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Herbs, such as Aconitum carmichaeli Debeaux (ACD), have long been used as therapies, but it is difficult to identify which organs of the human body are affected by the various compounds. In this study, we predicted the organ where the drug predominantly acts using bioinformatics and verified it using transcriptomics. We constructed a computer-aided brain system network (BSN) and intestinal system network (ISN). We predicted the action points of ACD using network pharmacology (NP) analysis and predicted the dockable proteins acting in the BSN and ISN using statistical-based docking analysis. The predicted results were verified using ACD-induced transcriptome analysis. The predicted results showed that both the NP and docking analyses predominantly acted on the BSN and showed better hit rates in the hub nodes. In addition, we confirmed through verification experiments that the SW1783 cell line had more than 10 times more differentially expressed genes than the HT29 cell line and that the dominant acting organ is the brain, using network dimension spanning analysis. In conclusion, we found that ACD preferentially acts in the brain rather than in the intestine, and this multi-bioinformatics-based approach is expected to be used in future studies of drug efficacy and side effects. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [Display omitted] • Novel mechanisms of action of PR are explored via systematic transcriptome analysis. • Aurora B pathway significantly decreased in PR-treated cells. • HG and OA have an inhibitory effect on Aurora B pathway. • PR extracts are highly effective in suppressing cell growth and colony formation. • PR extracts inhibit Aurora kinase activity. [ABSTRACT FROM AUTHOR]

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., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Park, Kim, Lee, Baek, Kim, Park, Yi and Cha.)

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 .