Network target for screening synergistic drug combinations with application to traditional Chinese medicine

Network-based identification and mechanism exploration of active ingredients against Alzheimer's disease via targeting endoplasmic reticulum stress from traditional chinese medicine

Alzheimer's disease is a neurodegenerative disease that leads to dementia and poses a serious threat to the health of the elderly. Traditional Chinese medicine (TCM) presents as a promising novel therapeutic therapy for preventing and treating dementia. Studies have shown that natural products derived from kidney-tonifying herbs can effectively inhibit AD. Furthermore, endoplasmic reticulum (ER) stress is a critical factor in the pathology of AD. Regulation of ER stress is a crucial approach to prevent and treat AD. Thus, in this study, we first collected kidney-tonifying herbs, integrated chemical ingredients from multiple TCM databases, and constructed a comprehensive drug-target network. Subsequently, we employed the endophenotype network (network proximity) method to identify potential active ingredients in kidney-tonifying herbs that prevented AD via regulating ER stress. By combining the predicted outcomes, we discovered that 32 natural products could ameliorate AD pathology via regulating ER stress. After a comprehensive evaluation of the multi-network model and systematic pharmacological analyses, we further selected several promising compounds for in vitro testing in the APP-SH-SY5Y cell model. Experimental results showed that echinacoside and danthron were able to effectively reduce ER stress-mediated neuronal apoptosis by inhibiting the expression levels of BIP, p-PERK, ATF6, and CHOP in APP-SH-SY5Y cells. Overall, this study utilized the endophenotype network to preliminarily decipher the effective material basis and potential molecular mechanism of kidney-tonifying Chinese medicine for prevention and treatment of AD.

Bioinformatics analysis based on extracted ingredients combined with network pharmacology, molecular docking and molecular dynamics simulation to explore the mechanism of Jinbei oral liquid in the therapy of idiopathic pulmonary fibrosis

Objective

Jinbei oral liquid (JBOL), which is derived from a traditional hospital preparation, is frequently utilized to treat idiopathic pulmonary fibrosis (IPF) and has shown efficacy in clinical therapy. However, there are now several obstacles facing the mechanism inquiry, including target proteins, active components, and the binding affinity between crucial compounds and target proteins. To gain additional insight into the mechanisms underlying JBOL in anti-IPF, this study used bioinformation technologies, including network pharmacology, molecular docking, and molecular dynamic simulation, with a substantial amount of data based on realistic constituents.

Methods

Using network pharmacology, we loaded 118 realistic compounds into the SwissTargetPrediction and SwissADME databases and screened the active compounds and target proteins. IPF-related targets were collected from the OMIM, DisGeNET, and GeneCards databases, and the network of IPF-active constituents was built with Cytoscape 3.10.1. The GO and KEGG pathway enrichment analyses were carried out using Metascape, and the protein-protein interaction (PPI) network was constructed to screen the key targets with the STRING database. Finally, the reciprocal affinity between the active molecules and the crucial targets was assessed through the use of molecular docking and molecular dynamics simulation.

Results

A total of 122 targets and 34 tested active compounds were summarized in this investigation. Among these, kaempferol, apigenin, baicalein were present in high degree. PPI networks topological analysis identified eight key target proteins. AGE-RAGE, EGFR, and PI3K-Akt signaling pathways were found to be regulated during the phases of cell senescence, inflammatory response, autophagy, and immunological response in anti-IPF of JBOL. It was verified by molecular docking and molecular dynamics simulation that the combining way and binding energy between active ingredients and selected targets.

Conclusions

This work forecasts the prospective core ingredients, targets, and signal pathways of JBOL in anti-IPF, which has confirmed the multiple targets and pathways of JBOL in anti-IPF and provided the first comprehensive assessment with bioinformatic approaches. With empirical backing and an innovative approach to the molecular mechanism, JBOL is being considered as a potential new medication.

AI empowering traditional Chinese medicine?

For centuries, Traditional Chinese Medicine (TCM) has been a prominent treatment method in China, incorporating acupuncture, herbal remedies, massage, and dietary therapy to promote holistic health and healing. TCM has played a major role in drug discovery, with over 60% of small-molecule drugs approved by the FDA from 1981 to 2019 being derived from natural products. However, TCM modernization faces challenges such as data standardization and the complexity of TCM formulations. The establishment of comprehensive TCM databases has significantly improved the efficiency and accuracy of TCM research, enabling easier access to information on TCM ingredients and encouraging interdisciplinary collaborations. These databases have revolutionized TCM research, facilitating advancements in TCM modernization and patient care. In addition, advancements in AI algorithms and database data quality have accelerated progress in AI for TCM. The application of AI in TCM encompasses a wide range of areas, including herbal screening and new drug discovery, diagnostic and treatment principles, pharmacological mechanisms, network pharmacology, and the incorporation of innovative AI technologies. AI also has the potential to enable personalized medicine by identifying patterns and correlations in patient data, leading to more accurate diagnoses and tailored treatments. The potential benefits of AI for TCM are vast and diverse, promising continued progress and innovation in the field.

Lipophilic derivatives of EGCG as potent α-amylase and α-glucosidase inhibitors ameliorating oxidative stress and inflammation

Uncontrolled hyperglycemia leads to increased oxidative stress, chronic inflammation, and insulin resistance, rendering diabetes management harder to accomplish. To tackle these myriads of challenges, researchers strive to explore innovative multifaceted treatment strategies, including inhibiting carbohydrate hydrolases. Herein, we report alkyl-ether EGCG derivatives as potent α-amylase and α-glucosidase inhibitors that could simultaneously ameliorate oxidative stress and inflammation. 4″-C18 EGCG, the most promising compound, showed multifold improvement in glycaemic management compared to acarbose, with 230-fold greater inhibition (competitive) of α-glucosidase (IC50 0.81 µM) and 3-fold better inhibition of α-amylase (IC50 3.74 µM). All derivatives showed stronger antioxidant activity (IC50 6.16-15.76 µM) than vitamin C, while acarbose showed none. 4″-C18 EGCG also downregulated pro-inflammatory cytokines and showed no significant cytotoxicity up to 50 µM in primary human peripheral blood mononuclear cells (PBMC), non-cancerous cell line, 3T3-L1 and HEK 293. The in silico binding affinity analysis of 4″-C18 EGCG with α-amylase and α-glucosidase was found to exhibit a good extent of interaction as compared to acarbose. In comparison to EGCG, 4″-Cn EGCG derivatives were found to remain stable in the physiological conditions even after 24 h. Together, the reported molecules demonstrated multifaceted antidiabetic potential inhibiting carbohydrate hydrolases, reducing oxidative stress, and inflammation, which are known to aggravate diabetes.

Shensong yangxin, a multi-functional traditional Chinese medicine for arrhythmia: A review of components, pharmacological mechanisms, and clinical applications

As a common cardiovascular disease (CVD), Arrhythmia refers to any abnormality in the origin, frequency, rhythm, conduction velocity, timing, pathway, sequence, or other aspect of cardiac impulses, and it is one of the common cardiovascular diseases in clinical practice. At present, various ion channel blockers are used for treatment of arrhythmia that include Na+ ion channel blockers, K+ ion channel blockers and Ca2+ ion channel blockers. While these drugs offer benefits, they have led to a gradual increase in drug-related adverse reactions across various systems. As a result, the quest for safe and effective antiarrhythmic drugs is pressing. Recent years have seen some advancements in the treatment of ventricular arrhythmias using traditional Chinese medicine(TCM). The theory of Luobing in TCM has proposed a new drug intervention strategy of "fast and slow treatment, integrated regulation" leading to a shift in mindset from "antiarrhythmic" to "rhythm-regulating". Guided by this theory, the development of Shen Song Yang Xin Capsules (SSYX) has involved various Chinese medicinal ingredients that comprehensively regulate the myocardial electrophysiological mechanism, exerting antiarrhythmic effects on multiple ion channels and non-ion channels. Similarly, in clinical studies, evidence-based research has confirmed that SSYX combined with conventional antiarrhythmic drugs can more effectively reduce the occurrence of arrhythmias. Therefore, this article provides a comprehensive review of the composition and mechanisms of action, pharmacological components, network pharmacology analysis, and clinical applications of SSYX guided by the theory of Luobing, aiming to offer valuable insights for improved clinical management of arrhythmias and related research.

Tongxinluo capsule as a multi-functional traditional Chinese medicine in treating cardiovascular disease: A review of components, pharmacological mechanisms, and clinical applications

Cardiovascular diseases (CVDs) are one of the most significant diseases that pose a threat to human health. The innovative traditional Chinese medicine Tongxinluo Capsule, developed under the guidance of the theory of traditional Chinese medicine, has good clinical efficacy in various cardiovascular diseases, this medicine has effects such as blood protection, vascular protection, myocardial protection, stabilizing vulnerable plaques, and vasodilation. However, CVDs are a multifactorial disease, and their underlying mechanisms are not fully understood. Therefore, exploring the mechanism of action and clinical application of Tongxinluo Capsule in the treatment of various cardiovascular diseases is beneficial for exerting its therapeutic effect from multiple components, targets, and pathways. At the same time, it provides broader treatment ideas for other difficult to treat diseases in the cardiovascular event chain, and has significant theoretical and clinical significance for improving the treatment of cardiovascular diseases with traditional Chinese medicine.

Coumestrol facilitates apoptosis in colorectal cancer cells by interacting with ZIP8 protein via the ferroptosis pathway

Objective: So far, there have been no reports of coumestrol inhibiting colorectal cancer (CRC) through the ferroptosis pathway. This study is to investigate the mechanism of the traditional Chinese medicine monomer coumestrol in the treatment of CRC. Methods: Data on CRC transcriptome sequencing was obtained from the GEO database and TCGA database. Bioinformatics analyses were conducted to screen for CRC prognostic-related key genes and their potential binding monomers in traditional Chinese medicine. The inhibitory effect of coumestrol on CRC cell lines (COLO 205 & HCT 116) was determined using the CCK-8 assay, and cell apoptosis was assessed by flow cytometry. The content of ferrous ions was measured using the Ferrous Ion Content Assay Kit. The expression of ferroptosis pathway-related genes SLC39A8, NCOA4, VDAC2, and NOX2 before and after small interference RNA (siRNA) was examined through real-time PCR and Western blotting. Results: SLC39A8 was found to be associated with CRC clinical progression staging, and its encoded protein ZIP8 may bind to coumestrol. KEGG enrichment analysis suggested that ZIP8 plays a role in iron transmembrane transport and may affect the expression of ferroptosis pathway-related genes NCOA4, VDAC2, and NOX2. Coumestrol was found to induce apoptosis in CRC cell lines by upregulating the expression of ferroptosis pathway-related genes SLC39A8, NCOA4, VDAC2, and NOX2. However, coumestrol was unable to upregulate the expression of ferroptosis pathway-related genes in CRC cell lines after SLC39A8 interference. Conclusion: Coumestrol facilitates apoptosis in CRC cells by interacting with ZIP8 protein via the ferroptosis pathway.

Quercetin and Kaempferol as Multi-Targeting Antidiabetic Agents against Mouse Model of Chemically Induced Type 2 Diabetes

Diabetes, a multifactorial metabolic disorder, demands the discovery of multi-targeting drugs with minimal side effects. This study investigated the multi-targeting antidiabetic potential of quercetin and kaempferol. The druggability and binding affinities of both compounds towards multiple antidiabetic targets were explored using pharmacokinetic and docking software (AutoDock Vina 1.1.2). Our findings showed that quercetin and kaempferol obey Lipinski's rule of five and exhibit desirable ADMET (absorption, distribution, metabolism excretion, and toxicity) profiles. Both compounds showed higher binding affinities towards C-reactive protein (CRP), interleukin-1 (IL-1), dipeptidyl peptidase-4 (DPP-IV), peroxisome proliferator-activated receptor gamma (PPARG), protein tyrosine phosphatase (PTP), and sodium-glucose co-transporter-1 (SGLT-1) compared to metformin (the positive control). Both quercetin and kaempferol inhibited α-amylase activity (in vitro) up to 20.30 ± 0.49 and 37.43 ± 0.42%, respectively. Their oral supplementation significantly reduced blood glucose levels (p < 0.001), improved lipid profile (p < 0.001), and enhanced total antioxidant status (p < 0.01) in streptozotocin-nicotinamide (STZ-NA)-induced diabetic mice. Additionally, both compounds significantly inhibited the proliferation of Huh-7 and HepG2 (cancer cells) (p < 0.0001) with no effect on the viability of Vero cell line (non-cancer). In conclusion, quercetin and kaempferol demonstrated higher binding affinities towards multiple targets than metformin. In vitro and in vivo antidiabetic potential along with the anticancer activities of both compounds suggest promise for further development in diabetes management. The combination of both drugs did not show a synergistic effect, possibly due to their same target on the receptors.

Drug repurposing for cancer

In the dynamic landscape of cancer therapeutics, the innovative strategy of drug repurposing emerges as a transformative paradigm, heralding a new era in the fight against malignancies. This book chapter aims to embark on the comprehension of the strategic deployment of approved drugs for repurposing and the meticulous journey of drug repurposing from earlier times to the current era. Moreover, the chapter underscores the multifaceted and complex nature of cancer biology, and the evolving field of cancer drug therapeutics while emphasizing the mandate of drug repurposing to advance cancer therapeutics. Importantly, the narrative explores the latest tools, technologies, and cutting-edge methodologies including high-throughput screening, omics technologies, and artificial intelligence-driven approaches, for shaping and accelerating the pace of drug repurposing to uncover novel cancer therapeutic avenues. The chapter critically assesses the breakthroughs, expanding the repertoire of repurposing drug candidates in cancer, and their major categories. Another focal point of this book chapter is that it addresses the emergence of combination therapies involving repurposed drugs, reflecting a shift towards personalized and synergistic treatment approaches. The expert analysis delves into the intricacies of combinatorial regimens, elucidating their potential to target heterogeneous cancer populations and overcome resistance mechanisms, thereby enhancing treatment efficacy. Therefore, this chapter provides in-depth insights into the potential of repurposing towards bringing the much-needed big leap in the field of cancer therapeutics.

Wiring Between Close Nodes in Molecular Networks Evolves More Quickly Than Between Distant Nodes

As species diverge, a wide range of evolutionary processes lead to changes in protein-protein interaction (PPI) networks and metabolic networks. The rate at which molecular networks evolve is an important question in evolutionary biology. Previous empirical work has focused on interactomes from model organisms to calculate rewiring rates, but this is limited by the relatively small number of species and sparse nature of network data across species. We present a proxy for variation in network topology: variation in drug-drug interactions (DDIs), obtained by studying drug combinations (DCs) across taxa. Here, we propose the rate at which DDIs change across species as an estimate of the rate at which the underlying molecular network changes as species diverge. We computed the evolutionary rates of DDIs using previously published data from a high-throughput study in gram-negative bacteria. Using phylogenetic comparative methods, we found that DDIs diverge rapidly over short evolutionary time periods, but that divergence saturates over longer time periods. In parallel, we mapped drugs with known targets in PPI and cofunctional networks. We found that the targets of synergistic DDIs are closer in these networks than other types of DCs and that synergistic interactions have a higher evolutionary rate, meaning that nodes that are closer evolve at a faster rate. Future studies of network evolution may use DC data to gain larger-scale perspectives on the details of network evolution within and between species.

Antimalarial Drug Combination Predictions Using the Machine Learning Synergy Predictor (MLSyPred©) tool

PURPOSE

Antimalarial drug resistance is a global public health problem that leads to treatment failure. Synergistic drug combinations can improve treatment outcomes and delay the development of drug resistance. Here, we describe the implementation of a freely available computational tool, Machine Learning Synergy Predictor (MLSyPred©), to predict potential synergy in antimalarial drug combinations.

METHODS

The MLSyPred© synergy prediction method extracts molecular fingerprints from the drugs' biochemical structures to use as features and also cleans and prepares the raw data. Five machine learning algorithms (Logistic Regression, Random Forest, Support vector machine, Ada Boost, and Gradient Boost) were implemented to build prediction models. Implementation and application of the MLSyPred© tool were tested using datasets from 1540 combinations of 79 drugs and compounds biologically evaluated in pairs for three strains of Plasmodium falciparum (3D7, HB3, and Dd2).

RESULTS

The best prediction models were obtained using Logistic Regression for antimalarials with the strains Dd2 and HB3 (0.81 and 0.70 AUC, respectively) and Random Forest for antimalarials with 3D7 (0.69 AUC). The MLSyPred© tool yielded 45% precision for synergistically predicted antimalarial drug combinations that were annotated and biologically validated, thus confirming the functionality and applicability of the tool.

CONCLUSION

 The MLSyPred© tool is freely available and represents a promising strategy for discovering potential synergistic drug combinations for further development as novel antimalarial therapies.

Hypolipidemic and Antithrombotic Effect of 6'-O-Caffeoylarbutin from Vaccinium dunalianum Based on Zebrafish Model, Network Pharmacology, and Molecular Docking

Vaccinium dunalianum leaf buds make one of the most commonly used herbal teas of the Yi people in China, which is used to treat articular rheumatism, relax tendons, and stimulates blood circulation in the body. In addition, 6'-O-caffeoylarbutin (CA) is a standardized extract of V. dunalianum, which has been found in dried leaf buds, reaching levels of up to 31.76%. Because of the uncommon phenomenon, it is suggested that CA may have a potential therapeutic role in hyperlipidemia and thrombosis. This study was designed to study the efficacy of CA on treating hyperlipidemia and thrombosis and the possible mechanisms behind these effects. Hyperlipidemia and thrombosis zebrafish models were treated with CA to observe variations of the integrated optical density within the vessels and the intensity of erythrocyte staining within the hearts. The possible mechanisms were explored using network pharmacology and molecular docking. The results demonstrate that CA exhibits an excellent hypolipidemic effect on zebrafish at concentrations ranging from 3.0 to 30.0 μg/mL and shows thrombosis inhibitory activity in zebrafish at a concentration of 30.0 μg/mL, with an inhibition rate of 44%. Moreover, network pharmacological research shows that MMP9, RELA, MMP2, PRKCA, HSP90AA1, and APP are major targets of CA for therapy of hyperlipidemia and thrombosis, and may relate to pathways in cancer, chemical carcinogenesis-receptor activation, estrogen signaling pathway, and the AGE-RAGE signaling pathway in diabetic complications.

Network pharmacology: towards the artificial intelligence-based precision traditional Chinese medicine

Network pharmacology (NP) provides a new methodological perspective for understanding traditional medicine from a holistic perspective, giving rise to frontiers such as traditional Chinese medicine network pharmacology (TCM-NP). With the development of artificial intelligence (AI) technology, it is key for NP to develop network-based AI methods to reveal the treatment mechanism of complex diseases from massive omics data. In this review, focusing on the TCM-NP, we summarize involved AI methods into three categories: network relationship mining, network target positioning and network target navigating, and present the typical application of TCM-NP in uncovering biological basis and clinical value of Cold/Hot syndromes. Collectively, our review provides researchers with an innovative overview of the methodological progress of NP and its application in TCM from the AI perspective.

Qili Qiangxin (QLQX) capsule as a multi-functional traditional Chinese medicine in treating chronic heart failure (CHF): A review of ingredients, molecular, cellular, and pharmacological mechanisms

Chronic heart failure (CHF) is a key part of cardiovascular continuum. Under the guidance of the theory of vessel-collateral doctrine, the present study proposes therapeutic benefits of Qili Qiangxin (QLQX) capsules, an innovative Chinese medicine, on chronic heart failure. The studies show that multiple targets of the drug on CHF, including enhancing myocardial systole, promoting urine excretion, inhibiting excessive activation of the neuroendocrine system, preventing ventricular remodeling by inhibiting inflammatory response, myocardial fibrosis, apoptosis and autophagy, enhancing myocardial energy metabolism, promoting angiogenesis, and improving endothelial function. Investigation on the effects and mechanism of the drug is beneficial to the treatment of chronic heart failure (CHF) through multiple targets and/or signaling pathways. Meanwhile, it provides new insights to further understand other refractory diseases in the cardiovascular continuum, and it also has an important theoretical and practical significance in enhancing prevention and therapeutic effect of traditional Chinese medicine for these diseases.

Integrating Chemical Profiling, In Vivo Study, and Network Pharmacology to Explore the Anti-inflammatory Effect of Pterocarpus dalbergioides Fruits and Its Correlation with the Major Phytoconstituents

The purpose of this study is to explore the anti-inflammatory activity of Pterocarpus dalbergioides fruit extract (PFE) and the underlying mechanism. Chemical profiling using ultraperformance liquid chromatography/mass spectrometry identified 28 compounds in PFE (12 flavonoids, 5 fatty acids, 4 phenolic compounds, 3 alkaloids, 2 sesquiterpenes, and 2 xanthophylls). PFE (2 g/kg) significantly inhibited carrageenan-induced rat paw edema after 4 h of administration (42% inhibition). A network-based strategy and molecular docking studies were utilized to uncover the anti-inflammatory mechanism. Out of the identified compounds, 16 compounds with DL ≥ 0.18 and F ≥ 30% were selected using bioavailability (F) and drug-likeness (DL) metrics. The network analysis revealed that 90 genes are considered key targets for the selected compounds and linked to the anti-inflammatory effect. Among all compounds, linoleic acid was found to be the top-most active constituent as it targets maximum genes. Four targets (TNF, IL6, AKT1, and CCL2) among the top 10 genes were found to be the main target genes that may contribute to the anti-inflammatory potential of PFE. Furthermore, KEGG (Kyoto encyclopedia of genes and genomes) pathway analysis revealed that PFE might regulate inflammation through five pathways: neuroactive ligand-receptor interaction, lipid and atherosclerosis, fluid shear stress and atherosclerosis, TNF signaling pathway, and rheumatoid arthritis. The docking study predicted the significant binding affinity between the top four active constituents (linoleic acid, 9-octadecenoic acid, 11,12,13-trihydroxy-9-octadecenoic acid, and rhamnetin-3-O-rhamnoside) and the selected target proteins (TNF and AKT1). The findings highlight PFE as a promising drug lead for controlling inflammation.

Repositioning of clinically approved drug Bazi Bushen capsule for treatment of Aizheimer's disease using network pharmacology approach and in vitro experimental validation

Aims

To explore the new indications and key mechanism of Bazi Bushen capsule (BZBS) by network pharmacology and in vitro experiment.

Methods

The ingredients library of BZBS was constructed by retrieving multiple TCM databases. The potential target profiles of the components were predicted by target prediction algorithms based on different principles, and validated by using known activity data. The target spectrum of BZBS with high reliability was screened by considering the source of the targets and the node degree in compound-target (C-T) network. Subsequently, new indications for BZBS were predicted by disease ontology (DO) enrichment analysis and initially validated by GO and KEGG pathway enrichment analysis. Furthermore, the target sets of BZBS acting on AD signaling pathway were identified by intersection analysis. Based on STRING database, the PPI network of target was constructed and their node degree was calculated. Two Alzheimer's disease (AD) cell models, BV-2 and SH-SY5Y, were used to preliminarily verify the anti-AD efficacy and mechanism of BZBS in vitro.

Results

In total, 1499 non-repeated ingredients were obtained from 16 herbs in BZBS formula, and 1320 BZBS targets with high confidence were predicted. Disease enrichment results strongly suggested that BZBS formula has the potential to be used in the treatment of AD. GO and KEGG enrichment results provide a preliminary verification of this point. Among them, 113 functional targets of BZBS belong to AD pathway. A PPI network containing 113 functional targets and 1051 edges for the treatment of AD was constructed. In vitro experiments showed that BZBS could significantly reduce the release of TNF-α and IL-6 and the expression of COX-2 and PSEN1 in Aβ_25-35-induced BV-2 cells, which may be related to the regulation of ERK_1/2/NF-κB signaling pathway. BZBS reduced the apoptosis rate of Aβ_25-35 induced SH-SY5Y cells, significantly increased mitochondrial membrane potential, reduced the expression of Caspase3 active fragment and PSEN1, and increased the expression of IDE. This may be related to the regulation of GSK-3β/β-catenin signaling pathway.

Conclusions

BZBS formula has a potential use in the treatment of AD, which is achieved through regulation of ERK_1/2, NF-κB signaling pathways, and GSK-3β/β-catenin signaling pathway. Furthermore, the network pharmacology technology is a feasible drug repurposing strategy to reposition new clinical use of approved TCM and explore the mechanism of action. The study lays a foundation for the subsequent in-depth study of BZBS in the treatment of AD and provides a basis for its application in the clinical treatment of AD.

Calycosin inhibits gemcitabine-resistant lung cancer cells proliferation through modulation of the LDOC1/GNL3L/NFκB

Lung cancer is the most common malignant cancer worldwide. Combination therapies are urgently needed to increase patient survival. Calycosin is a phytoestrogen isoflavone that has been reported previously to inhibit tumor cell growth, although its effects on lung cancer remain unclear. The aim of this study was to investigate the effects of calycosin on cell proliferation and apoptosis of gemcitabine-resistant lung cancer cells. Using calycosin to treat human lung cancer cells (CL1-0) and gemcitabine-resistant lung cancer cells (CL1-0 GEMR) and examine the effects on the cells. Cultured human lung cancer cells (CL1-0) and gemcitabine-resistant lung cancer cells (CL1-0 GEMR) were treated with increasing concentrations of calycosin. Cell viability and apoptosis were studied by the 3-(4,5-dimethylthiazol-2-yl)-2,5 diphenyltetrazolium bromide, flow cytometry, and TUNEL assays. Western blots were used to measure the expression levels of proliferation-related proteins and cancer stem cell proteins in CL1-0 GEMR cells. The results showed that calycosin treatment inhibited cell proliferation, decreased cell migration ability, and suppressed cancer stem cell properties in CL1-0 GEMR cells. Interestingly, in CL1-0 GEMR cells, calycosin treatment not only increased LDOC1 but also decreased GNL3L/NFκB protein levels and mRNA levels, in concentration-dependent manners. We speculate that calycosin inhibited cell proliferation of the gemcitabine-resistant cell line through regulating the LDOC1/GNL3L/NFκB pathway.

Network pharmacology, a promising approach to reveal the pharmacology mechanism of Chinese medicine formula

ETHNOPHARMACOLOGICAL RELEVANCE

Network pharmacology is a new discipline based on systems biology theory, biological system network analysis, and multi-target drug molecule design specific signal node selection. The mechanism of action of TCM formula has the characteristics of multiple targets and levels. The mechanism is similar to the integrity, systematization and comprehensiveness of network pharmacology, so network pharmacology is suitable for the study of the pharmacological mechanism of Chinese medicine compounds.

AIM OF THE STUDY

The paper summarizes the present application status and existing problems of network pharmacology in the field of Chinese medicine formula, and formulates the research ideas, up-to-date key technology and application method and strategy of network pharmacology. Its purpose is to provide guidance and reference for using network pharmacology to reveal the modern scientific connotation of Chinese medicine.

MATERIALS AND METHODS

Literatures in this review were searched in PubMed, China National Knowledge Infrastructure (CNKI), Web of Science, ScienceDirect and Google Scholar using the keywords "traditional Chinese medicine", "Chinese herb medicine" and "network pharmacology". The literature cited in this review dates from 2002 to 2022.

RESULTS

Using network pharmacology methods to predict the basis and mechanism of pharmacodynamic substances of traditional Chinese medicines has become a trend.

CONCLUSION

Network pharmacology is a promising approach to reveal the pharmacology mechanism of Chinese medicine formula.

Mechanisms of Ganweikang Tablets against Chronic Hepatitis B: A Comprehensive Study of Network Analysis, Molecular Docking, and Chemical Profiling

The hepatitis B virus (HBV) is one of the major viral infection problems worldwide in public health. The exclusive proprietary Chinese medicine Ganweikang (GWK) tablet has been marketed for years in the treatment of chronic hepatitis B (CHB). However, the pharmacodynamic material basis and underlying mechanism of GWK are not completely clear. This study is aimed at investigating the pharmacological mechanism of the GWK tablet in the treatment of CHB. The chemical ingredient information was obtained from the Traditional Chinese Medicine Database and Analysis Platform (TCMSP), Traditional Chinese Medicines Integrated Database (TCMID), and Shanghai Institute of Organic Chemistry of CAS. Ingredients and disease-related targets were defined by a combination of differentially expressed genes from CHB transcriptome data and open-source databases. Target-pathway-target (TPT) network analysis, molecular docking, and chemical composition analysis were adopted to further verify the key targets and corresponding active ingredients of GWK. Eight herbs of GWK were correlated to 330 compounds with positive oral bioavailability, and 199 correlated targets were identified. The TPT network was constructed based on the 146 enriched targets by KEGG pathway analysis, significantly associated with 95 pathways. Twenty-five nonvolatile components and 25 volatile components in GWK were identified in UPLC-QTOF/MS and GC-MS chromatograms. The key active ingredients of GWK include ferulic acid, oleanolic acid, ursolic acid, tormentic acid, 11-deoxyglycyrrhetic acid, dibenzoyl methane, anisaldehyde, wogonin, protocatechuic acid, psoralen, caffeate, dimethylcaffeic acid, vanillin, β-amyrenyl acetate, formonentin, aristololactam IIIa, and 7-methoxy-2-methyl isoflavone, associated with targets CA2, NFKB1, RELA, AKT1, JUN, CA1, CA6, IKBKG, FOS, EP300, CREB1, STAT1, MMP9, CDK2, ABCB1, and ABCG2.

Chinese herbal medicine for the treatment of cardiovascular diseases ─ targeting cardiac ion channels

Cardiovascular disease (CVD) remains the leading cause of morbidity and mortality, imposing an increasing global health burden. Cardiac ion channels (voltage-gated Na_V, Ca_V, K_Vs, and others) synergistically shape the cardiac action potential (AP) and control the heartbeat. Dysfunction of these channels, due to genetic mutations, transcriptional or post-translational modifications, may disturb the AP and lead to arrhythmia, a major risk for CVD patients. Although there are five classes of anti-arrhythmic drugs available, they can have varying levels of efficacies and side effects on patients, possibly due to the complex pathogenesis of arrhythmias. As an alternative treatment option, Chinese herbal remedies have shown promise in regulating cardiac ion channels and providing anti-arrhythmic effects. In this review, we first discuss the role of cardiac ion channels in maintaining normal heart function and the pathogenesis of CVD, then summarize the classification of Chinese herbal compounds, and elaborate detailed mechanisms of their efficacy in regulating cardiac ion channels and in alleviating arrhythmia and CVD. We also address current limitations and opportunities for developing new anti-CVD drugs based on Chinese herbal medicines.

Mechanism Repositioning Based on Integrative Pharmacology: Anti-Inflammatory Effect of Safflower in Myocardial Ischemia–Reperfusion Injury

Safflower (Carthamus tinctorius. L) possesses anti-tumor, anti-thrombotic, anti-oxidative, immunoregulatory, and cardio-cerebral protective effects. It is used clinically for the treatment of cardio-cerebrovascular disease in China. This study aimed to investigate the effects and mechanisms of action of safflower extract on myocardial ischemia–reperfusion (MIR) injury in a left anterior descending (LAD)-ligated model based on integrative pharmacology study and ultra-performance liquid chromatography–quadrupole time-of-flight-tandem mass spectrometer (UPLC-QTOF-MS/MS). Safflower (62.5, 125, 250 mg/kg) was administered immediately before reperfusion. Triphenyl tetrazolium chloride (TTC)/Evans blue, echocardiography, terminal deoxynucleotidyl transferase-mediated dUTP nick-end labeling (TUNEL) assay, lactate dehydrogenase (LDH) ability, and superoxide dismutase (SOD) levels were determined after 24 h of reperfusion. Chemical components were obtained using UPLC-QTOF-MS/MS. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed. Quantitative real-time polymerase chain reaction (qRT-PCR) and Western blotting were used to analyze mRNA and protein levels, respectively. Safflower dose-dependently reduced myocardial infarct size, improved cardiac function, decreased LDH levels, and increased SOD levels in C57/BL6 mice. A total of 11 key components and 31 hub targets were filtered based on the network analysis. Comprehensive analysis indicated that safflower alleviated inflammatory effects by downregulating the expression of NFκB1, IL-6, IL-1β, IL-18, TNFα, and MCP-1 and upregulating NFκBia, and markedly increased the expression of phosphorylated PI3K, AKT, PKC, and ERK/2, HIF1α, VEGFA, and BCL2, and decreased the level of BAX and phosphorylated p65. Safflower shows a significant cardioprotective effect by activating multiple inflammation-related signaling pathways, including the NFκB, HIF-1α, MAPK, TNF, and PI3K/AKT signaling pathways. These findings provide valuable insights into the clinical applications of safflower.

Prospects for the application of traditional Chinese medicine network pharmacology in food science research

There has always been a particular difficulty with in-depth research on the mechanisms of food nutrition and bioactivity. The main function of food is to meet the nutritional needs of the human body, rather than to exert a therapeutic effect. Its relatively modest biological activity makes it difficult to study from the perspective of general pharmacological models. With the popularity of functional foods and the concept of dietary therapy, and the development of information and multi-omics technology in food research, research into these mechanisms is moving towards a more microscopic future. Network pharmacology has accumulated nearly 20 years of research experience in traditional Chinese medicine (TCM), and there has been no shortage of work from this perspective on the medicinal functions of food. Given the similarity between the concept of 'multi-component-multi-target' properties of food and TCM, we think that network pharmacology is applicable to the study of the complex mechanisms of food. Here we review the development of network pharmacology, summarize its application to 'medicine and food homology', and propose a methodology based on food characteristics for the first time, demonstrating its feasibility for food research. © 2023 Society of Chemical Industry.

Insights into the mechanisms of triptolide nephrotoxicity through network pharmacology-based analysis and RNA-seq

INTRODUCTION

Triptolide (TPL) is a promising plant-derived compound for clinical therapy of multiple human diseases; however, its application was limited considering its toxicity.

METHODS

To explore the underlying molecular mechanism of TPL nephrotoxicity, a network pharmacology based approach was utilized to predict candidate targets related with TPL toxicity, followed by deep RNA-seq analysis to characterize the features of three transcriptional elements include protein coding genes (PCGs), long noncoding RNAs (lncRNAs) and circular RNAs (circRNAs) as well as their associations with nephrotoxicity in rats with TPL treatment.

RESULTS & DISCUSSION

Although the deeper mechanisms of TPL nephrotoxcity remain further exploration, our results suggested that c-Jun is a potential target of TPL and Per1 related circadian rhythm signaling is involved in TPL induced renal toxicity.

Network-based drug repurposing for the treatment of COVID-19 patients in different clinical stages

In the severe acute respiratory coronavirus disease 2019 (COVID-19) pandemic, there is an urgent need to develop effective treatments. Through a network-based drug repurposing approach, several effective drug candidates are identified for treating COVID-19 patients in different clinical stages. The proposed approach takes advantage of computational prediction methods by integrating publicly available clinical transcriptome and experimental data. We identify 51 drugs that regulate proteins interacted with SARS-CoV-2 protein through biological pathways against COVID-19, some of which have been experimented in clinical trials. Among the repurposed drug candidates, lovastatin leads to differential gene expression in clinical transcriptome for mild COVID-19 patients, and estradiol cypionate mainly regulates hormone-related biological functions to treat severe COVID-19 patients. Multi-target mechanisms of drug candidates are also explored. Erlotinib targets the viral protein interacted with cytokine and cytokine receptors to affect SARS-CoV-2 attachment and invasion. Lovastatin and testosterone block the angiotensin system to suppress the SARS-CoV-2 infection. In summary, our study has identified effective drug candidates against COVID-19 for patients in different clinical stages and provides comprehensive understanding of potential drug mechanisms.

Biochemical reaction network topology defines dose-dependent Drug-Drug interactions

Drug combination therapy is a promising strategy to enhance the desired therapeutic effect, while reducing side effects. High-throughput pairwise drug combination screening is a commonly used method for discovering favorable drug interactions, but is time-consuming and costly. Here, we investigate the use of reaction network topology-guided design of combination therapy as a predictive in silico drug-drug interaction screening approach. We focused on three-node enzymatic networks, with general Michaelis-Menten kinetics. The results revealed that drug-drug interactions critically depend on the choice of target arrangement in a given topology, the nature of the drug, and the desired level of change in the network output. The results showed a negative correlation between antagonistic interactions and the dosage of drugs. Overall, the negative feedback loops showed the highest synergistic interactions (the lowest average combination index) and, intriguingly, required the highest drug doses compared to other topologies under the same condition.

Improvement of obesity by Liupao tea is through the IRS-1/PI3K/AKT/GLUT4 signaling pathway according to network pharmacology and experimental verification

BACKGROUND

Obesity is a state of accumulating excessive body fat, charactering by a high blood lipid and associating with various metabolic diseases. As a kind of dark tea, many studies revealed that long-term drinking Liupao tea (LT) can reduce weight (Liu et al., 2014). However, the anti-obesity mechanism and active ingredients of LT are not known.

METHODS

Liquid chromatography-mass spectrometry (LC-MS) combined with network pharmacology was used to screen the active components and related targets of Liupao tea water extract (LTWE). The key anti-obesity targets and pathways of LTWE were predicted by protein-protein interaction (PPI) networks, and enrichment analyses using Kyoto Encyclopedia of Genes and Genomes and Gene Ontology databases. Then, the active components selected by high-performance liquid chromatography (HPLC) fingerprinting were used together with LTWE in an adipogenic model and insulin resistance (IR) model in vitro.

RESULTS

Most of the compounds identified from LTWE were flavonofids, esters, and amides. Key targets such as RAC-alpha serine/threonine-protein kinase, insulin, and tumor necrosis factor (TNF) were involved in the phosphatidylinositol-3-kinase-protein kinase B (PI3K-AKT) signaling pathway, pathways in cancer, and other pathways. Four active components were screened by network pharmacology combined with HPLC fingerprinting. The in vitro experiment of LTWE and its four active components showed that in insulin-resistant 3T3-L1 cells, LTWE, (-)-epigallocatechin gallate (EGCG) and gallic acid (GA) inhibited adipocyte differentiation. Three factors could inhibit the differentiation of 3T3-L1 cells by decreasing gene expression of peroxisome proliferators-activated receptor γ (PPARγ), fatty acid synthase (FAS), CCAAT/enhancer binding proteins-α (C/EBPα) and interleukin-6 (IL-6). Caffeine and ellagic acid (EA) showed opposite results, but their effects on promoting adipose differentiation diminished with increasing concentrations of drug. In dexamethasone-induced insulin-resistant 3T3-L1 cells, the fluorescence intensity of 2-Deoxy-2-[(7-nitro-2,1,3-Benzoxadiazol-4-yl)amino]-d-glucose revealed that LTWE, GA, EGCG, caffeine, and EA significantly promoted glucose consumption. LTWE, GA, and EA improved insulin resistance in adipocytes by upregulating gene expression of insulin receptor substrate-1 (IRS-1), PI3K, AKT, and glucose transporter 4 (GLUT4).

CONCLUSION

LC-MS combined with network pharmacology preliminarianized that LTWE acts mainly on the PI3K-AKT signaling pathway. Cell experiments revealed that the anti-obesity effect of LTWE is the result of multi-component action, which inhibits the proliferation and differentiation of preadipocytes by regulating gene expression of adipogenic transcription factors and proinflammatory factors, and improves IR by activating the IRS-1/PI3K/AKT/GLUT4 pathway.

Exploration of the Potential Mechanisms of Lingqihuangban Granule for Treating Diabetic Retinopathy Based on Network Pharmacology

BACKGROUND

The Lingqihuangban Granule (LQHBG), a remarkable Chinese herbal compound, has been used for decades to treat diabetic retinopathy (DR) in the Department of Ophthalmology, Shanghai General Hospital (National Clinical Research Center for Eye Diseases) with obvious effects. Through the method of network pharmacology, the present study constructed bioactive component-relative targets and protein-protein interaction network of the LQHBG and implemented gene function analysis and pathway enrichment of targets, discussing the mechanisms of traditional Chinese medicine LQHBG in treating DR.

MATERIALS AND METHODS

The bioactive ingredients of LQHBG were screened and obtained using TCMSP and ETCM databases, while the potential targets of bioactive ingredients were predicted by SwissTargetPrediction and ETCM databases. Compared with the disease target databases of TTD, Drugbank, OMIM and DisGeNET, the therapeutic targets of LQHBG for DR were extracted. Based on the DAVID platform, GO annotation and KEGG pathway analyses of key targets were explored, combined with the screening of core pathways on the Omicshare database and pathway annotation on the Reactome database.

RESULTS

A total of 357 bioactive components were screened from LQHBG, involving 86 possible targets of LQHBG treating DR. In the PPI network, INS and ALB were identified as key genes. The effective targets were enriched in multiple signaling pathways, such as PI3K/Akt and MAPK pathways.

CONCLUSION

This study revealed the possible targets and pathways of LQHBG treating DR, reflecting the characteristics of multicomponent, multitarget and multipathway treatment of a Chinese herbal compound, and provided new ideas for further discussion.

Network pharmacology predicts combinational effect of novel herbal pair consist of Ephedrae herba and Coicis semen on adipogenesis in 3T3-L1 cells

BACKGROUND

Herbal combinations are regarded as basic strategy in oriental medicine with various purposes. Ephedrae herba (EH) and Coicis semen (CS) are two herbal medicines used to treat obesity in many herbal prescriptions, yet the effect and significance of this herbal pair have not been evaluated.

PURPOSE

This study is to elucidate the effect of a novel herbal pair, EH-CS, on obesity and identify the key synergistic mechanism underlying it.

METHODS

We investigated the network of herbs comprising the anti-obesity herbal prescriptions. Using the tools of network pharmacology, we investigated the compound-target interactions of EH and CS in combination to predict their effects in combination. Five EH-CS samples with different EH to CS ratios were prepared to investigate their efficacies in adipocytes.

RESULTS

1-mode network analysis of herbs in prescriptions based on literature review revealed the importance of EH-CS in anti-obesity prescriptions. The herbal combination comprised of equivalent weights (1:1) of EH and CS most potently reduced mature adipocyte adiposity, although several markers of adipogenesis and lipid synthesis were more suppressed by pure EH. PTGS2 (COX-2 gene) expression, a common target of EH and CS as deduced by compound-target network analysis, was affected by EH-CS extract treatments. However, EH at high concentration (25 μg/ml) notably increased PTGS2 expression without adversely affecting cell viability. However, EH-CS combination of the same concentration markedly decreased PTGS2 gene expression.

CONCLUSION

These results show that the compounds in CS and EH act in concert to enhance the pharmacological effect of EH, but control unexpected effects of EH treatment.

Gou Qi Zi inhibits proliferation and induces apoptosis through the PI3K/AKT1 signaling pathway in non-small cell lung cancer

Background

Gou Qi Zi (Lycium barbarum) is a traditional herbal medicine with antioxidative effects. Although Gou Qi Zi has been used to prevent premature aging and in the treatment of non-small cell lung cancer (NSCLC), its mechanism of action in NSCLC remains unclear. The present study utilized network pharmacology to assess the potential mechanism of action of Gou Qi Zi in the treatment of NSCLC.

Methods

The TCMSP, TCMID, SwissTargetPrediction, DrugBank, DisGeNET, GeneCards, OMIM and TTD databases were searched for the active components of Gou Qi Zi and their potential therapeutic targets in NSCLC. Protein-protein interaction networks were identified and the interactions of target proteins were analyzed. Involved pathways were determined by GO enrichment and KEGG pathway analyses using the Metascape database, and molecular docking technology was used to study the interactions between active compounds and potential targets. These results were verified by cell counting kit-8 assays, BrdU labeling, flow cytometry, immunohistochemistry, western blotting, and qRT-PCR.

Results

Database searches identified 33 active components in Gou Qi Zi, 199 predicted biological targets and 113 NSCLC-related targets. A network of targets of traditional Chinese medicine compounds and potential targets of Gou Qi Zi in NSCLC was constructed. GO enrichment analysis showed that Gou Qi Zi targeting of NSCLC was mainly due to the effect of its associated lipopolysaccharide. KEGG pathway analysis showed that Gou Qi Zi acted mainly through the PI3K/AKT1 signaling pathway in the treatment of NSCLC. Molecular docking experiments showed that the bioactive compounds of Gou Qi Zi could bind to AKT1, C-MYC and TP53. These results were verified by experimental assays.

Conclusion

Gou Qi Zi induces apoptosis and inhibits proliferation of NSCLC in vitro and in vivo by inhibiting the PI3K/AKT1 signaling pathway.

Potential bioactive compounds and mechanisms of Fibraurea recisa Pierre for the treatment of Alzheimer's disease analyzed by network pharmacology and molecular docking prediction

Introduction

Heat-clearing and detoxifying Chinese medicines have been documented to have anti-Alzheimer's disease (AD) activities according to the accumulated clinical experience and pharmacological research results in recent decades. In this study, Fibraurea recisa Pierre (FRP), the classic type of Heat-clearing and detoxifying Chinese medicine, was selected as the object of research.

Methods

12 components with anti-AD activities were identified in FRP by a variety of methods, including silica gel column chromatography, multiple databases, and literature searches. Then, network pharmacology and molecular docking were adopted to systematically study the potential anti-AD mechanism of these compounds. Consequently, it was found that these 12 compounds could act on 235 anti-AD targets, of which AKT and other targets were the core targets. Meanwhile, among these 235 targets, 71 targets were identified to be significantly correlated with the pathology of amyloid beta (Aβ) and Tau.

Results and discussion

In view of the analysis results of the network of active ingredients and targets, it was observed that palmatine, berberine, and other alkaloids in FRP were the key active ingredients for the treatment of AD. Further, Kyoto encyclopedia of genes and genomes (KEGG) pathway enrichment analysis revealed that the neuroactive ligand-receptor interaction pathway and PI3K-Akt signaling pathway were the most significant signaling pathways for FRP to play an anti-AD role. Findings in our study suggest that multiple primary active ingredients in FRP can play a multitarget anti-AD effect by regulating key physiological processes such as neurotransmitter transmission and anti-inflammation. Besides, key ingredients such as palmatine and berberine in FRP are expected to be excellent leading compounds of multitarget anti-AD drugs.

Calycosin attenuates Angiostrongylus cantonensis-induced parasitic meningitis through modulation of HO-1 and NF-κB activation

Angiostrongylus cantonensis causes a form of parasitic meningitis in humans. Albendazole (ABZ) kills nematode larvae in the brain. However, dead larvae can trigger a severe inflammatory response, resulting in brain damage. Accumulating evidence suggests that calycosin represents a potential anti-inflammatory therapeutic candidate. In this study, we investigated the combined effects of ABZ and calycosin in angiostrongyliasis caused by A. cantonensis in BALB/c mice. Inflammatory mediators (such as phospho-nuclear factor-κB, cyclooxygenase-2, matrix metalloproteinase-9, tumour necrosis factor-α and interleukin-1β) are associated with the development of meningitis and immune inflammatory reactions. We found that A. cantonensis significantly induces inflammatory mediator production and increases the blood–brain barrier (BBB) permeability. However, co-administration of both ABZ and calycosin markedly suppressed meningitis and inflammatory mediator production and decreased the BBB permeability compared to treatment with a single drug. Furthermore, calycosin and ABZ plus calycosin treatment facilitated production of the antioxidant haem oxygenase-1 (HO-1). Moreover, co-therapy with ABZ and calycosin failed to mitigate angiostrongyliasis in the presence of tin-protoporphyrin IX, an HO-1-specific inhibitor. This finding suggests that the beneficial effects of ABZ plus calycosin treatment on the regulation of inflammation are mediated by the modulation of HO-1 activation. The present results provide new insights into the treatment of human angiostrongyliasis using co-therapy with ABZ and calycosin.

Multiple-Gene Regulation for Enhanced Antitumor Efficacy with Branch-PCR-Assembled TP53 and MYC Gene Nanovector

Multiple proteins are involved in network regulation through the crosstalk of different signaling pathways in cancers. Here, we propose a novel strategy of genome therapy with branch-PCR-assembled gene nanovectors to perform network-based gene regulation at multiple levels for cancer therapy. To validate network-based multiplex-gene regulation for genome therapy, we chose to simultaneously target one tumor suppressor gene (TP53) and one oncogene (MYC) in two different signaling pathways. The results showed that, compared to gene nanovectors targeting single genes (NP-TP53 and NP-shMYC), branch-PCR-assembled gene nanovectors simultaneously expressing p53 proteins and MYC shRNA arrays (NP-TP53-shMYC) showed enhanced antitumor efficacy in both MDA-MB-231 cancer cells and an MDA-MB-231-tumor-bearing mouse model. These findings indicate the feasibility and effectiveness of genome therapy in cancer therapy.

Identification of the Mechanism of Matrine Combined with Glycyrrhizin for Hepatocellular Carcinoma Treatment through Network Pharmacology and Bioinformatics Analysis

Matrine and glycyrrhizin are representative active ingredients of traditional Chinese medicine (TCM) used in clinical practice. Studies have demonstrated that matrine has antitumor pharmacological effects and that glycyrrhizin protects liver function. However, the potential bioactive compounds and mechanisms remain unknown, as well as whether they have synergistic effects in killing cancer cells and protecting liver cells. To investigate the synergistic effects and mechanism of matrine combined with glycyrrhizin in hepatocellular carcinoma (HCC) treatment, we used both network pharmacology and bioinformatics analyses. First, the chemical gene interaction information of matrine and glycyrrhizin was obtained from the PubChem database. The pathogenic genes of HCC were accessed from five public databases. The RNA sequencing data and clinical information of HCC patients were downloaded from The Cancer Genome Atlas (TCGA). Next, the overlapping genes among the potential targets of matrine and glycyrrhizin and HCC-related targets were determined using bioinformatics analysis. We constructed the drug-target interaction network. Prognosis-associated genes were acquired through the univariate Cox regression model and Lasso-Cox regression model. The results were verified by the International Cancer Genome Consortium (ICGC) database. Finally, we predicted the immune function of the samples. The drug-target interaction network consisted of 10 matrine and glycyrrhizin targets. We selected a Lasso-Cox regression model consisting of 3 differentially expressed genes (DEGs) to predict the efficacy of the combination in HCC. Subsequently, we successfully predicted the overall survival of HCC patients using the constructed prognostic model and investigated the correlation of the immune response. Matrine and glycyrrhizin have synergistic effects on HCC. The model we obtained consisted of three drug-target genes by Lasso-Cox regression analysis. The model independently predicted the combined effect of matrine and glycyrrhizin in HCC treatment and OS, which will be helpful for guiding clinical treatment. The prognostic model was correlated with the immune cells and immune checkpoints of patients, which had an adjuvant effect on HCC immunotherapy. Matrine and glycyrrhizin can have therapeutic effects on HCC by promoting the production or enhancing the core gene activity in the drug network and improving the immune system function of patients.

Yuan-Zhi decoction in the treatment of Alzheimer’s disease: An integrated approach based on chemical profiling, network pharmacology, molecular docking and experimental evaluation

Yuan-Zhi Decoction (YZD) is a traditional Chinese medical formulation with demonstrated clinical benefits in Alzheimer’s disease (AD). We used liquid chromatography coupled with mass spectrometry to identify 27 unique chemical components of YZD. Analyzing these using network pharmacology and molecular docking models identified 34 potential interacting molecular targets involved in 26 biochemical pathways. When tested in an animal model of AD, the APP/PS1 transgenic mice showed measurable improvements in spatial orientation and memory after the administration of YZD. These improvements coincided with significantly reduced deposition of Aβ plaques and tau protein in the hippocampi in the treated animals. In addition, a decreased BACE1 and beta-amyloid levels, a downregulation of the p-GSK-3β/GSK-3β, and an upregulation of the PI3K and p-AKT/AKT pathway was seen in YZD treated animals. These in vivo changes validated the involvement of molecular targets and pathways predicted in silico analysis of the chemical components of YZD. This study provides scientific support for the clinical use of YZD and justifies further investigations into its effects in AD. Furthermore, it demonstrates the utility of network pharmacology in elucidating the biochemical mechanisms underlying the beneficial effects of traditional Chinese medicines (TCM).

MatchMaker: A Deep Learning Framework for Drug Synergy Prediction

Drug combination therapies have been a viable strategy for the treatment of complex diseases such as cancer due to increased efficacy and reduced side effects. However, experimentally validating all possible combinations for synergistic interaction even with high-throughout screens is intractable due to vast combinatorial search space. Computational techniques can reduce the number of combinations to be evaluated experimentally by prioritizing promising candidates. We present MatchMaker that predicts drug synergy scores using drug chemical structure information and gene expression profiles of cell lines in a deep learning framework. For the first time, our model utilizes the largest known drug combination dataset to date, DrugComb. We compare the performance of MatchMaker with the state-of-the-art models and observe up to  ∼ 15% correlation and  ∼ 33% mean squared error (MSE) improvements over the next best method. We investigate the cell types and drug pairs that are relatively harder to predict and present novel candidate pairs. MatchMaker is built and available at https://github.com/tastanlab/matchmaker.

Metabolomics and integrated network pharmacology analysis reveal SNKAF decoction suppresses cell proliferation and induced cell apoptisis in hepatocellular carcinoma via PI3K/Akt/P53/FoxO signaling axis

BACKGROUND

There is no comprehensive treatment method for hepatocellular carcinoma (HCC); hence, research and development are still focused on systemic therapies, including drugs. Sinikangai fang (SNKAF) decoction, a classic Chinese herbal prescription, has been widely used to treat liver cancer. However, there is no research on its core active component and target.

METHODS

Mouse models were established to measure the anticancer effect of SNKAF decoction on HCC. Further, we investigated the effect of SNKAF decoction on inhibition of hepatoma cells proliferation using cell viability, cloning and invasion assays in vitro. The components of SNKAF were collected from the Traditional Chinese Medicine Systems Pharmacology (TCMSP) database and TCM@Taiwan database. Metabolomic analysis was used to identify the potential genes and pathways in HCC treated with SNKAF decoction. Then, the expression of phosphoinositide 3-kinase (PI3K), Akt, P53, FoxO proteins of the potential signal pathways were detected using Western blot.

RESULTS

The animal experiments showed that SNKAF decoction inhibited tumor growth (P < 0.05) and induced no weight loss in the mice. In vitro data showed that HCCLM3 and MHCC97H cell proliferation was inhibited by SNKAF serum in a time- and concentration dependent manner. Further combined analysis network pharmacology with metabonomics showed that 217 target genes overlapped. The core target genes included BCL2, MCL1, Myc, PTEN, gsk3b, CASP9, CREB1, MDM2, pt53 and CCND1. Cancer-associated pathways were largely involved in SNKAF mechanisms, including P53, FoxO, and PI3K/Akt signaling pathways, which are closely related to induced-tumor cell apoptosis. In addition, Western bolt verified that 10% SNKAF serum significantly affected the main proteins of PI3K/Akt/P53/FoxO signaling pathway in both cell lines.

CONCLUSION

SNKAF decoction-containing serum inhibited HCCLM3 and MHCC97H cell proliferation, migration, invasion, and induced-tumor cell apoptosis in-vivo. We confirmed that SNKAF decoction is a promising alternative treatments for HCC patients.

Bibliometric Analysis of Network Pharmacology in Traditional Chinese Medicine

Aim

We evaluated the developmental process, research status, and existing challenges of network pharmacology. Moreover, we elucidated the corresponding solutions to improve and develop network pharmacology.

Methods

Research data for the current study were retrieved from the Web of Science. The developmental process of network pharmacology was analyzed using HisCite, whereas cooccurrence analysis of countries, institutions, keywords, and references in literature was conducted using CiteSpace.

Results

In literature, there was a trend of annual increase of studies on network pharmacology and China was found to be the country with the most published literature on network pharmacology. The main publishing research institutions were universities of traditional Chinese medicine (TCM). The keywords with more research frequency were TCM, mechanisms, molecular docking, and quercetin, among others.

Conclusion

Currently, studies on network pharmacology are mainly associated with the exploration of action mechanisms of TCM. The main active ingredient in many Chinese medicines is quercetin. This ingredient may lead to deviation of research results, inability to truly analyze active ingredients, and even mislead the research direction of TCM. Such deviation may be because the database fails to reflect the content and composition changes of Chinese medicinal components. The database does not account for interactions among components, targets, and diseases, and it ignores the different pathological states of the disease. Therefore, network pharmacology should be improved from the databases and research methods.

Protective Effect of Hedyotis diffusa Willd. Ethanol Extract on Isoniazid-Induced Liver Injury in the Zebrafish Model

Objective

Methods

Results

Conclusion

A New Estimation Method for the Biological Interaction Predicting Problems

For the past decades, computational methods have been developed to predict various interactions in biological problems. Usually these methods treated the predicting problems as semi-supervised problem or positive-unlabeled(PU) learning problem. Researchers focused on the prediction of unlabeled samples and hoped to find novel interactions in the datasets they collected. However, most of the computational methods could only predict a small proportion of undiscovered interactions and the total number was unknown. In this paper, we developed an estimation method with deep learning to calculate the number of undiscovered interactions in the unlabeled samples, derived its asymptotic interval estimation, and applied it to the compound synergism dataset, drug-target interaction(DTI) dataset and MicroRNA-disease interaction dataset successfully. Moreover, this method could reveal which dataset contained more undiscovered interactions and would be a guidance for the experimental validation. Furthermore, we compared our method with some mixture proportion estimators and demonstarted the efficacy of our method. Finally, we proved that AUC and AUPR were related with the number of undiscovered interactions, which was regarded as another evaluation indicator for the computational methods.

Integrated Network Pharmacology Approach for Drug Combination Discovery: A Multi-Cancer Case Study

Despite remarkable efforts of computational and predictive pharmacology to improve therapeutic strategies for complex diseases, only in a few cases have the predictions been eventually employed in the clinics. One of the reasons behind this drawback is that current predictive approaches are based only on the integration of molecular perturbation of a certain disease with drug sensitivity signatures, neglecting intrinsic properties of the drugs. Here we integrate mechanistic and chemocentric approaches to drug repositioning by developing an innovative network pharmacology strategy. We developed a multilayer network-based computational framework integrating perturbational signatures of the disease as well as intrinsic characteristics of the drugs, such as their mechanism of action and chemical structure. We present five case studies carried out on public data from The Cancer Genome Atlas, including invasive breast cancer, colon adenocarcinoma, lung squamous cell carcinoma, hepatocellular carcinoma and prostate adenocarcinoma. Our results highlight paclitaxel as a suitable drug for combination therapy for many of the considered cancer types. In addition, several non-cancer-related genes representing unusual drug targets were identified as potential candidates for pharmacological treatment of cancer.

Calycosin alleviates H2 O2 -induced astrocyte injury by restricting oxidative stress through the Akt/Nrf2/HO-1 signaling pathway

Oxidative stress-induced brain cell damage is a crucial factor in the pathogenesis of reactive oxygen species (ROS)-associated neurological diseases. Further, studies show that astrocytes are an important immunocompetent cell in the brain and play a potentially significant role in various neurological diseases. Therefore, elimination of ROS overproduction might be a potential strategy for preventing and treating neurological diseases. Accumulating evidence indicates that calycosin, a main active ingredient in the Chinese herbal medicine Huangqi (Radix Astragali Mongolici), is a potential therapeutic candidate with anti-inflammation and/or anticancer effects. Here, we investigated the protective effect of calycosin in brain astrocytes by mimicking in vitro oxidative stress using H₂ O₂ . The results revealed that H₂ O₂ significantly induced ROS and inflammatory factor (tumor necrosis factor [TNF]-α and interleukin [IL]-1β) production, whereas post-treatment with calycosin dramatically and concentration-dependently suppressed H₂ O₂ -induced damage by enhancing cell viability, repressing ROS and inflammatory factor production, and increasing superoxide dismutase (SOD) expression. Additionally, we found that calycosin facilitated nuclear factor erythroid 2-related factor 2 (Nrf2) expression and promoted its nuclear translocation, thereby inducing the expression of antioxidant molecules (heme oxygenase [HO]-1 and SOD) following H₂ O₂ treatment. Moreover, calycosin did not attenuated H₂ O₂ -induced astrocyte damage and ROS production in the presence of the ML385 (a Nrf2-specific inhibitor) and following Nrf2 silencing. Furthermore, calycosin failed to increase Akt phosphorylation and mitigate H₂ O₂ -induced astrocyte damage in the presence of the LY294002 (a selective phosphatidylinositol 3-kinase inhibitor), indicating that calycosin-mediated regulation of oxidative-stress homeostasis involved Akt/Nrf2/HO-1 signaling. These findings demonstrated that calycosin protects against oxidative injury in brain astrocytes by regulating oxidative stress through the AKT/Nrf2/HO-1 signaling pathway.

Disclosing targets and pharmacological mechanisms of total bioflavonoids extracted from Selaginella doederleinii against non-small cell lung cancer by combination of network pharmacology and proteomics

ETHNOPHARMACOLOGICAL RELEVANCE

Previously, the total bioflavonoids extract from Selaginella doederleinii (SDTBE) presented favorable in vitro and in vivo activities against non-small cell lung cancer (NSCLC), hinting at its medicinal potential. However, up to nowadays, targets and integrative action mechanisms of SDTBE are still not very clear, which presents an obstacle to the development of herbal medicine.

AIM OF THE STUDY

The present study aimed to disclose the potential targets and integrative action mechanism of SDTBE against NSCLC.

MATERIALS AND METHODS

A system pharmacology-based strategy including target fishing, network pharmacology analysis and molecular docking were applied to predict the potential targets and pathways for the seven main active ingredients in SDTBE. A proteomics study was subsequently performed for validating the affected pathways and possible targets. Western blot assay, mouse xenograft tumor model and immunofluorescence assays were used to further confirm the key targets and integrative action mechanisms of SDTBE against NSCLC.

RESULTS

By system pharmacology, it was inferred that SDTBE could mainly act on mitogen-activated protein kinase (MAPK) and PI3K-AKT signaling pathways by targeting epidermal growth factor receptor (EGFR), protein kinase B (AKT) and mitogen-activated or extracellular signal-regulated protein kinase (MEK), which was validated by proteomics results, and further confirmed in vitro and in vivo by Western blot and immunofluorescence assays.

CONCLUSION

SDTBE targeting multi-targets including EGFR, AKT and MEK could exert its anti-NSCLC effect mainly via MAPK and PI3K-AKT signaling pathways.

Network Pharmacology-Based and Experimental Identification of the Effects of Paeoniflorin on Major Depressive Disorder

Objective: Major depressive disorder (MDD) is one of the most common psychiatric disorders, the diagnosis and treatment of MDD are major clinical issues. However, there is a lack of effective biomarkers and drugs diagnosis and therapeutics of MDD. In the present study, bioinformatics analysis combined with an experimental verification strategy was used to identify biomarkers and paeoniflorin targets for MDD diagnosis and treatment.

Methods: Based on network pharmacology, we obtained potential targets and pathways of paeoniflorin as an antidepressant through multiple databases. We then constructed a protein-protein interaction network and performed enrichment analyses. According to the results, we performed in vivo and in vitro experimental validation.

Results: The results showed that paeoniflorin may exert an antidepressant effect by regulating cell inflammation, synaptic function, NF-κB signaling pathway, and intestinal inflammation.

Conclusion: NPM1, HSPA8, HSPA5, HNRNPU, and TNF are the targets of paeoniflorin treatment. In addition, we demonstrated that paeoniflorin inhibits inflammatory cytokine production via the p38MAPK/NF-κB pathway and has neuroprotective effects on the synaptic structure. Our findings provide valuable evidence for the diagnosis and treatment of MDD.

East Asian Herbal Medicine to Reduce Primary Pain and Adverse Events in Cancer Patients : A Systematic Review and Meta-Analysis With Association Rule Mining to Identify Core Herb Combination

Objective: Cancer pain is an important factor in cancer management that affects a patient’s quality of life and survival-related outcomes. The aim of this review was to systematically evaluate the efficacy and safety of oral administration of East Asian herbal medicine (EAHM) for primary cancer pain and to explore core herb patterns based on the collected data.

Methods: A comprehensive literature search was conducted in 11 electronic databases, namely, PubMed, Cochrane Library, Cumulative Index to Nursing & Allied Health Literature, EMBASE, Korean Studies Information Service System, Research Information Service System, Oriental Medicine Advanced Searching Integrated System, Korea Citation Index, Chinese National Knowledge Infrastructure Database (CNKI), Wanfang Data, and CiNii for randomized controlled trials from their inception until August 19, 2021. Statistical analysis was performed in R version 4.1.1 and R studio program using the default settings of the meta-package. When heterogeneity in studies was detected, the cause was identified through meta-regression and subgroup analysis. Methodological quality was independently assessed using the revised tool for risk of bias in randomized trials (Rob 2.0).

Results: A total of 38 trials with 3,434 cancer pain patients met the selection criteria. Meta-analysis favored EAHM-combined conventional medicine on response rate (risk ratio: 1.06; 95% CI: 1.04 to 1.09, p < 0.0001), continuous pain intensity (standardized mean difference: −1.74; 95% CI: −2.17 to −1.30, p < 0.0001), duration of pain relief (standardized mean difference: 0.96, 95% CI: 0.69 to 1.22, p < 0.0001), performance status (weighted mean difference: 10.71; 95% CI: 4.89 to 16.53, p = 0.0003), and opioid usage (weighted mean difference: −20.66 mg/day; 95% CI: −30.22 to −11.10, p < 0.0001). No significant difference was observed between EAHM and conventional medicine on response rate and other outcomes. Patients treated with EAHM had significantly reduced adverse event (AE) incidence rates. In addition, based on the ingredients of herb data in this meta-analysis, four combinations of herb pairs, which were frequently used together for cancer pain, were derived.

Conclusion: EAHM monotherapy can decrease adverse events associated with pain management in cancer patients. Additionally, EAHM-combined conventional medicine therapy may be beneficial for patients with cancer pain in increasing the response rate, relieving pain intensity, improving pain-related performance status, and regulating opioid usage. However, the efficacy and safety of EAHM monotherapy are difficult to conclude due to the lack of methodological quality and quantity of studies. More well-designed, multicenter, double-blind, and placebo-controlled randomized clinical trials are needed in the future. In terms of the core herb combination patterns derived from the present review, four combinations of herb pairs might be promising for cancer pain because they have been often distinctly used for cancer patients in East Asia. Thus, they are considered to be worth a follow-up study to elucidate their actions and effects.

Systematic Review Registration:https://www.crd.york.ac.uk/prospero/, identifier CRD42021265804

Network pharmacology and in vitro studies reveal the pharmacological effects and molecular mechanisms of Shenzhi Jiannao prescription against vascular dementia

Background

Shenzhi Jiannao (SZJN) prescription is a type of herbal formula adopted in the management of cognitive impairment and related disorders. However, its effects and related regulatory mechanisms on vascular dementia (VD) are elusive. Herein, network pharmacology prediction was employed to explore the pharmacological effects and molecular mechanisms of SZJN prescription on VD using network pharmacology prediction, and validated the results through in vitro experiments.

Methods

Through a search in the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) database, chemical composition and targets for SZJN prescription were retrieved. The potential targets for VD were then obtained from the GeneCards and DisGeNET databases. The network was constructed that depicted the interactions between putative SZJN prescription and known therapeutic targets for VD using Cytoscape 3.7.1. Analysis of protein-protein interaction was achieved via STRING 11.0 software, followed by Gene Ontology (GO) functional enrichment and Kyoto Gene and Genome Encyclopedia (KEGG) pathway analyses. To validate the computer-predicted results, in vitro experiments based on an excitotoxic injury model were designed using glutamate-exposed PC12 cells, and treated with varying concentrations (low, 0.05; medium, 0.1 and high, 0.2 mg/mL) of SZJN prescription. Cell viability and cell death were detected using the IncuCyte imaging system. Moreover, the expression profiles of Caspase-3 were analyzed through qRT-PCR.

Results

Twenty-eight potentially active ingredients for SZJN prescription, including stigmasterol, beta-sitosterol, and kaempferol, plus 21 therapeutic targets for VD, including PTGS2, PTGS1, and PGR were revealed. The protein-protein interaction network was employed for the analysis of 20 target proteins, including CASP3, JUN, and AChE. The enrichment analysis demonstrated candidate targets of SZJN prescription were more frequently involved in neuroactive ligand-receptor interaction, calcium, apoptosis, and cholinergic synaptic signaling pathways. In vitro experiments revealed that SZJN prescription could significantly reverse glutamate-induced cell viability loss and cell death, and lower the levels of Caspase-3 mRNA in glutamate-induced PC12 cells.

Conclusions

Collectively, this study demonstrated that SZJN prescription exerted the effect of treating VD by regulating multi-targets and multi-channels with multi-components through the method of network pharmacology. Furthermore, in vitro results confirmed that SZJN prescription attenuated glutamate-induced neurotoxicity.

Network pharmacology-based strategy to investigate the active ingredients and molecular mechanisms of Scutellaria Barbata D. Don against radiation pneumonitis

INTRODUCTION

Herbal medicines combined with radiotherapy significantly reduced the incidence of radiation pneumonitis (RP), and the Scutellaria barbata D. Don (SBD) is a perennial herb that has been reported to protect against radiation-induced pneumonitis. However, the exact molecular mechanism is not known. The objective of this research was to investigate the against radiation pneumonitis ingredients and their functional mechanisms in SBD.

METHODS

Based on the network pharmacology approaches, we collected active ingredients and target genes in SBD against RP through Traditional Chinese Medicine System Pharmacology (TCMSP) Database, and the "Herb-Ingredients-Target Genes-Disease" Network was constructed by using of Cytoscape. STRING analysis was performed to reveal the protein-protein interactions, and then we applied enrichment analysis on these target proteins, gene function, and pathways.

RESULTS

A total of 18 ingredients in SBD regulate 65 RP related target proteins, which show that quercetin, luteolin, baicalein, wogonin may be the key active ingredients, while IL6, AKT1, VEGFA, MMP9, CCL2, prostaglandin-endoperoxide synthase 2 (PTGS2) (cyclooxygenase-2 [COX-2]), CXCL8, IL1B, mitogen-activated protein kinase (MAPK1), and IL10 were identified as critical targets. Besides, the results of Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis indicated that predicted targets of SBD are mostly associated with the pathological process of oxidative stress and inflammation. AGE- Receptor of Advanced Glycation Endproducts (RAGE) signaling pathway in diabetic complications, IL-17 signaling pathway, hypoxia-inducible factor-1 (HIF-1) signaling pathway, NF-kappa B signaling pathway might serve as the principal pathways for RP treatment.

CONCLUSION

In our study, the pharmacological and molecular mechanism of SBD against RP was predicted from a holistic perspective, and the results provided theoretical guidance for researchers to explore the mechanism in further research.