a systematic transcriptomic analysis. We analyzed the drug-responsive transcriptome profiling of A549 lung cancer cell line after treating them with multiple doses of BR water (W-BR) and ethanol (E-BR) extracts and their phytochemicals. In vitro validation experiments were performed using both A549 and the immortalized human keratinocyte line HaCaT. Pathway enrichment analysis revealed the anti-cancer effects of BR treatment via inhibition of cell proliferation and induction of apoptosis. Enhanced cell adhesion and migration were observed with the W-BR but not with the E-BR. Comparison with a disease signature database validated an indication of the W-BR for skin disorders. Moreover, W-BR treatment showed the wound-healing effect in skin and lung cells. The main active ingredients of BR showed only the anti-cancer effect of the E-BR and not the wound healing effect of the W-BR, suggesting the need for research on minor ingredients of BR.

Individualized Diagnosis and Prescription in Traditional Medicine: Decision-Making Process Analysis and Machine Learning-Based Analysis Tool Development.

While pattern identification (PI) is an essential process in traditional medicine (TM), it is difficult to objectify since it relies heavily on implicit knowledge. Therefore, this study aimed to propose a machine learning (ML)-based analysis tool to evaluate the clinical decision-making process of PI in terms of explicit and implicit knowledge, and to observe the actual process by which this knowledge affects the choice of diagnosis and treatment in individual TM doctors. Clinical data for the development of the analysis tool were collected using a questionnaire administered to allergic rhinitis (AR) patients and the diagnosis and prescription results of TM doctors based on the completed AR questionnaires. Explicit knowledge and implicit knowledge were defined based on the doctors' explicit scoring and feature evaluations of ML models, respectively. There were many differences between the explicit and implicit importance scores in this study. Implicit importance is more closely related to explicit importance in prescription than in diagnosis. The analysis results for eight doctors showed that our tool could successfully identify explicit and implicit knowledge in the PI process. This is the first study to evaluate the actual process by which explicit and implicit knowledge affect the choice of individual TM doctors and to identify assessment tools for the definition of the decision-making process in diagnosing PI and prescribing herbal treatments by TM clinicians. The assessment tool suggested in this study could be broadly used for the standardization of precision medicine, including TM therapeutics.

Systems pharmacology approaches in herbal medicine research: a brief review.

Herbal medicine, a multi-component treatment, has been extensively practiced for treating various symptoms and diseases. However, its molecular mechanism of action on the human body is unknown, which impedes the development and application of herbal medicine. To address this, recent studies are increasingly adopting systems pharmacology, which interprets pharmacological effects of drugs from consequences of the interaction networks that drugs might have. Most conventional network- based approaches collect associations of herb-compound, compound-target, and target-disease from individual databases, respectively, and construct an integrated network of herb-compound- target-disease to study the complex mechanisms underlying herbal treatment. More recently, rapid advances in highthroughput omics technology have led numerous studies to exploring gene expression profiles induced by herbal treatments to elicit information on direct associations between herbs and genes at the genome-wide scale. In this review, we summarize key databases and computational methods utilized in systems pharmacology for studying herbal medicine. We also highlight recent studies that identify modes of action or novel indications of herbal medicine by harnessing drug-induced transcriptome data. [BMB Reports 2022; 55(9): 417-428].

Identification of a novel anticancer mechanism of Paeoniae Radix extracts based on systematic transcriptome analysis.

Paeoniae Radix (PR) has a great therapeutic value in many clinical applications; however, the presence of various bioactive compounds and its complicated effects on human health makes its precise mechanisms of action unclear. This study investigated the effects of PR at the molecular pathway level by profiling genome-wide gene expression changes following dose-dependent treatment of human lung cancer cells (A549) with PR water extract (WPR), PR ethanol extracts (EPR), as well as their individual components. We found that PR exerts anticancer effects in A549 cells by regulating numerous pathways. Specifically, EPR and two compounds, namely, hederagenin (HG) and oleanolic acid (OA), significantly downregulate the Aurora B pathway. Furthermore, we generated an integrated PR extracts-compounds-target genes network in the Aurora B pathway to understand their interactions. Our findings reinforce that inhibiting Aurora kinase activity is a therapeutic target for treating cancers, providing the potential for novel mechanisms of action for PR and its components against lung cancer.

Identification of gallic acid as a active ingredient of Syzygium aromaticum against tacrolimus-induced damage in renal epithelial LLC-PK1 cells and rat kidney.

Tacrolimus (FK506), a calcineurin inhibitor, is an effective immunosuppressive agent mainly used to lower the risk of organ rejection after allogeneic organ transplant. However, FK506-associated adverse effects, such as nephrotoxicity, may limit its therapeutic use. In this study, we confirmed that epigallocatechin-3-gallate (EGCG), sanguiin H-6, and gallic acid increased cell survival following FK506-induced cytotoxicity in renal epithelial LLC-PK1. Among these compounds, gallic acid exerted the strongest protective effect, further confirmed in the FK506-induced nephrotoxicity rat model. Additionally, we identified supporting evidence for the nephroprotective function of gallic acid using molecular docking and bioavailability investigations.

Machine learning-based prediction of Sasang constitution types using comprehensive clinical information and identification of key features for diagnosis.

BACKGROUND: Despite the importance of accurate Sasang type diagnosis, a unique form of Korean medicine, there have been concerns about consistency among diagnoses. We investigate a data-driven integrative diagnostic model by applying machine learning to a multicenter clinical dataset with comprehensive features. METHODS: Extremely randomized trees (ERT), support vector machines, multinomial logistic regression, and K-nearest neighbor were applied, and performances were evaluated by cross-validation. The feature importance of the classifier was analyzed to understand which information is crucial in diagnosis. RESULTS: The ERT classifier showed the highest performance, with an overall f1 score of 0.60 ± 0.060. The feature classes of body measurement, personality, general information, and cold-heat were more decisive than others in classifying Sasang types. Costal angle was the most informative feature. In pairwise classification, we found Sasang type-dependent distinctions that body measurement features played a key role in TE-SE and TE-SY datasets, while personality and cold-heat features showed importance in SE-SY dataset. CONCLUSION: Current study investigated a comprehensive diagnostic model for Sasang type using machine learning and achieved better performance than previous studies. This study helps data-driven decision making in clinics by revealing key features contributing to the Sasang type diagnosis.

Neuroprotective γ-Pyrones from Fusarium Solani JS-0169: Cell-Based Identification of Active Compounds and an Informatics Approach to Predict the Mechanism of Action.

Glutamate toxicity has been implicated in neuronal cell death in both acute CNS injury and in chronic diseases. In our search for neuroprotective agents obtained from natural sources that inhibit glutamate toxicity, an endophytic fungus, Fusarium solani JS-0169 isolated from the leaves of Morus alba, was found to show potent inhibitory activity. Chemical investigation of the cultures of the fungus JS-0169 afforded isolation of six compounds, including one new γ-pyrone (1), a known γ-pyrone, fusarester D (2), and four known naphthoquinones: karuquinone B (3), javanicin (4), solaniol (5), and fusarubin (6). To identify the protective effects of the isolated compounds (1-6), we assessed their inhibitory effect against glutamate-induced cytotoxicity in HT22 cells. Among the isolates, compound 6 showed significant neuroprotective activity on glutamate-mediated HT22 cell death. In addition, the informatics approach using in silico systems pharmacology identified that compound 6 may exert its neuroprotective effect by controlling the amount of ubiquinone. The results suggest that the metabolites produced by the endophyte Fusarium solani JS-0169 might be related to the neuroprotective activity of its host plant, M. alba.

Absolute Configuration and Corrected NMR Assignment of 17-Hydroxycyclooctatin, a Fused 5-8-5 Tricyclic Diterpene.

The absolute configuration and corrected NMR assignment of 17-hydroxycyclooctatin isolated from Streptomyces sp. M56 recovered from a nest of South African Macrotermes natalensis termites are reported. 17-Hydroxycyclooctatin is a unique tricyclic diterpene (C20) consisting of a fused 5-8-5 ring system, and in this study, its structure was unambiguously determined by a combination of HR-ESIMS and 1D and 2D NMR spectroscopic experiments to produce corrected NMR assignments. The absolute configuration of 17-hydroxycyclooctatin is reported for the first time in the current study using chemical reactions and quantum chemical ECD calculations. The corrected NMR assignments were verified using a gauge-including atomic orbital NMR chemical shifts calculation, followed by DP4 probability. To understand the pharmacological properties of 17-hydroxycyclooctatin, a network pharmacological approach and molecular docking analyses were used, which also predicted its effects on human breast cancer cell lines. Cytotoxicity and antiestrogenic activity of 17-hydroxycyclooctatin were determined, and it was found this compound may be an ERα antagonist.

A Systems-Level Analysis of Mechanisms of Platycodon grandiflorum Based on A Network Pharmacological Approach.

Platycodon grandiflorum (PG) is widely used in Asia for its various beneficial effects. Although many studies were conducted to understand the molecular mechanisms of PG, it is still unclear how the combinations of multiple ingredients work together to exert its therapeutic effects. The aim of the present study was to provide a comprehensive review of the systems-level mechanisms of PG by adopting network pharmacological analysis. We constructed a compound⁻target⁻disease network for PG using experimentally validated and machine-leaning-based prediction results. Each target of the network was analyzed based on previously known pharmacological activities of PG. Gene ontology analysis revealed that the majority of targets were related to cellular and metabolic processes, responses to stimuli, and biological regulation. In pathway enrichment analyses of targets, the terms related to cancer showed the most significant enrichment and formed distinct clusters. Degree matrix analysis for target⁻disease associations of PG suggested the therapeutic potential of PG in various cancers including hepatocellular carcinoma, gastric cancer, prostate cancer, small-cell lung cancer, and renal cell carcinoma. We expect that network pharmacological approaches will provide an understanding of the systems-level mechanisms of medicinal herbs and further develop their therapeutic potentials.