Enhancing ß-cell function and identity in type 2 diabetes: The protective role of Coptis deltoidea C. Y. Cheng et Hsiao via glucose metabolism modulation and AMPK signaling activation.

BACKGROUND: Abnormalities in glucose metabolism may be the underlying cause of ß-cell dysfunction and identity impairment resulting from high glucose exposure. In China, Coptis deltoidea C. Y. Cheng et Hsiao (YL) has demonstrated remarkable hypoglycemic effects. HYPOTHESIS/PURPOSE: To investigate the hypoglycemic effect of YL and determine the mechanism of YL in treating diabetes. METHODS: A type 2 diabetes mouse model was used to investigate the pharmacodynamics of YL. YL was administrated once daily for 8 weeks. The hypoglycemic effect of YL was assessed by fasting blood glucose, an oral glucose tolerance test, insulin levels, and other indexes. The underlying mechanism of YL was examined by targeting glucose metabolomics, western blotting, and qRT-PCR. Subsequently, the binding capacity between predicted AMP-activated protein kinase (AMPK) and important components of YL (Cop, Ber, and Epi) were validated by molecular docking and surface plasmon resonance. Then, in AMPK knockdown MIN6 cells, the mechanisms of Cop, Ber, and Epi were inversely confirmed through evaluations encompassing glucose-stimulated insulin secretion, markers indicative of ß-cell identity, and the examination of glycolytic genes and products. RESULTS: YL (0.9 g/kg) treatment exerted notable hypoglycemic effects and protected the structural integrity and identity of pancreatic ß-cells. Metabolomic analysis revealed that YL inhibited the hyperactivated glycolysis pathway in diabetic mice, thereby regulating the products of the tricarboxylic acid cycle. KEGG enrichment revealed the intimate relationship of this process with the AMPK signaling pathway. Cop, Ber, and Epi in YL displayed high binding affinities for AMPK protein. These compounds played a pivotal role in preserving the identity of pancreatic ß-cells and amplifying insulin secretion. The mechanism underlying this process involved inhibition of glucose uptake, lowering intracellular lactate levels, and elevating acetyl coenzyme A and ATP levels through AMPK signaling. The use of a glycolytic inhibitor corroborated that attenuation of glycolysis restored ß-cell identity and function. CONCLUSION: YL demonstrates significant hypoglycemic efficacy. We elucidated the potential mechanisms underlying the protective effects of YL and its active constituents on ß-cell function and identity by observing glucose metabolism processes in pancreatic tissue and cells. In this intricate process, AMPK plays a pivotal regulatory role.

Jinkui Shenqi pills ameliorate diabetes by regulating hypothalamic insulin resistance and POMC/AgRP expression and activity.

BACKGROUND: Research on the imbalance of proopiomelanocortin (POMC)/agouti-related protein (AgRP) neurons in the hypothalamus holds potential insights into the pathophysiology of diabetes. Jinkui Shenqi pills (JSP), a prevalent traditional Chinese medicine, regulate hypothalamic function and treat diabetes. PURPOSE: To investigate the hypoglycemic effect of JSP and explore the probable mechanism in treating diabetes. METHODS: A type 2 diabetes mouse model was used to investigate the pharmacodynamics of JSP. The glucose-lowering efficacy of JSP was assessed through various metrics including body weight, food consumption, fasting blood glucose (FBG), serum insulin levels, and an oral glucose tolerance test (OGTT). To elucidate the modulatory effects of JSP on hypothalamic mechanisms, we quantified the expression and activity of POMC and AgRP and assessed the insulin-mediated phosphoinositide 3-kinase (PI3K)/protein kinase A (AKT)/forkhead box O1 (FOXO1) pathway in diabetic mice via western blotting and immunohistochemistry. Additionally, primary hypothalamic neurons were exposed to high glucose and palmitic acid levels to induce insulin resistance, and the influence of JSP on POMC/AgRP protein expression and activation was evaluated by PI3K protein inhibition using western blotting and immunofluorescence. RESULTS: Medium- and high-dose JSP treatment effectively inhibited appetite, resulting in a steady declining trend in body weight, FBG, and OGTT results in diabetic mice (p < 0.05). These JSP groups also had significantly increased insulin levels (p < 0.05). Importantly, the medium-dose group exhibited notable protection of hypothalamic neuronal and synaptic structures, leading to augmentation of dendritic length and branching (p < 0.05). Furthermore, low-, medium-, and high-dose JSP groups exhibited increased phosphorylated (p) INSR, PI3K, pPI3K, AKT, and pAKT expression, as well as decreased FOXO1 and increased pFOXO1 expression, indicating improved hypothalamic insulin resistance in diabetic mice (p < 0.05). Treatment with 10% JSP-enriched serum produced a marked elevation of both expression and activation of POMC (p < 0.05), with a concurrent reduction in AgRP expression and activation within primary hypothalamic neurons (p < 0.05). Intriguingly, these effects could be attributed to the regulatory dynamics of PI3K activity. CONCLUSION: Our findings suggest that JSP can ameliorate diabetes by regulating POMC/AgRP expression and activity. The insulin-mediated PI3K/AKT/FOXO1 pathway plays an important regulatory role in this intricate process.

Screening of key functional components of Taohong Siwu Decoction on ischemic stroke treatment based on multiobjective optimization approach and experimental validation.

BACKGROUND: Taohong Siwu Decoction (THSWD) is a widely used traditional Chinese medicine (TCM) prescription in the treatment of ischemic stroke. There are thousands of chemical components in THSWD. However, the key functional components are still poorly understood. This study aimed to construct a mathematical model for screening of active ingredients in TCM prescriptions and apply it to THSWD on ischemic stroke. METHODS: Botanical drugs and compounds in THSWD were acquired from multiple public TCM databases. All compounds were initially screened by ADMET properties. SEA, HitPick, and Swiss Target Prediction were used for target prediction of the filtered compounds. Ischemic stroke pathological genes were acquired from the DisGeNet database. The compound-target-pathogenic gene (C-T-P) network of THSWD was constructed and then optimized using the multiobjective optimization (MOO) algorithm. We calculated the cumulative target coverage score of each compound and screened the top compounds with 90% coverage. Finally, verification of the neuroprotective effect of these compounds was performed with the oxygen-glucose deprivation and reoxygenation (OGD/R) model. RESULTS: The optimized C-T-P network contains 167 compounds, 1,467 predicted targets, and 1,758 stroke pathological genes. And the MOO model showed better optimization performance than the degree model, closeness model, and betweenness model. Then, we calculated the cumulative target coverage score of the above compounds, and the cumulative effect of 39 compounds on pathogenic genes reached 90% of all compounds. Furthermore, the experimental results showed that decanoic acid, butylphthalide, chrysophanol, and sinapic acid significantly increased cell viability. Finally, the docking results showed the binding modes of these four compounds and their target proteins. CONCLUSION: This study provides a methodological reference for the screening of potential therapeutic compounds of TCM. In addition, decanoic acid and sinapic acid screened from THSWD were found having potential neuroprotective effects first and verified with cell experiments, however, further in vitro and in vivo studies are needed to explore the precise mechanisms involved.

Decoding the key compounds and mechanism of Shashen Maidong decoction in the treatment of lung cancer.

BACKGROUND: Lung cancer is a malignant tumour with the fastest increase in morbidity and mortality around the world. The clinical treatments available have significant side effects, thus it is desirable to identify alternative modalities to treat lung cancer. Shashen Maidong decoction (SMD) is a commonly used traditional Chinese medicine (TCM) formula for treating lung cancer in the clinic. While the key functional components (KFC) and the underlying mechanisms of SMD treating lung cancer are still unclear. METHODS: We propose a new integrated pharmacology model, which combines a novel node-importance calculation method and the contribution decision rate (CDR) model, to identify the KFC of SMD and to deduce their mechanisms in the treatment of lung cancer. RESULTS: The enriched effective Gene Ontology (GO) terms selected from our proposed node importance detection method could cover 97.66% of enriched GO terms of reference targets. After calculating CDR of active components in key functional network, the first 82 components covered 90.25% of the network information, which were defined as KFC. 82 KFC were subjected to functional analysis and experimental validation. 5-40 µM protocatechuic acid, 100-400 µM paeonol or caffeic acid exerted significant inhibitory activity on the proliferation of A549 cells. The results show that KFC play an important therapeutic role in the treatment of lung cancer by targeting Ras, AKT, IKK, Raf1, MEK, and NF-κB in the PI3K-Akt, MAPK, SCLC, and NSCLC signaling pathways active in lung cancer. CONCLUSIONS: This study provides a methodological reference for the optimization and secondary development of TCM formulas. The strategy proposed in this study can be used to identify key compounds in the complex network and provides an operable test range for subsequent experimental verification, which greatly reduces the experimental workload.

A Metabolic Driven Bio-Responsive Hydrogel Loading Psoralen for Therapy of Rheumatoid Arthritis.

Overexpressed matrix metalloproteinases, hypoxia microenvironment, and metabolic abnormality are important pathological signs of rheumatoid arthritis (RA). Designing a delivery carrier according to the pathological characteristics of RA that can control drug release in response to disease severity may be a promising treatment strategy. Psoralen is the main active ingredient isolated from Psoralea corylifolia L. and possesses excellent anti-inflammatory activities as well as improving bone homeostasis. However, the specific underlying mechanisms, particularly the possible relationships between the anti-RA effects of psoralen and related metabolic network, remain largely unexplored. Furthermore, psoralen shows systemic side effects and has unsatisfactory solubility. Therefore, it is desirable to develop a novel delivery system to maximize psoralen's therapeutic effect. In this study, a self-assembled degradable hydrogel platform is developed that delivers psoralen and calcium peroxide to arthritic joints and controls the release of psoralen and oxygen according to inflammatory stimulation, to regulate homeostasis and the metabolic disorder of the anoxic arthritic microenvironment. Therefore, the hydrogel drug delivery system based on the responsiveness of the inflammatory microenvironment and regulation of metabolism provides a new therapeutic strategy for RA treatment.

Decoding the underlying mechanisms of Di-Tan-Decoction in treating intracerebral hemorrhage based on network pharmacology.

BACKGROUND: Chinese medicine usually acts as "multi-ingredients, multi-targets and multi-pathways" on complex diseases, and these action modes reflect the coordination and integrity of the treatment process with traditional Chinese medicine (TCM). System pharmacology is developed based on the cross-disciplines of directional pharmacology, system biology, and mathematics, has the characteristics of integrity and synergy in the treatment process of TCM. Therefore, it is suitable for analyzing the key ingredients and mechanisms of TCM in treating complex diseases. Intracerebral Hemorrhage (ICH) is one of the leading causes of death in China, with the characteristics of high mortality and disability rate. Bring a significant burden on people and society. An increasing number of studies have shown that Chinese medicine prescriptions have good advantages in the treatment of ICH, and Ditan Decoction (DTT) is one of the commonly used prescriptions in the treatment of ICH. Modern pharmacological studies have shown that DTT may play a therapeutic role in treating ICH by inhibiting brain inflammation, abnormal oxidative stress reaction and reducing neurological damage, but the specific key ingredients and mechanism are still unclear. METHODS: To solve this problem, we established PPI network based on the latest pathogenic gene data of ICH, and CT network based on ingredient and target data of DTT. Subsequently, we established optimization space based on PPI network and CT network, and constructed a new model for node importance calculation, and proposed a calculation method for PES score, thus calculating the functional core ingredients group (FCIG). These core functional groups may represent DTT therapy for ICH. RESULTS: Based on the strategy, 44 ingredients were predicted as FCIG, results showed that 80.44% of the FCIG targets enriched pathways were coincided with the enriched pathways of pathogenic genes. Both the literature and molecular docking results confirm the therapeutic effect of FCIG on ICH via targeting MAPK signaling pathway and PI3K-Akt signaling pathway. CONCLUSIONS: The FCIG obtained by our network pharmacology method can represent the effect of DTT in treating ICH. These results confirmed that our strategy of active ingredient group optimization and the mechanism inference could provide methodological reference for optimization and secondary development of TCM.

Acetyl-CoA carboxylase 1 depletion suppresses de novo fatty acid synthesis and mitochondrial ß-oxidation in castration-resistant prostate cancer cells.

Cancer cells, including those of prostate cancer (PCa), often hijack intrinsic cell signaling to reprogram their metabolism. Part of this reprogramming includes the activation of de novo synthesis of fatty acids that not only serve as building blocks for membrane synthesis but also as energy sources for cell proliferation. However, how de novo fatty acid synthesis contributes to PCa progression is still poorly understood. Herein, by mining public datasets, we discovered that the expression of acetyl-CoA carboxylase alpha (ACACA), which encodes acetyl-CoA carboxylase 1 (ACC1), was highly expressed in human PCa. In addition, patients with high ACACA expression had a short disease-free survival time. We also reported that depletion of ACACA reduced de novo fatty acid synthesis and PI3K/AKT signaling in the human castration-resistant PCa (CRPC) cell lines DU145 and PC3. Furthermore, depletion of ACACA downregulates mitochondrial beta-oxidation, resulting in mitochondrial dysfunction, a reduction in ATP production, an imbalanced NADP+/NADPhydrogen(H) ratio, increased reactive oxygen species, and therefore apoptosis. Reduced exogenous fatty acids by depleting lipid or lowering serum supplementation exacerbated both shRNA depletion and pharmacological inhibition of ACACA-induced apoptosis in vitro. Collectively, our results suggest that inhibition of ectopic ACACA, together with suppression of exogenous fatty acid uptake, can be a novel strategy for treating currently incurable CRPC.

Decoding the Key Functional Combined Components Group and Uncovering the Molecular Mechanism of Longdan Xiegan Decoction in Treating Uveitis.

Objective: Longdan Xiegan Decoction (LXD) is a famous herbal formula in China. It has been proved that LXD has been shown to have a significant inhibitory effect on suppresses the inflammatory cells associated with uveitis. However, the key functional combination of component groups and their possible mechanisms remain unclear. Methods: The community detecting model of the network, the functional response space, and reverse prediction model were utilized to decode the key components group (KCG) and possible mechanism of LXD in treating uveitis. Finally, MTT assay, NO assay and ELISA assay were applied to verify the effectiveness of KCG and the accuracy of our strategy. Results: In the components-targets-pathogenic genes-disease (CTP) network, a combination of Huffman coding and random walk algorithm was used and eight foundational acting communities (FACs) were discovered with important functional significance. Verification has shown that FACs can represent the corresponding C-T network for treating uveitis. A novel node importance calculation method was designed to construct the functional response space and pick out 349 effective proteins. A total of 54 components were screened and defined as KCG. The pathway enrichment results showed that KCG and their targets enriched signal pathways of IL-17, Toll-like receptor, and T cell receptor played an important role in the pathogenesis of uveitis. Furthermore, experimental verification results showed that important KCG quercetin and sitosterol markedly inhibited the production of nitric oxide and significantly regulated the level of TNF-α and IFN-γ in Lipopolysaccharide-induced RAW264.7 cells. Discussion: In this research, we decoded the potential mechanism of the multi-components-genes-pathways of LXD's pharmacological action mode against uveitis based on an integrated pharmacology approach. The results provided a new perspective for the future studies of the anti-uveitis mechanism of traditional Chinese medicine.

Mathematical algorithm-based identification of the functional components and mechanisms in depression treatment: An example of Danggui-Shaoyao-San.

Depression, a complex epidemiological mental disorder, affects around 350 million people worldwide. Despite the availability of antidepressants based on monoamine hypothesis of depression, most patients suffer side effects from these drugs, including psychomotor impairment and dependence liability. Traditional Chinese medicine (TCM) is receiving more and more attention due to the advantages of high therapeutic performance and few side effects in depression treatment. However, complex multicomponents and multi-targets in TCM hinder our ability to identify the functional components and molecular mechanisms of its efficacy. In this study, we designed a novel strategy to capture the functional components and mechanisms of TCM based on a mathematical algorithm. To establish proof of principle, the TCM formula Danggui-Shaoyao-San (DSS), which possesses remarkable antidepressant effect but its functional components and mechanisms are unclear, is used as an example. According to the network motif detection algorithm, key core function motifs (CIM) of DSS in treating depression were captured, followed by a functional analysis and verification. The results demonstrated that 198 pathways were enriched by the target genes of the CIM, and 179 coincided with the enriched pathways of pathogenic genes, accounting for 90.40% of the gene enrichment pathway of the C-T network. Then the functional components group (FCG) comprising 40 components was traced from CIM based on the target coverage accumulation algorithm, after which the pathways enriched by the target genes of FCG were selected to elucidate the potential mechanisms of DSS in treating depression. Finally, the pivotal components in FCG of DSS and the related pathways were selected for experimental validation in vitro and in vivo. Our results indicated good accuracy of the proposed mathematical algorithm in sifting the FCG from the TCM formula, which provided a methodological reference for discovering functional components and interpreting molecular mechanisms of the TCM formula in treating complex diseases.

Possible mechanism and Atorvastatin-based treatment in cupping therapy-related subdural hematoma: A case report and literature review.

Subdural hematoma (SDH) is one of the most lethal types of traumatic brain injury. SDH caused by Intracranial Pressure Reduction (ICPR) is rare, and the mechanism remains unclear. Here, we report three cases of SDH that occurred after substandard cupping therapy and are conjected to be associated with ICPR. All of them had undergone cupping treatments. On the last cupping procedure, they experienced a severe headache after the cup placed on the occipital-neck junction (ONJ) was suddenly removed and were diagnosed with SDH the next day. In standard cupping therapy, the cups are not usually placed on the ONJ. We speculate that removing these cups on the soft tissue over the cisterna magna repeatedly created localized negative pressure, caused temporary but repeated ICPR, and eventually led to SDH development. The Monro-Kellie Doctrine can explain the mechanism behind this - it states that the intracranial pressure is regulated by a fixed system, with any change in one component causing a compensatory change in the other. The repeated ICPR promoted brain displacement, tearing of the bridging veins, and development of SDH. The literature was reviewed to illustrate the common etiologies and therapies of secondary ICPR-associated SDH. Despite the popularity of cupping therapy, its side effects are rarely mentioned. This case is reported to remind professional technicians to fully assess a patient's condition before cupping therapy and ensure that the cups are not placed at the ONJ.

Computational Metabolomics Reveals the Potential Mechanism of Matrine Mediated Metabolic Network Against Hepatocellular Carcinoma.

Hepatocellular carcinoma (HCC) is a complex issue in cancer treatment in the world at present. Matrine is the main active ingredient isolated from Sophora flavescens air and possesses excellent antitumor effects in HCC. However, the specific underlying mechanisms, especially the possible relationships between the anti-HCC effect of matrine and the related metabolic network of HCC, are not yet clear and need further clarification. In this study, an integrative metabolomic-based bioinformatics algorithm was designed to explore the underlying mechanism of matrine on HCC by regulating the metabolic network. Cell clone formation, invasion, and adhesion assay were utilized in HCC cells to evaluate the anti-HCC effect of matrine. A cell metabolomics approach based on LC-MS was used to obtain the differential metabolites and metabolic pathways regulated by matrine. The maximum activity contribution score model was developed and applied to calculate high contribution target genes of matrine, which could regulate a metabolic network based on the coexpression matrix of matrine-regulated metabolic genes and targets. Matrine significantly repressed the clone formation and invasion, enhanced cell-cell adhesion, and hampered cell matrix adhesion in SMMC-7721 cells. Metabolomics results suggested that matrine markedly regulated the abnormal metabolic network of HCC by regulating the level of choline, creatine, valine, spermidine, 4-oxoproline, D-(+)-maltose, L-(-)-methionine, L-phenylalanine, L-pyroglutamic acid, and pyridoxine, which are involved in D-glutamine and D-glutamate metabolism, glycine, serine and threonine metabolism, arginine and proline metabolism, etc. Our proposed metabolomic-based bioinformatics algorithm showed that the regulating metabolic networks of matrine exhibit anti-HCC effects through acting on MMP7, ABCC1, PTGS1, etc. At last, MMP7 and its related target ß-catenin were validated. Together, the metabolomic-based bioinformatics algorithm reveals the effects of the regulating metabolic networks of matrine in treating HCC relying on the unique characteristics of the multitargets and multipathways of traditional Chinese medicine.

Detecting Key Functional Components Group and Speculating the Potential Mechanism of Xiao-Xu-Ming Decoction in Treating Stroke.

Stroke is a cerebrovascular event with cerebral blood flow interruption which is caused by occlusion or bursting of cerebral vessels. At present, the main methods in treating stroke are surgical treatment, statins, and recombinant tissue-type plasminogen activator (rt-PA). Relatively, traditional Chinese medicine (TCM) has widely been used at clinical level in China and some countries in Asia. Xiao-Xu-Ming decoction (XXMD) is a classical and widely used prescription in treating stroke in China. However, the material basis of effect and the action principle of XXMD are still not clear. To solve this issue, we designed a new system pharmacology strategy that combined targets of XXMD and the pathogenetic genes of stroke to construct a functional response space (FRS). The effective proteins from this space were determined by using a novel node importance calculation method, and then the key functional components group (KFCG) that could mediate the effective proteins was selected based on the dynamic programming strategy. The results showed that enriched pathways of effective proteins selected from FRS could cover 99.10% of enriched pathways of reference targets, which were defined by overlapping of component targets and pathogenetic genes. Targets of optimized KFCG with 56 components can be enriched into 166 pathways that covered 80.43% of 138 pathways of 1,012 pathogenetic genes. A component potential effect score (PES) calculation model was constructed to calculate the comprehensive effective score of components in the components-targets-pathways (C-T-P) network of KFCGs, and showed that ferulic acid, zingerone, and vanillic acid had the highest PESs. Prediction and docking simulations show that these components can affect stroke synergistically through genes such as MEK, NFκB, and PI3K in PI3K-Akt, cAMP, and MAPK cascade signals. Finally, ferulic acid, zingerone, and vanillic acid were tested to be protective for PC12 cells and HT22 cells in increasing cell viabilities after oxygen and glucose deprivation (OGD). Our proposed strategy could improve the accuracy on decoding KFCGs of XXMD and provide a methodologic reference for the optimization, mechanism analysis, and secondary development of the formula in TCM.

White tea alleviates non-alcoholic fatty liver disease by regulating energy expenditure and lipid metabolism.

Non-alcoholic fatty liver disease (NAFLD) is one of the leading causes of liver disease, which lacks effective treatments. Abnormal lipid metabolism and inflammation are the most prominent pathological manifestations of NAFLD. Recently, it has been reported that white tea extract (WTE) can regulate lipid metabolism in human adipocytes and liver cancer cells in vitro. However, its beneficial effects on NAFLD and the underlying mechanisms remain largely unknown. Here, we showed that WTE alleviated obesity, lipid accumulation, hepatic steatosis, and liver injury in a mouse model of NAFLD. Mechanistically, we demonstrated that WTE exerted the anti-NAFLD effect by decreasing the expression of genes involved in lipid transport and synthesis processes while activating genes associated with energy expenditure. In addition, a comparison of the transcriptional responses of WTE with that of green tea extract (GTE) revealed that WTE can not only regulate lipid metabolism and stress response like GTE but also regulate antioxidant and inflammatory pathways more effectively. Taken together, our findings demonstrate that WTE inhibits the progression of NAFLD in a mouse model and indicate that WTE can be a potential dietary intervention for NAFLD.

Uncovering the potential mechanism of Xue Fu Zhu Yu Decoction in the treatment of intracerebral hemorrhage.

BACKGROUND: Chinese herbal medicine (CHM) is characterized by "multi- compounds, multi-targets and multi-pathway", which has advanced benefits for preventing and treating complex diseases, but there still exists unsolved issues, mainly include unclear material basis and underlying mechanism of prescription. Integrated pharmacology is a hot cross research area based on system biology, mathematics and poly-pharmacology. It can systematically and comprehensively investigate the therapeutic reaction of compounds or drugs on pathogenic genes network, and is especially suitable for the study of complex CHM systems. Intracerebral Hemorrhage (ICH) is one of the main causes of death among Chinese residents, which is characterized with high mortality and high disability rate. In recent years, the treatment of ICH by CHM has been deeply researched. Xue Fu Zhu Yu Decoction (XFZYD), one of the commonly used prescriptions in treating ICH at clinic level, has not been clear about its mechanism. METHODS: Here, we established a strategy, which based on compounds-targets, pathogenetic genes, network analysis and node importance calculation. Using this strategy, the core compounds group (CCG) of XFZYD was predicted and validated by in vitro experiments. The molecular mechanism of XFZYD in treating ICH was deduced based on CCG and their targets. RESULTS: The results show that the CCG with 43 compounds predicted by this model is highly consistent with the corresponding Compound-Target (C-T) network in terms of gene coverage, enriched pathway coverage and accumulated contribution of key nodes at 89.49%, 88.72% and 90.11%, respectively, which confirmed the reliability and accuracy of the effective compound group optimization and mechanism speculation strategy proposed by us. CONCLUSIONS: Our strategy of optimizing the effective compound groups and inferring the mechanism provides a strategic reference for explaining the optimization and inferring the molecular mechanism of prescriptions in treating complex diseases of CHM.

Elucidating the Synergistic Effect of Multiple Chinese Herbal Prescriptions in the Treatment of Post-stroke Neurological Damage.

Background: Traditional Chinese medicine (TCM) has been widely used in the treatment of human diseases. However, the synergistic effects of multiple TCM prescriptions in the treatment of stroke have not been thoroughly studied. Objective of the study: This study aimed to reveal the mechanisms underlying the synergistic effects of these TCM prescriptions in stroke treatment and identify the active compounds. Methods: Herbs and compounds in the Di-Tan Decoction (DTD), Xue-Fu Zhu-Yu Decoction (XFZYD), and Xiao-Xu-Ming Decoction (XXMD) were acquired from the TCMSP database. SEA, HitPick, and TargetNet web servers were used for target prediction. The compound-target (C-T) networks of three prescriptions were constructed and then filtered using the collaborative filtering algorithm. We combined KEGG enrichment analysis, molecular docking, and network analysis approaches to identify active compounds, followed by verification of these compounds with an oxygen-glucose deprivation and reoxygenation (OGD/R) model. Results: The filtered DTD network contained 39 compounds and 534 targets, the filtered XFZYD network contained 40 compounds and 508 targets, and the filtered XXMD network contained 55 compounds and 599 targets. The filtered C-T networks retained approximately 80% of the biological functions of the original networks. Based on the enriched pathways, molecular docking, and network analysis results, we constructed a complex network containing 3 prescriptions, 14 botanical drugs, 26 compounds, 13 targets, and 5 pathways. By calculating the synergy score, we identified the top 5 candidate compounds. The experimental results showed that quercetin, baicalin, and ginsenoside Rg1 independently and synergistically increased cell viability. Conclusion: By integrating pharmacological and chemoinformatic approaches, our study provides a new method for identifying the effective synergistic compounds of TCM prescriptions. The filtered compounds and their synergistic effects on stroke require further research.

Detecting Critical Functional Ingredients Group and Mechanism of Xuebijing Injection in Treating Sepsis.

Sepsis is a systemic inflammatory reaction caused by various infectious or noninfectious factors, which can lead to shock, multiple organ dysfunction syndrome, and death. It is one of the common complications and a main cause of death in critically ill patients. At present, the treatments of sepsis are mainly focused on the controlling of inflammatory response and reduction of various organ function damage, including anti-infection, hormones, mechanical ventilation, nutritional support, and traditional Chinese medicine (TCM). Among them, Xuebijing injection (XBJI) is an important derivative of TCM, which is widely used in clinical research. However, the molecular mechanism of XBJI on sepsis is still not clear. The mechanism of treatment of "bacteria, poison and inflammation" and the effects of multi-ingredient, multi-target, and multi-pathway have still not been clarified. For solving this issue, we designed a new systems pharmacology strategy which combines target genes of XBJI and the pathogenetic genes of sepsis to construct functional response space (FRS). The key response proteins in the FRS were determined by using a novel node importance calculation method and were condensed by a dynamic programming strategy to conduct the critical functional ingredients group (CFIG). The results showed that enriched pathways of key response proteins selected from FRS could cover 95.83% of the enriched pathways of reference targets, which were defined as the intersections of ingredient targets and pathogenetic genes. The targets of the optimized CFIG with 60 ingredients could be enriched into 182 pathways which covered 81.58% of 152 pathways of 1,606 pathogenetic genes. The prediction of CFIG targets showed that the CFIG of XBJI could affect sepsis synergistically through genes such as TAK1, TNF-α, IL-1ß, and MEK1 in the pathways of MAPK, NF-κB, PI3K-AKT, Toll-like receptor, and tumor necrosis factor signaling. Finally, the effects of apigenin, baicalein, and luteolin were evaluated by in vitro experiments and were proved to be effective in reducing the production of intracellular reactive oxygen species in lipopolysaccharide-stimulated RAW264.7 cells, significantly. These results indicate that the novel integrative model can promote reliability and accuracy on depicting the CFIGs in XBJI and figure out a methodological coordinate for simplicity, mechanism analysis, and secondary development of formulas in TCM.

A System Pharmacology Model for Decoding the Synergistic Mechanisms of Compound Kushen Injection in Treating Breast Cancer.

Breast cancer (BC) is one of the most common malignant tumors among women worldwide and can be treated using various methods; however, side effects of these treatments cannot be ignored. Increasing evidence indicates that compound kushen injection (CKI) can be used to treat BC. However, traditional Chinese medicine (TCM) is characterized by "multi-components" and "multi-targets", which make it challenging to clarify the potential therapeutic mechanisms of CKI on BC. Herein, we designed a novel system pharmacology strategy using differentially expressed gene analysis, pharmacokinetics synthesis screening, target identification, network analysis, and docking validation to construct the synergy contribution degree (SCD) and therapeutic response index (TRI) model to capture the critical components responding to synergistic mechanisms of CKI in BC. Through our designed mathematical models, we defined 24 components as a high contribution group of synergistic components (HCGSC) from 113 potentially active components of CKI based on ADME parameters. Pathway enrichment analysis of HCGSC targets indicated that Rhizoma Heterosmilacis and Radix Sophorae Flavescentis could synergistically target the PI3K-Akt signaling pathway and the cAMP signaling pathway to treat BC. Additionally, TRI analysis showed that the average affinity of HCGSC and targets involved in the key pathways reached -6.47 kcal/mmol, while in vitro experiments proved that two of the three high TRI-scored components in the HCGSC showed significant inhibitory effects on breast cancer cell proliferation and migration. These results demonstrate the accuracy and reliability of the proposed strategy.

Computational Network Pharmacology-Based Strategy to Capture Key Functional Components and Decode the Mechanism of Chai-Hu-Shu-Gan-San in Treating Depression.

Traditional Chinese medicine (TCM) usually plays therapeutic roles on complex diseases in the form of formulas. However, the multicomponent and multitarget characteristics of formulas bring great challenges to the mechanism analysis and secondary development of TCM in treating complex diseases. Modern bioinformatics provides a new opportunity for the optimization of TCM formulas. In this report, a new bioinformatics analysis of a computational network pharmacology model was designed, which takes Chai-Hu-Shu-Gan-San (CHSGS) treatment of depression as the case. In this model, effective intervention space was constructed to depict the core network of the intervention effect transferred from component targets to pathogenic genes based on a novel node importance calculation method. The intervention-response proteins were selected from the effective intervention space, and the core group of functional components (CGFC) was selected based on these intervention-response proteins. Results show that the enriched pathways and GO terms of intervention-response proteins in effective intervention space could cover 95.3 and 95.7% of the common pathways and GO terms that respond to the major functional therapeutic effects. Additionally, 71 components from 1,012 components were predicted as CGFC, the targets of CGFC enriched in 174 pathways which cover the 86.19% enriched pathways of pathogenic genes. Based on the CGFC, two major mechanism chains were inferred and validated. Finally, the core components in CGFC were evaluated by in vitro experiments. These results indicate that the proposed model with good accuracy in screening the CGFC and inferring potential mechanisms in the formula of TCM, which provides reference for the optimization and mechanism analysis of the formula in TCM.

Analysis of Molecular Mechanism of Erxian Decoction in Treating Osteoporosis Based on Formula Optimization Model.

Osteoporosis (OP) is a highly prevalent orthopedic condition in postmenopausal women and the elderly. Currently, OP treatments mainly include bisphosphonates, receptor activator of nuclear factor kappa-B ligand (RANKL) antibody therapy, selective estrogen receptor modulators, teriparatide (PTH1-34), and menopausal hormone therapy. However, increasing evidence has indicated these treatments may exert serious side effects. In recent years, Traditional Chinese Medicine (TCM) has become popular for treating orthopedic disorders. Erxian Decoction (EXD) is widely used for the clinical treatment of OP, but its underlying molecular mechanisms are unclear thanks to its multiple components and multiple target features. In this research, we designed a network pharmacology method, which used a novel node importance calculation model to identify critical response networks (CRNs) and effective proteins. Based on these proteins, a target coverage contribution (TCC) model was designed to infer a core active component group (CACG). This approach decoded the mechanisms underpinning EXD's role in OP therapy. Our data indicated that the drug response network mediated by the CACG effectively retained information of the component-target (C-T) network of pathogenic genes. Functional pathway enrichment analysis showed that EXD exerted therapeutic effects toward OP by targeting PI3K-Akt signaling (hsa04151), calcium signaling (hsa04020), apoptosis (hsa04210), estrogen signaling (hsa04915), and osteoclast differentiation (hsa04380) via JNK, AKT, and ERK. Our method furnishes a feasible methodological strategy for formula optimization and mechanism analysis and also supplies a reference scheme for the secondary development of the TCM formula.

A metabolic data-driven systems pharmacology strategy for decoding and validating the mechanism of Compound Kushen Injection against HCC.

ETHNOPHARMACOLOGICAL RELEVANCE: Compound Kushen Injection (CKI) is a widely used TCM formula for treatment of carcinomatous pain and tumors of digestive system including hepatocellular carcinoma (HCC). However, the potential mechanisms of CKI for treatment of HCC have not been systematically and deeply studied. AIM OF STUDY: A metabolic data-driven systems pharmacology approach was utilized to investigate the potential mechanisms of CKI for treatment of HCC. MATERIALS AND METHODS: Based on phenotypic data generated by metabolomics and genotypic data of drug targets, a propagation model based on Dijkstra program was proposed to decode the effective network of key genotype-phenotype of CKI in treating HCC. The pivotal pathway was predicted by target propagation mode of our proposed model, and was validated in SMMC-7721 cells and diethylnitrosamine-induced rats. RESULTS: Metabolomics results indicated that 12 differential metabolites, and 5 metabolic pathways might be involved in the anti-HCC effect of CKI. A total of 86 metabolic related genes that affected by CKI were obtained. The results calculated by propagation model showed that 6475 shortest distance chains might be involved in the anti-HCC effect of CKI. According to the results of propagation mode, EGFR was identified as the core target of CKI for the anti-HCC effect. Finally, EGFR and its related pathway EGFR-STAT3 signaling pathway were validated in vivo and in vitro. CONCLUSION: The proposed method provides a methodological reference for explaining the underlying mechanism of TCM in treating HCC.