MSH-DTI: multi-graph convolution with self-supervised embedding and heterogeneous aggregation for drug-target interaction prediction.

BACKGROUND: The rise of network pharmacology has led to the widespread use of network-based computational methods in predicting drug target interaction (DTI). However, existing DTI prediction models typically rely on a limited amount of data to extract drug and target features, potentially affecting the comprehensiveness and robustness of features. In addition, although multiple networks are used for DTI prediction, the integration of heterogeneous information often involves simplistic aggregation and attention mechanisms, which may impose certain limitations. RESULTS: MSH-DTI, a deep learning model for predicting drug-target interactions, is proposed in this paper. The model uses self-supervised learning methods to obtain drug and target structure features. A Heterogeneous Interaction-enhanced Feature Fusion Module is designed for multi-graph construction, and the graph convolutional networks are used to extract node features. With the help of an attention mechanism, the model focuses on the important parts of different features for prediction. Experimental results show that the AUROC and AUPR of MSH-DTI are 0.9620 and 0.9605 respectively, outperforming other models on the DTINet dataset. CONCLUSION: The proposed MSH-DTI is a helpful tool to discover drug-target interactions, which is also validated through case studies in predicting new DTIs.

Exploring the mechanism of Lianhuaqingwen (LHQW) in treating chronic bronchitis based on network pharmacology and experimental validation.

BACKGROUND: Lianhuaqingwen (LHQW) has been used in the treatment of chronic bronchitis, but the precise mechanism through which LHQW exhibits its anti-inflammatory effects in this context is not yet fully understood. The aim of this study was to investigate the active ingredients and signaling pathways responsible for LHQW's effectiveness in managing chronic bronchitis. METHODS: The research leveraged the TCMSP database to determine the active compounds and drug targets of LHQW. In parallel, the GeneCards, DrugBank, and PharmGkb databases were used to uncover targets pertinent to chronic bronchitis. To discern the potential mechanisms by which LHQW's active ingredients might treat chronic bronchitis, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed. Network pharmacology facilitated the construction of a drug-active ingredient-disease target network, aiding in forecasting the core targets for chronic bronchitis treatment by LHQW. Subsequently, molecular docking techniques alongside in vitro experiments were applied to confirm the interactions between the active ingredients and the primary targets. RESULTS: A total of 157 active ingredients, 225 potential drug targets, and 594 bronchitis-related targets were derived from various databases. Following this, 76 potential gene targets were pinpointed by integrating drug and related targets. GO and KEGG enrichment analyses were employed to identify key pathways involved in LHQW's mechanism for treating chronic bronchitis. By constructing a protein-protein interaction (PPI) network for the 76 potential gene targets, four core targets (TNF, IL6, IFNG, and STAT3) were identified as primarily involved in responses to lipopolysaccharide, the TNF pathway, and the JAK-STAT pathway. Molecular docking results revealed a favorable affinity between multiple active ingredients of LHQW and the four core targets, suggesting that the therapeutic effects are mediated through the inhibition of inflammatory responses and signaling pathways. Interestingly, quercetin, an active ingredient of LHQW, was observed to bind to all four core targets simultaneously. Furthermore, cell experiment and western blot analysis indicated that both LHQW and quercetin exhibit anti-inflammatory effects by targeting the four core proteins and the JAK-STAT pathways. CONCLUSION: This research emphasizes the diverse active ingredients, targets, channels, and pathways of LHQW in the treatment of chronic bronchitis, providing important perspectives for the creation of novel therapeutic drugs and clinical uses.

Integrated spatial metabolomics and network pharmacology to explore the pharmacodynamic substances and mechanism of Radix ginseng-Schisandra chinensis Herb Couple on Alzheimer's disease.

Radix ginseng and Schisandra chinensis have been extensively documented in traditional Chinese medicine (TCM) for their potential efficacy in treating dementia. However, the precise mechanism of their therapeutic effects remains to be fully elucidated. In this study, air flow-assisted desorption electrospray ionization mass spectrometry imaging (AFADESI-MSI) and network pharmacology are used to investigate the pharmacodynamics and mechanism underlying the herbal combination consisting of Radix ginseng-Schisandra chinensis (RS) in a rodent model for Alzheimer's disease (AD). Brain histopathological findings suggested that RS attenuates hippocampal damage in AD mice, making this combination a potential AD treatment. Twenty-eight biomarkers were identified by spatial metabolomics analysis, which are intricately linked to neuroinflammation, neurotransmitter imbalance, energy deficiency, oxidative stress, and aberrant fatty acid metabolism in AD. The total extract of RS (TE) affected 22 of these biomarkers, with the small molecule components of RS (SN) significantly influencing 19 and the large molecule components of RS (PR) impacting 14. Nine small molecule components are likely to dominate the pharmacodynamics of RS. We constructed a target interaction network based on the corresponding bioactivities that revealed relationships amongst 11 key biomarkers, 8 active ingredients and 12 critical targets. This research illustrates the immense potential of spatial metabolomics and network pharmacology in the study of TCM, revealing the targets and mechanisms underlying herbal formulas.

Effect and mechanism of Yiqing decoction on hyperuricemia rats.

This study aimed to experimentally compare the uric acid-lowering effect and renal protection of Yiqing Fang in a rat model of hyperuricemia. Additionally, we used network pharmacology to predict the potential active components, targets, and pathways of Yiqing Fang. Male SD rats were randomly divided into control, model, Yiqing Fang, allopurinol, and probenecid groups. Serum creatinine (Scr), blood urea nitrogen (BUN), serum uric acid (UA), alanine transaminase (ALT), complete blood count, and urinary NAG enzyme levels were measured. Standard pathology and electron microscopy samples were prepared from the left kidney to observe renal pathological changes, renal fibrosis, and collagen III expression levels. In addition, we employed network pharmacology to investigate the molecular mechanisms and pathways of Yiqing Fang. The Yiqing Fang group showed significantly lower levels of Scr, BUN, UA, ALT, urinary NAG enzyme, complete blood count, and liver function tests compared to the model group (P < 0.05). Furthermore, both the Yiqing Fang and allopurinol groups exhibited significant reductions in renal pathological changes compared to the model group, along with decreased expression of collagen III. Network pharmacology analysis identified a total of 27 specific sites related to hyperuricemia. The main active components were predicted to include quercetin, berberine, beta-sitosterol, epimedin C, and dioscin. The primary target sites were predicted to include TNF, IL-6, IL-17, IL-1B, and VEGFA. Yiqing Fang may exert its effects through regulation of drug response, urate metabolism, purine compound absorption, inflammation response, lipopolysaccharide response, cytokine activity, and antioxidant activity. These effects may be mediated through signaling pathways such as IL-17, HIF-1, and AGE-RAGE. Yiqing Fang offers potential as a treatment for hyperuricemia due to its multiple active components, targeting of various sites, and engagement of multiple pathways.

Analysis of Pathological Factors of Long Head of Biceps Tendinopathy Based on Network Pharmacology.

OBJECTIVES: To investigate the therapeutic effect and mechanism of Danggui Buxue Tang in the treatment of biceps longus tendon lesions, and to preliminarily explore the relevant factors affecting this injury. METHODS: Using network pharmacology analysis methods, the potential mechanism of Danggui Buxue Tang in treating key lesions of the long head of the biceps brachii muscle was studied. RESULTS: Model analysis revealed 44 protein-protein interactions associated with long head binding. The distribution of 19 strongly correlated targets is Pharmaper>SEA>Stitch>Swiss. Further discovery revealed 17 immune system and inflammation related KEGG pathways with P values less than 0.01. The TNF and sphingolipid signaling pathways are associated with inflammation, while the MAPK signaling pathway is associated with immunity. Finally, it was found that the FoxO and HIF-1 signaling pathways are directly associated with long head restraint injury in the biceps brachii muscle. CONCLUSION: Danggui Buxue Tang inhibits related pathways, regulates the immune system, reduces inflammation, and alleviates disease progression. Danggui Buxue Tang can be an effective choice for treating combined lesions of the long head of the biceps brachii muscle.

Effect of black cloth ointment on hypertrophic scar formation: An investigation using integrated network pharmacology and animal assay.

BACKGROUND: Hypertrophic scars (HS) are a common disfiguring condition in daily clinical encounters which brings a lot of anxieties and concerns to patients, but the treatment options of HS are limited. Black cloth ointment (BCO), as a cosmetic ointment applicable to facial scars, has shown promising therapeutic effects for facial scarring. However, the molecular mechanisms underlying its therapeutic effects remain unclear. MATERIAL AND METHODS: Network pharmacology was first applied to analyze the major active components of BCO and the related signaling pathways. Subsequently, rabbit ear scar model was successfully established to determine the pharmacological effects of BCO and its active component ß-elemene on HS. Finally, the molecular mechanism of BCO and ß-elemene was analyzed by Western blot. RESULTS: Through the network pharmacology, it showed that ß-elemene was the main active ingredient of BCO, and it could significantly improve the pathological structure of HS and reduce collagen deposition. BCO and ß-elemene could increase the expression of ER stress-related markers and promote the increase of apoptotic proteins in the Western blot experiment and induce the apoptosis of myofibroblasts. CONCLUSIONS: Our findings indicate that the material basis for the scar-improving effects of the BCO is ß-elemene, and cellular apoptosis is the key mechanism through which the BCO and ß-elemene exert their effects.

Exploring the mechanism of dendrobine in treating metabolic associated fatty liver disease based on network pharmacology and experimental validation.

BACKGROUND: This study investigates the therapeutic mechanisms of dendrobine, a primary bioactive compound in Dendrobium nobile, for Metabolic Associated Fatty Liver Disease (MASLD) management. Utilizing network pharmacology combined with experimental validation, the clinical effectiveness of dendrobine in MASLD treatment was assessed and analyzed. RESULTS: The study demonstrates significant improvement in liver function among MASLD patients treated with Dendrobium nobile. Network pharmacology identified key targets such as Peroxisome Proliferator-Activated Receptor Gamma (PPARG), Interleukin 6 (IL6), Tumor Necrosis Factor (TNF), Interleukin 1 Beta (IL1B), and AKT Serine/Threonine Kinase 1 (AKT1), with molecular docking confirming their interactions. Additionally, dendrobine significantly reduced ALT and AST levels in palmitic acid-treated HepG2 cells, indicating hepatoprotective properties and amelioration of oxidative stress through decreased Malondialdehyde (MDA) levels and increased Superoxide Dismutase (SOD) levels. CONCLUSION: Dendrobine mitigates liver damage in MASLD through modulating inflammatory and immune responses and affecting lipid metabolism, potentially by downregulating inflammatory mediators like TNF, IL6, IL1B, and inhibiting AKT1 and Signal Transducer and Activator of Transcription 3 (STAT3). This study provides a theoretical basis for the application of dendrobine in MASLD treatment, highlighting its potential as a therapeutic agent.

Serum metabolomics analysis combined with network pharmacology reveals possible mechanisms of postoperative cognitive dysfunction in the treatment of Mongolian medicine Eerdun Wurile basic formula.

This study analyzed the endogenous metabolites and metabolic pathways in the serum of Sprague-Dawley (SD) rats gavaged with the Eerdun Wurile basic formula (EWB) using metabolomics methods and network pharmacology to explore the possible mechanism of action of the EWB in improving postoperative cognitive dysfunction (POCD). SD rats were divided into the basic formula group, which received the EWB, and the control group, which received equal amounts of distilled water. The blood was collected from the abdominal aorta and analyzed for metabolite profiles using ultra-high-performance liquid chromatography-mass spectrometry (UHPLC-MS). Network pharmacology predicts the targets of the differential metabolites and disease targets; takes the intersection and constructs a "metabolite-disease-target" network; and performs protein-protein interaction, Gene Ontology, and Kyoto Encyclopedia of Genes and Genomes analyses. A total of 56 metabolites were selected for significant differences between the groups, mainly affecting amphetamine addiction, alcoholism, and regulation of lipolysis in adipocytes. A total of 177 potential targets for differential metabolite action in POCD were selected. The PI3K-Akt pathway, the HIF-1 pathway, and the FoxO pathway were in key positions. The studies have shown that EWB could improve POCD through multicomponents, multitargets, and multipathways, providing new possibilities and reference values for the treatment of POCD.

Exploring Potential Targets and Pathways of Toxicity Attenuation Through Serum Pharmacochemistry and Network Pharmacology in the Processing of Aconiti Lateralis Radix Praeparata.

Aconiti Lateralis Radix Praeparata (Fuzi, FZ) is a frequently utilized traditional Chinese medicine (TCM) in clinical settings. However, its toxic and side effects, particularly cardiac injury, are apparent, necessitating processing before use. To investigate the mechanism of toxicity induced by absorbed components and the mitigating effect of processed FZ, we established a comprehensive method combining serum pharmacochemistry and a network pharmacology approach. In total, 31 chemical components were identified in the plasma, with a general decrease in response intensity observed for these components in processed FZ. Subsequently, four components were selected for network pharmacology analysis. This analysis revealed 150 drug action targets and identified 1162 cardiac toxicity targets. Through intersection analysis, 41 key targets related to cardiac toxicity were identified, along with 9 significant Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. The most critical targets identified were AKT1, MTOR, and PARP1. The key biological pathways implicated were adrenergic signaling in cardiomyocytes, proteoglycans in cancer, and the calcium signaling pathway. Significant differences were observed in histological staining and biochemical indicators in the cardiac tissue of rats treated with FZ, indicating that processing could indeed reduce its cardiotoxicity. Indeed, this article presents a valuable strategy for elucidating the toxification mechanism of toxic TCM.

Integrating serum metabolomics analysis and network pharmacology to reveal the potential mechanism of Shengmai Jianghuang San in the treatment of nasopharyngeal carcinoma.

Shengmai Jianghuang San (SMJHS) is a traditional Chinese herbal compound reported to inhibit Nasopharyngeal Carcinoma (NPC) progression and enhance radiosensitivity. However, the specific active ingredients and regulatory mechanisms of SMJHS against NPC, particularly under hypoxic conditions, remain unclear. In this study, Sprague-Dawley (SD) rats were gavaged with Shengmai Jianghuang San (SMJHS), and their blood was collected from the abdominal aorta. UHPLC-Q-Exactive orbitrap MS/MS was used to identify the metabolite profiles of SMJHS drug-containing serum. A molecular network of the active compositions in SMJHS targeting NPC was constructed through network pharmacology and molecular docking. The HIF-1α/VEGF pathway was in key positions. The effects of SMJHS on the proliferation, migration, and radiosensitivity of hypoxic NPC cells were assessed by in vitro experiments. NPC cell lines stably overexpressing HIF-1α were established using a lentivirus to investigate the regulation of HIF-1α/VEGF signaling in hypoxic NPC cells by SMJHS. Through a combination of network pharmacological analysis, cellular biofunctional validation, and molecular biochemical experiments, our study found that SMJHS had an anti-proliferative effect on NPC cells cultured under hypoxic conditions, inhibiting their migration and increasing their radiosensitivity. Additionally, SMJHS suppressed the expression of HIF-1α and VEGFA, exhibiting potential as an effective option for improving NPC treatment.

Quality assessment and Q-markers discovery in Citri Sarcodactylis Fructus by integrating serum pharmacochemistry and network pharmacology.

INTRODUCTION: Citri Sarcodactylis Fructus (CSF), a common fruit and traditional Chinese medicine (TCM), has been hindered in its further development and research owing to the lack of comprehensive and specific quality evaluation standards. OBJECTIVE: This study aimed to establish clear TCM quality standards related to the therapeutic mechanisms of CSF and to provide a basis for subsequent research and development. METHODS: Ultra-high performance liquid chromatography coupled with hybrid quadrupole-orbitrap high-resolution mass spectrometry (UPLC-Q-orbitrap HRMS) technology was used to comprehensively identify CSF components and explore their absorbance levels in rat serum. Network pharmacology research methods were employed to investigate the potential mechanisms of action of the identified components in the treatment of major clinical diseases. Subsequently, a combination of HPLC chromatographic fingerprinting for qualitative analysis and multi-index content determination was used to evaluate the detectability of the identified quality markers (Q-markers). RESULTS: Twenty-six prototype components were tentatively characterized in rat serum. Network pharmacology analysis showed six effective components, namely 7-hydroxycoumarin, isoscopoletin, diosmin, hesperidin, 5,7-dimethoxycoumarin, and bergapten, which played important roles in the treatment of chronic gastritis, functional dyspepsia, peptic ulcer, and depression and were preliminarily identified as Q-markers. The results of content determination in 15 batches of CSF indicated significant differences in the content of medicinal materials from different origins. However, compared with the preliminarily determined Q-markers, all six components could be measured and were determined as Q-markers of CSF. CONCLUSION: The chemical Q-markers obtained in this study could be used for effective quality control of CSF.

Transplanting network pharmacology technology into food science research: A comprehensive review on uncovering food-sourced functional factors and their health benefits.

Network pharmacology is an emerging interdisciplinary research method. The application of network pharmacology to reveal the nutritional effects and mechanisms of active ingredients in food is of great significance in promoting the development of functional food, facilitating personalized nutrition, and exploring the mechanisms of food health effects. This article systematically reviews the application of network pharmacology in the field of food science using a literature review method. The application progress of network pharmacology in food science is discussed, and the mechanisms of functional factors in food on the basis of network pharmacology are explored. Additionally, the limitations and challenges of network pharmacology are discussed, and future directions and application prospects are proposed. Network pharmacology serves as an important tool to reveal the mechanisms of action and health benefits of functional factors in food. It helps to conduct in-depth research on the biological activities of individual ingredients, composite foods, and compounds in food, and assessment of the potential health effects of food components. Moreover, it can help to control and enhance their functionality through relevant information during the production and processing of samples to guarantee food safety. The application of network pharmacology in exploring the mechanisms of functional factors in food is further analyzed and summarized. Combining machine learning, artificial intelligence, clinical experiments, and in vitro validation, the achievement transformation of functional factor in food driven by network pharmacology is of great significance for the future development of network pharmacology research.

Integrated Lipidomics and Network Pharmacology Reveal Mechanism of Memory Impairment Improvement by Yuanzhi San.

Memory impairment (MI) is caused by a variety of causes, endangering human health. Yuanzhi San (YZS) is a common prescription used for the treatment of MI, but its mechanism of action needs further exploration. The purpose of this study was to investigate this mechanism through lipidomics and network pharmacology. Sprague Dawley (SD) rats were divided randomly into the normal, model, and YZS groups. The rats were gavaged with aluminum chloride (200 mg/kg) and intraperitoneally injected with D-galactose (400 mg/kg) every day for 60 days, except for the normal group. From the 30th day, YZS (13.34 g/kg) was gavaged once a day to the rats in the YZS group. Post-YZS treatment, ultra-high-performance liquid chromatography-mass spectrometry (UHPLC/MS) analysis was implemented to conduct a lipidomics study in the hippocampus of rats with memory impairment induced by aluminum chloride and D-galactose. Eight differential metabolites were identified between the normal group and the model group, whereas between the model group and the YZS group, 20 differential metabolites were established. Metabolic pathway analysis was performed on the aforementioned lipid metabolites, all of which were involved in sphingolipid and glycerophospholipid metabolism. Furthermore, serum pharmacochemistry analysis of YZS was carried out at the early stage of our research, which discovered 62 YZS prototype components. The results of the network pharmacology analysis showed that they were related to 1030 genes, and 451 disease genes were related to MI. There were 73 intersections between the YZS and MI targets. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis showed that these targets were closely related to the sphingolipid metabolic, calcium signaling, and other pathways. The integrated approach of lipidomics and network pharmacology was then focused on four major targets, including PHK2, GBA, SPTLC1, and AChE, as well as their essential metabolites (glucosylceramide, N-acylsphingosine, phosphatidylserine, phosphatidylcholine, and phosphatidylcholine) and pathways (sphingolipid, glycerophospholipid, and arachidonic acid metabolism). The significant affinity of the primary target for YZS was confirmed by molecular docking. The obtained results revealed that the combination of lipidomics and network pharmacology could be used to determine the effect of YZS on the MI biological network and metabolic state, and evaluate the drug efficacy of YZS and its related mechanisms of action.

Network Pharmacology-Based Approach for Investigating the Role of Xanthii Fructus in Treatment of Allergic Rhinitis.

Xanthii Fructus (XF) has been used for treatment of allergic rhinitis (AR), but its pharmacological mechanism of action remains unclear. We aimed to explore the potential mechanism of XF in treatment of AR by using a network pharmacology approach combined with in vivo verification experiments in this study. We identified 945 AR-related pathogenic genes, 11 active components in XF and 178 targets of those active components by corresponding databases. Finally, 54 targets of active components from XF in treatment of AR were identified by the Protein-protein interaction (PPI) network, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, among which Tumor Necrosis Factor (TNF), Mitogen-activated Protein Kinase 3 (MAPK3), Prostaglandin G/H Synthase 2 (PTGS2), Epidermal Growth Factor Receptor (EGFR) showed strongest interactions. The molecular docking analysis showed that moupinamide could bind to EGFR at LEU704 and LEU703, and PTGS2 at TRP387; 24-Ethylcholest-4-en-3-one was identified to bind to MAPK3 at THR347. The validation of quantitative real-time reverse transcription PCR (RT-PCR) showed that XF decreased the levels of MAPK3, PTGS2, and EGFR expression in the nasal mucosa from AR mice gavaged with an XF water decoction. Meanwhile, the levels of interleukin (IL)-4, IL-5 and IL-13were also decreased after the treatment of XF by Enzyme-linked immunosorbent assay (ELISA). Our results provide the pharmacological mechanism and possible intervention targets of XF in treatment of AR.

Systematic analysis of the potential off-target activities of osimertinib by computational target fishing.

Osimertinib is a third-generation epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor used to treat non-small cell lung cancer. However, its off-targets are obscure, and systematic analysis of off-target activities remains to be performed. Here, we identified the off-targets of osimertinib using PharmMapper and DRAR-CPI and analyzed the intersected targets using the GeneMANIA and DAVID servers. A drug-target-pathway network was constructed to visualize the associations. The results showed that osimertinib is associated with 31 off-targets, 40 Kyoto Encyclopedia of Genes and Genomes pathways, and 9 diseases. Network analysis revealed that the targets were involved in cancer and other physiological processes. In addition to EGFR, molecular docking analysis showed that seven proteins, namely Janus kinase 3, peroxisome proliferator-activated receptor alpha, renin, mitogen-activated protein kinases, lymphocyte-specific protein tyrosine kinase, cell division protein kinase 2 and proto-oncogene tyrosine-protein kinase Src, could also be potential targets of osimertinib. In conclusion, osimertinib is predicted to target multiple proteins and pathways, resulting in the formation of an action network via which it exerts systematic pharmacological effects.

Network Pharmacology Integrated Molecular Docking Revealed the Mechanism of Jianpi Yiqi Taohua Decoction Against Ulcerative Colitis.

BACKGROUND Jianpi Yiqi Taohua decoction (JYTD) has shown therapeutic effects in ulcerative colitis (UC). However, the pharmacological mechanism of JYTD against UC remains unclear. MATERIAL AND METHODS Compounds and targets of JYTD and UC-related genes were screened from public databases. Integrated analysis was performed to identify therapeutic targets of UC, followed by functional enrichment analysis. Protein-protein interaction interaction (PPI) and pharmacological networks were then established. Molecular docking was used to validate the affinity of compounds and their targets. Further, the efficacy of JYTD was evaluated by meta-analysis. Relevant studies were searched from 5 databases. Outcomes were complete response rate (CRR) and overall response rate (ORR), and pooled results were estimated by risk ratio (RR) with  corresponding 95% confidence intervals (CIs). RESULTS The pharmacological network identified 13 herbal medicines, 28 compounds, 54 targets, and 20 pathways. Stigmasterol, liquiritigenin, and naringenin were potential active compounds, and PRKCA, NFKB1, ESR1, NTRK1, AKT1, PPARG, RXRA, and VDR were hub targets. Pathway analysis revealed that genes were mainly involved in the cellular response to lipids. Molecular docking indicated that AKT1, NFKB1, ESR1, NTRK1, PRKCA, and PPARG exhibited good affinity to 6 key compounds of JYTD. Then, meta-analysis revealed that Tao Hua decoction treatment significantly improved CRR (RR, 1.21; 95% CI, 1.06-1.37; P=0.004) and ORR (RR, 1.16; 95% CI, 1.08-1.24; P<0.001). CONCLUSIONS JYTD was found to have preventive and therapeutic effects on UC through multiple compounds, targets, and pathways. These findings enhanced our understanding of the potential pharmacological mechanisms of JYTD against UC.

Mechanism of action of Tripterygium wilfordii for treatment of idiopathic membranous nephropathy based on network pharmacology.

BACKGROUND: Although thunder god vine (Tripterygium wilfordii) has been widely used for treatment of idiopathic membranous nephropathy (IMN), the pharmacological mechanisms underlying its effects are still unclear. This study investigated potential therapeutic targets and the pharmacological mechanism of T. wilfordii for the treatment of IMN based on network pharmacology. METHODS: Active components of T. wilfordii were obtained from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform. IMN-associated target genes were collected from the GeneCards, DisGeNET, and OMIM databases. VENNY 2.1 was used to identify the overlapping genes between active compounds of T. wilfordii and IMN target genes. The STRING database and Cytoscape 3.7.2 software were used to analyze interactions among overlapping genes. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses of the targets were performed using Rx64 4.0.2 software, colorspace, stringi, DOSE, clusterProfiler, and enrichplot packages. RESULTS: A total of 153 compound-related genes and 1485 IMN-related genes were obtained, and 45 core genes that overlapped between both categories were identified. The protein-protein interaction network and MCODE results indicated that the targets TP53, MAPK8, MAPK14, STAT3, IFNG, ICAM1, IL4, TGFB1, PPARG, and MMP1 play important roles in the treatment of T. wilfordii on IMN. Enrichment analysis showed that the main pathways of targets were the AGE signaling pathway, IL-17 signaling pathway, TNF signaling pathway, and Toll-like receptor signaling pathway. CONCLUSION: This study revealed potential multi-component and multi-target mechanisms of T. wilfordii for the treatment of IMN based on network pharmacological, and provided a scientific basis for further experimental studies.

The mechanism research on the anti-liver fibrosis of emodin based on network pharmacology.

AIMS: This study was designated to illustrate the underlying mechanisms of emodin anti-liver fibrosis via network pharmacology and experiment. METHODS: The TSMCP and Genecards database were applied to screen the relevant targets of emodin or liver fibrosis. The essential target was selected by using Cytoscape to analyze the topological network of potential targets. Furthermore, we constructed a preliminary molecule docking study to explore the binding site by Surflex-Dock suite SYBYL X 2.0. The DAVID database was selected for gene functional annotations and KEGG enrichment analysis. Moreover, we demonstrated the ameliorating effect of emodin on carbon tetrachloride (CCl4 )-induced liver injury in mice. We also verified the network predictions in vitro via various techniques. RESULTS: The collected results showed that 35 targets were related to emodin, and 6,198 targets were associated with liver fibrosis. The Venn analysis revealed that 17 intersection targets were correlated with emodin anti-liver fibrosis. The topological network analysis suggested that the p53 was the remarkable crucial target. Besides, the molecule docking results showed that emodin could directly interact with p53 by binding the active site residues ASN345, GLN331, and TYR347. Finally, KEGG pathway enrichment results indicated that essential genes were mainly enriched in mitogen-activated protein kinase (MAPK) signaling pathways. Moreover, our study confirmed that emodin alleviated CCl4 -induced liver injury in mice, inducing hepatic stellate cells (HSCs) apoptosis via regulating the p53/ERK/p38 axis. CONCLUSIONS: This study partially verified the network pharmacological prediction of emodin inducing HSCs cell apoptosis through the p53/ERK/p38 axis.

Complex Cytochrome P450 Kinetics Due to Multisubstrate Binding and Sequential Metabolism. Part 2. Modeling of Experimental Data.

Three CYP3A4 substrates, midazolam, ticlopidine, and diazepam, display non-Michaelis-Menten kinetics, form multiple primary metabolites, and are sequentially metabolized to secondary metabolites. We generated saturation curves for these compounds and analyzed the resulting datasets using a number of single-substrate and multisubstrate binding models. These models were parameterized using rate equations and numerical solutions of the ordinary differential equations. Multisubstrate binding models provided results superior to single-substrate models, and simultaneous modeling of multiple metabolites provided better results than fitting the individual datasets independently. Although midazolam datasets could be represented using standard two-substrate models, more complex models that include explicit enzyme-product complexes were needed to model the datasets for ticlopidine and diazepam. In vivo clearance predictions improved markedly with the use of in vitro parameters from the complex models versus the Michaelis-Menten equation. The results highlight the need to use sufficiently complex kinetic schemes instead of the Michaelis-Menten equation to generate accurate kinetic parameters. SIGNIFICANCE STATEMENT: The metabolism of midazolam, ticlopidine, and diazepam by CYP3A4 results in multiple metabolites and sequential metabolism. This study evaluates the use of rate equations and numerical methods to characterize the in vitro enzyme kinetics. Use of complex cytochrome P450 kinetic models is necessary to obtain accurate parameter estimates for predicting in vivo disposition.

Network pharmacology of triptolide in cancer cells: implications for transcription factor binding.

Background Triptolide is an active natural product, which inhibits cell proliferation, induces cell apoptosis, suppresses tumor metastasis and improves the effect of other therapeutic treatments in several cancer cell lines by affecting multiple molecules and signaling pathways, such as caspases, heat-shock proteins, DNA damage and NF-ĸB. Purpose We investigated the effect of triptolide towards NF-ĸB and GATA1. Methods We used cell viability assay, compare and cluster analyses of microarray-based mRNA transcriptome-wide expression data, gene promoter binding motif analysis, molecular docking, Ingenuity pathway analysis, NF-ĸB reporter cell assay, and electrophoretic mobility shift assay (EMSA) of GATA1. Results Triptolide inhibited the growth of drug-sensitive (CCRF-CEM, U87.MG) and drug-resistant cell lines (CEM/ADR5000, U87.MGΔEGFR). Hierarchical cluster analysis showed six major clusters in dendrogram. The sensitive and resistant cell lines were statistically significant (p = 0.65 × 10-2) distributed. The binding motifs of NF-κB (Rel) and of GATA1 proteins were significantly enriched in regions of 25 kb upstream promoter of all genes. IPA showed the networks, biological functions, and canonical pathways influencing the activity of triptolide towards tumor cells. Interestingly, upstream analysis for the 40 genes identified by compare analysis revealed ZFPM1 (friend of GATA protein 1) as top transcription regulator. However, we did not observe any effect of triptolide to the binding of GATA1 in vitro. We confirmed that triptolide inhibited NF-κB activity, and it strongly bound to the pharmacophores of IκB kinase ß and NF-κB in silico. Conclusion Triptolide showed promising inhibitory effect toward NF-κB, making it a potential candidate for targeting NF-κB.