HIT 2.0: an enhanced platform for Herbal Ingredients' Targets

Exploring the Mechanism of Zilongjin in Treating Lung Adenocarcinoma Based on Network Pharmacology Combined with Experimental Verification

Zilongjin (ZLJ) is a common traditional Chinese medicine for lung adenocarcinoma (LUAD) treatment. However, its mechanisms of action remain to be elucidated. Network pharmacology was used to explore the underlying mechanisms of ZLJ on LUAD treatment. The disease-related targets were determined from the Gene-Cards and DisGeNET databases. Active compounds and targets of ZLJ were obtained from the HIT, TCMSP, and TCMID databases. Then the protein-protein interaction (PPI) network was built by the STRING database to identify core-hub targets of ZLJ in LUAD. Next, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were employed to analyze the enriched regulatory pathways of targets. Molecular docking analysis was used to evaluate interactions between potential targets and active compounds. Finally, qRT-PCR was used to further verify the results of network pharmacology. A total of 124 LUAD-related targets of ZLJ and 5 active compounds of ZLJ from the relevant databases were screened out. Among these target proteins, JUN, CDH1, PPARG, and FOS were core hub-genes in the PPI network. GO and KEGG pathway enrichment analysis indicated that these targets might regulate the PPAR signaling pathway in LUAD. JUN, PPARG, and FOS levels were upregulated, while CDH1 level was downregulated in LUAD cells. This study discerned that ZLJ may target genes such as JUN, FOS, PPARG, and CDH1 via the PPAR signaling pathway in LUAD, offering foundational insights for further exploration of ZLJ in clinical applications.

The Potential Mechanisms of Qufeng Zhitong Capsule against Rheumatoid Arthritis Based on Network Pharmacology and In Vitro Experiments

Qufeng Zhitong capsule (QFZTC) is a traditional Chinese herbal formula with potential therapeutic efficacy in rheumatoid arthritis (RA). This study seeks to clarify the potential effects and mechanisms of QFZTC against RA. Active compounds and targets of QFZTC were retrieved from the Herbal Ingredients' Targets (HIT), Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP), and Traditional Chinese Medicine Integrated Database (TCMID) databases. RA-related targets were searched on GeneCards and DisGeNET databases. Protein-protein interaction (PPI) network was established using the STRING database. Gene ontology (GO) and Kyoto Encyclopedia of Gene and Genome (KEGG) enrichment analyses were performed on hub targets. Molecular docking was conducted on hub targets and active compounds. High-performance liquid chromatography (HPLC) was applied to characterize the active compounds in QFZTC. RA-fibroblast like synoviocytes (RA-FLSs) were cultured and treated by QFZTC-containing serum, in which proinflammatory cytokines and hub targets were detected. Cell viability was determined by cell counting kit-8 (CCK-8) assay. A total of 360 active compounds and 445 potential targets are identified for QFZTC against RA. Protein-protein interaction (PPI) network determined five hub targets, interleukin 6 (IL6), IL1B, VEGFA, JUN, and tumor necrosis factor (TNF). GO and KEGG analyses revealed that the MAPK pathway may be a critical signaling in QFZTC treating RA. Molecular docking showed that luteolin, kaempferol, and myricetin has good affinity with TNF, and they were identified by HPLC. In vitro experiments confirmed that QFZTC restrained the cell viability and inflammation in RA. This study revealed the active compounds and molecular targets for QFZTC treating RA. QFZTC is a promising drug and ameliorates RA by inhibiting inflammatory response.

Integrating network pharmacology and Mendelian randomization to explore potential targets of matrine against ovarian cancer

BACKGROUND

Matrine has been reported inhibitory effects on ovarian cancer (OC) cell progression, development, and apoptosis. However, the molecular targets of matrine against OC and the underlying mechanisms of action remain elusive.

OBJECTIVE

This study endeavors to unveil the potential targets of matrine against OC and to explore the intricate relationships between these targets and the pathogenesis of OC.

METHODS

The effects of matrine on the OC cells (A2780 and AKOV3) viability, apoptosis, migration, and invasion was investigated through CCK-8, flow cytometry, wound healing, and Transwell analyses, respectively. Next, Matrine-related targets, OC-related genes, and ribonucleic acid (RNA) sequence data were harnessed from publicly available databases. Differentially expressed analyses, protein-protein interaction (PPI) network, and Venn diagram were involved to unravel the core targets of matrine against OC. Leveraging the GEPIA database, we further validated the expression levels of these core targets between OC cases and controls. Mendelian randomization (MR) study was implemented to delve into potential causal associations between core targets and OC. The AutoDock software was used for molecular docking, and its results were further validated using RT-qPCR in OC cell lines.

RESULTS

Matrine reduced the cell viability, migration, invasion and increased the cell apoptosis of A2780 and AKOV3 cells (P< 0.01). A PPI network with 578 interactions among 105 candidate targets was developed. Finally, six core targets (TP53, CCND1, STAT3, LI1B, VEGFA, and CCL2) were derived, among which five core targets (TP53, CCND1, LI1B, VEGFA, and CCL2) differential expressed in OC and control samples were further picked for MR analysis. The results revealed that CCND1 and TP53 were risk factors for OC. Molecular docking analysis demonstrated that matrine had good potential to bind to TP53, CCND1, and IL1B. Moreover, matrine reduced the expression of CCND1 and IL1B while elevating P53 expression in OC cell lines.

CONCLUSIONS

We identified six matrine-related targets against OC, offering novel insights into the molecular mechanisms underlying the therapeutic effects of matrine against OC. These findings provide valuable guidance for developing more efficient and targeted therapeutic approaches for treating OC.

Molecular Mechanisms of Medicinal Plant Securinega suffruticosa-derived Compound Securinine against Spinal Muscular Atrophy based on Network Pharmacology and Experimental Verification

BACKGROUND

Spinal Muscular Atrophy (SMA) is a severe motor neuronal disorder with high morbidity and mortality. Securinine has shown the potential to treat SMA; however, its anti-SMA role remains unclear.

OBJECTIVE

This study aims to reveal the anti-SMA mechanisms of securinine.

METHODS

Securinine-associated targets were acquired from Herbal Ingredients' Targets (HIT), Similarity Ensemble Approach (SEA), and SuperPred. SMA-associated targets were obtained from GeneCards and Dis- GeNET. Protein-protein Interaction (PPI) network was constructed using GeneMANIA, and hug targets were screened using cytoHubba. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed using ClusterProfifiler. Molecular docking was conducted using Pymol and Auto- Dock. In vitro assays were used to verify the anti-SMA effects of securinine.

RESULTS

Twenty-six intersection targets of securinine and SMA were obtained. HDAC1, HDAC2, TOP2A, PIK3R1, PRMT5, JAK2, HSP90AB1, TERT, PTGS2, and PAX8 were the core targets in PPI network. GO analysis demonstrated that the intersecting targets were implicated in the regulation of proteins, steroid hormones, histone deacetylases, and DNA transcription. KEGG analysis, pathway-pathway, and hub target-pathway networks revealed that securinine might treat SMA through TNF, JAK-STAT, Ras, and PI3K-Akt pathways. Securinine had a favorable binding affinity with HDAC1, HSP90AB, JAK2, PRMT5, PTGS2, and TERT. Securinine rescued viability suppression, mitochondria damage, and SMN loss in the SMA cell model. Furthermore, securinine increased HDAC1 and PRMT5 expression, decreased PTGS2 expression, suppressed the JAK2-STAT3 pathway, and promoted the PI3K-Akt pathway.

CONCLUSION

Securinine might alleviate SMA by elevating HDAC1 and PRMT5 expression and reducing PTGS2 via JAK2-STAT3 suppression and PI3K-Akt activation.

Mechanism Study of Polydatin in Treating Spinal Cord Injury by Modulating Mitochondrial Membrane Potential Based on Network Pharmacology and Molecular Docking

Spinal cord injury (SCI) is one of the most devastating central lesions, and mitochondrial function plays an important role in secondary injury after SCI. Polydatin (PD) is a natural glycosylated precursor of resveratrol, showing mitochondrial preservation effects in the central nervous system. This study aimed to identify the hub target genes of PD on mitochondrial membrane potential (MMP) in SCI. A comprehensive analysis was performed on SCI-related genes, MMP-related genes, and PD targets screening from public databases. Differential expression analysis was conducted to identify differentially expressed genes (DEGs) in SCI. Gene set enrichment analysis (GSEA) and gene set variation analysis (GSVA) were employed to assess pathway enrichment. Protein-protein interaction (PPI) network analysis and molecular docking were conducted to identify key genes and evaluate the binding affinity between PD and hub genes. A total of 16,958 SCI-related genes, 2,786 MMP-related genes, 318 PD-related target genes, and 7229 DEGs were identified. Intersection analysis revealed 46 genes common to all four categories. GSEA and GSVA analysis identified significant enrichment of pathways associated with suppressed and activated SCI biological processes. The PPI network analysis identified seven core hub genes: EGFR, SRC, VEGFA, STAT3, ERBB2, TP53, and RHOA. Molecular docking revealed strong binding affinities between PD and ERBB2, EGFR, and RHOA. The findings based on computational investigation from public databases suggest that PD may have therapeutic potential for SCI by modulating MMP. These results contribute to the understanding of SCI pathogenesis and the development of novel therapeutic strategies.

Compound-composed Chinese medicine of Huachansu triggers apoptosis of gastric cancer cells through increase of reactive oxygen species levels and suppression of proteasome activities

BACKGROUND

Huachansu (HCS), a known Chinese patent drug extracted from the Chinese toad skin, is frequently used for the treatment of various advanced cancers, especially gastric cancer, due to the good therapeutic effect. However, it is rather difficult to clarify the active substances and molecular mechanisms involved owing to the lack of appropriate research strategies. We recently proposed the concept and research ideas of compound-composed Chinese medicine formula.

PURPOSE

To discover compound-composed Chinese medicine from Huachansu and to explore its mechanism of action in inducing apoptosis of gastric cancer cells.

METHOD

Network pharmacology combined with serum pharmacochemistry was utilized to screen the predominant active constituents from HCS against gastric cancer. Then, the compound-composed Chinese medicine of HCS (CCMH) was prepared according to their relative contents in serum. The pharmacological effects and potential mechanisms for CCMH were investigated by assays for cell viability, cell cycle, apoptosis, mitochondrial membrane potential (MMP), proteomics, reactive oxygen species (ROS), N-Acetylcysteine (NAC) antagonism, proteasome activity, and western blot.

RESULTS

CCMH was comprised of arenobufagin (11.14%), bufalin (18.67%), bufotalin (7.33%), cinobufagin (16.67%), cinobufotalin (16.74%), gamabufotalin (8.45%), resibufogenin (12.03%), and telocinobufagin (8.97%). CCMH evidently induced proliferation inhibition, cell cycle arrest, apoptosis, and MMP collapse in gastric cancer cells, possessing the better activities than HCS. Proteomic analysis showed that CCMH influenced ROS pathway, ubiquitin proteasome system, and PI3K/Akt and MAPK signaling pathways. CCMH markedly enhanced intracellular ROS levels in gastric cancer cells, which was reversed by NAC. Accordingly, NAC antagonized the apoptosis-inducing effect of CCMH. Significantly decreased proteasome 20S activity by CCMH was observed in gastric cancer cells. CCMH also regulated the expression of key proteins in PI3K/Akt and MAPK signaling pathways.

CONCLUSION

CCMH possesses more significant apoptotic induction effects on gastric cancer cells than HCS, which is achieved primarily through suppression of proteasome activities and increase of ROS levels, followed by regulating PI3K/Akt and MAPK signaling pathways. Network pharmacology combined with serum pharmacochemistry is an effective strategy for discovering compound-composed Chinese medicine from traditional Chinese medicine, which can help clarify the pharmacological substances and mechanisms of action for traditional Chinese medicine.

Network Proximity Analysis Deciphers the Pharmacological Mechanism of Osthole against D-Galactose Induced Cognitive Disorder in Rats

Osthole, a natural coumarin found in various medicinal plants, has been previously reported to have neuroprotective effects. However, the specific mechanism by which Osthole alleviates dysmnesia associated with Alzheimer's disease (AD) remains unclear. This study aimed to investigate the neuroprotective properties of Osthole against cognitive impairment in rats induced by D-galactose and elucidate its pharmacological mechanism. The rat model was established by subcutaneously injecting D-galactose at a dose of 150 mg/kg/day for 56 days. The effect of Osthole on cognitive impairment was evaluated by behavior and biochemical analysis. Subsequently, a combination of in silico prediction and experimental validation was performed to verify the network-based predictions, using western blot, Nissl staining, and immunofluorescence. The results demonstrate that Osthole could improve memory dysfunction induced by D-galactose in Sprague Dawley male rats. A network proximity-based approach and integrated pathways analysis highlight two key AD-related pathological processes that may be regulated by Osthole, including neuronal apoptosis, i.e., neuroinflammation. Among them, the pro-apoptotic markers (Bax), anti-apoptotic protein (Bcl-2), the microgliosis (Iba-1), Astro-cytosis (GFAP), and inflammatory cytokines (TNF-R1) were evaluated in both hippocampus and cortex. The results indicated that Osthole significantly ameliorated neuronal apoptosis and neuroinflammation in D-galactose-induced cognitive impairment rats. In conclusion, this study sheds light on the pharmacological mechanism of Osthole in mitigating D-galactose-induced memory impairment and identifies Osthole as a potential drug candidate for AD treatment, targeting multiple signaling pathways through network proximity and integrated pathways analysis.

Identifying the natural products in the treatment of atherosclerosis by increasing HDL-C level based on bioinformatics analysis, molecular docking, and in vitro experiment

BACKGROUND

Previous studies have demonstrated that high-density lipoprotein cholesterol (HDL-C) plays an anti-atherosclerosis role through reverse cholesterol transport. Several studies have validated the efficacy and safety of natural products in treating atherosclerosis (AS). However, the study of raising HDL-C levels through natural products to treat AS still needs to be explored.

METHODS

The gene sets associated with AS were collected and identified by differential gene analysis and database query. By constructing a protein-protein interaction (PPI) network, the core submodules in the network are screened out. At the same time, by calculating node importance (Nim) in the PPI network of AS disease and combining it with Kyoto Encyclopedia of genes and genomes (KEGG) pathways enrichment analysis, the key target proteins of AS were obtained. Molecular docking is used to screen out small natural drug molecules with potential therapeutic effects. By constructing an in vitro foam cell model, the effects of small molecules on lipid metabolism and key target expression of foam cells were investigated.

RESULTS

By differential gene analysis, 451 differential genes were obtained, and a total of 313 disease genes were obtained from 6 kind of databases, then 758 AS-related genes were obtained. The enrichment analysis of the KEGG pathway showed that the enhancement of HDL-C level against AS was related to Lipid and atherosclerosis, Cholesterol metabolism, Fluid shear stress and atherosclerosis, PPAR signaling pathway, and other pathways. Then we intersected 31 genes in the core module of the PPI network, the top 30 genes in Nims, and 32 genes in the cholesterol metabolism pathway, and finally found 3 genes. After the above analysis and literature collection, we focused on the following three related gene targets: APOA1, LIPC, and CETP. Molecular docking showed that Genistein has a good binding affinity for APOA1, CETP, and LIPC. In vitro, experiments showed that Genistein can up-regulated APOA1, LIPC, and CETP levels.

CONCLUSIONS

Based on our research, Genistein may have the effects of regulating HDL-C and anti-atherosclerosis. Its mechanism of action may be related to the regulation of LIPC, CETP, and APOA1 to improve lipid metabolism.

Unveiling the mechanisms of nephrotoxicity caused by nephrotoxic compounds using toxicological network analysis

Billions of people worldwide have experienced irreversible kidney injuries, which is mainly attributed to the complexity of drug-induced nephrotoxicity. Consequently, there is an urgent need for uncovering the mechanisms of nephrotoxicity caused by compounds. In the present study, a network-based methodology was applied to explore the mechanisms of nephrotoxicity induced by specific compounds. Initially, a total of 42 nephrotoxic compounds and 60 kinds of syndromes associated with nephrotoxicity were collected from public resources. Afterward, network localization and separation algorithms were used to map the targets of compounds and diseases into the human interactome. By doing so, 199 statistically significant nephrotoxic networks displaying the interaction between compound targets and disease genes were obtained, which played pivotal roles in compounds-induced nephrotoxicity. Subsequently, enrichment analysis pinpointed core Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathways that highlight commonalities in nephrotoxicity induced by nephrotoxic compounds. It was found that nephrotoxic compounds primarily induce nephrotoxicity by mediating the advanced glycosylation end products-receptor for advanced glycosylation end products signaling pathway in diabetic complications, human cytomegalovirus infection, lipid and atherosclerosis, Kaposi sarcoma-associated herpesvirus infection, apoptosis, and the phosphatidylinositol 3-kinase-Akt pathways. These results provide valuable insights for preventing drug-induced nephrotoxicity. Furthermore, the approaches we used are also helpful in conducting research on other kinds of toxicities.

ccTCM: A quantitative component and compound platform for promoting the research of traditional Chinese medicine

Traditional Chinese medicine (TCM) databases play a vital role in bridging the gap between TCM and modern medicine, as well as in promoting the popularity of TCM. Elucidating the bioactive ingredients of Chinese medicinal materials is key to TCM modernization and new drug discovery. However, one drawback of current TCM databases is the lack of quantitative data on the constituents of Chinese medicinal materials. Herein, we present ccTCM, a web-based platform designed to provide a component and compound-content-based resource on TCM and analysis services for medical experts. In terms of design features, ccTCM combines resource distribution, similarity analysis, and molecular-mechanism analysis to accelerate the discovery of bioactive ingredients in TCM. ccTCM contains 273 Chinese medicinal materials commonly used in clinical settings, covering 29 functional classifications. By searching and comparing, we finally adopted 2043 studies, from which we collected the compounds contained in each TCM with content greater than 0.001 %, and a total of 1449 were extracted. Subsequently, we collected 40,767 compound-target pairs by integrating multiple databases. Taken together, ccTCM is a versatile platform that can be used by TCM scientists to perform scientific and clinical TCM studies based on quantified ingredients of Chinese medicinal materials. ccTCM is freely accessible at http://www.cctcm.org.cn.

Multi-level advances in databases related to systems pharmacology in traditional Chinese medicine: a 60-year review

The therapeutic effects of traditional Chinese medicine (TCM) involve intricate interactions among multiple components and targets. Currently, computational approaches play a pivotal role in simulating various pharmacological processes of TCM. The application of network analysis in TCM research has provided an effective means to explain the pharmacological mechanisms underlying the actions of herbs or formulas through the lens of biological network analysis. Along with the advances of network analysis, computational science has coalesced around the core chain of TCM research: formula-herb-component-target-phenotype-ZHENG, facilitating the accumulation and organization of the extensive TCM-related data and the establishment of relevant databases. Nonetheless, recent years have witnessed a tendency toward homogeneity in the development and application of these databases. Advancements in computational technologies, including deep learning and foundation model, have propelled the exploration and modeling of intricate systems into a new phase, potentially heralding a new era. This review aims to delves into the progress made in databases related to six key entities: formula, herb, component, target, phenotype, and ZHENG. Systematically discussions on the commonalities and disparities among various database types were presented. In addition, the review raised the issue of research bottleneck in TCM computational pharmacology and envisions the forthcoming directions of computational research within the realm of TCM.

Network pharmacology combined with molecular docking and experimental verification to elucidate functional mechanism of Fufang Zhenzhu Tiaozhi against type 2 diabetes mellitus

Fufang Zhenzhu Tiaozhi (FTZ) capsules have been prescribed for treating glucose and lipid metabolism disorders such as type 2 diabetes mellitus (T2DM). However, the underlying mechanism remains unknown. In this study, network pharmacology and experimental verification were combined to investigate the mechanisms of FTZ in treating T2DM. A total of 176 active ingredients and 1169 corresponding targets were screened using biological databases. 598 potential targets of T2DM were retrieved from GeneCards, PharmGKB, OMIM, Drugbank, and TTD. The Venn diagram was employed to identify the 194 intersection targets, which were employed to construct the "Herb-Compound-Target" interacting networks. These common targets were also used to prepare a protein-protein interaction (PPI) network to uncover potential targets. The four core targets were docked to their corresponding targets for binding analysis. Additionally, the top-ranked poses of ingredients and the positive compounds from each protein were evaluated for stability using molecular dynamics. Our results suggest that core active ingredients such as kaempferol, luteolin, and baicalein have high binding affinity and stability with AKT1, PTGS2 (also known as COX-2), DPP4, and PAPRG. GO and KEGG analyses indicated that the treatment T2DM by FTZ might be related to different pathway like AMPK and EGFR pathways. The experimental validation results proved that kaempferol, luteolin, and baicalein could significantly inhibit the activity of DPP4 and COX-2, kaempferol and luteolin were also able to activate AKT and AMPK signaling pathway. This study further validated previous findings and enhanced our understanding of the potential effects of FTZ on T2DM.Communicated by Ramaswamy H. Sarma.

Network medicine framework reveals generic herb-symptom effectiveness of traditional Chinese medicine

Understanding natural and traditional medicine can lead to world-changing drug discoveries. Despite the therapeutic effectiveness of individual herbs, traditional Chinese medicine (TCM) lacks a scientific foundation and is often considered a myth. In this study, we establish a network medicine framework and reveal the general TCM treatment principle as the topological relationship between disease symptoms and TCM herb targets on the human protein interactome. We find that proteins associated with a symptom form a network module, and the network proximity of an herb's targets to a symptom module is predictive of the herb's effectiveness in treating the symptom. These findings are validated using patient data from a hospital. We highlight the translational value of our framework by predicting herb-symptom treatments with therapeutic potential. Our network medicine framework reveals the scientific foundation of TCM and establishes a paradigm for understanding the molecular basis of natural medicine and predicting disease treatments.

Effect of Shan Zha (Hawthorn or Crataegus) on gastrointestinal cancer: A network pharmacology and molecular docking study

Background

Shan Zha (Hawthorn or Crataegus) is a traditional Chinese medicine (TCM) most commonly used for the treatment of hyperlipidemia. Gastrointestinal cancer is closely correlated with blood lipid levels. This study illustrates the potential anticancer effects of Shan Zha on gastrointestinal tumors based on network pharmacology and molecular docking.

Methods

Hawthorn's bioactive ingredients and drug targets were obtained from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP), Integrative Pharmacology-based Research Platform of Traditional Chinese Medicine version 2.0 (TCMIP v2.0), and Herbal Ingredients' Targets Platform (HIT 2.0) databases. Validated disease targets of gastrointestinal cancer were obtained from the Therapeutic Targets Database (TTD) and HIT 2.0 databases. Protein-protein interaction analysis of intersecting genes was performed using the Search Tool for the Retrieval of Interacting Genes (STRING) database. The functions of these genes were further analyzed by performing gene ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. Molecular docking verification was performed using Molecular Operating Environment (MOE) software.

Results

Four main bioactive components were identified in Shan Zha. A total of 271 potential drug targets were identified, and 393 gastrointestinal-tumor targets were obtained. Through protein interaction analysis of intersecting targets, the main components of Shan Zha were found to interact more closely with proteins such as tumor protein p53 (TP53), AKT serine/threonine kinase 1 (AKT1), JUN proto-oncogene (JUN), interleukin 6 (IL6), epidermal growth factor receptor (EGFR), and vascular endothelial growth factor A (VEGFA). KEGG pathway enrichment analysis showed a total of 127 pathways, mainly involving pathways in multiple types of cancer, the Phosphatidylinositol 3-kinase-Akt (PI3K-Akt) signaling pathway, and EGFR tyrosine kinase inhibitor resistance. Combined with The Cancer Genome Atlas (TCGA) differential analysis, key targets, including TP53, cyclin D1 (CCND1), EGFR, and VEGFA, were screened. Molecular docking results showed that quercetin and kaempferol had the good binding potential for TP53, CCND1, EGFR, and VEGFA.

Conclusion

These findings suggest that Shan Zha exerts its effects on gastrointestinal cancers through a multitarget, multi-component, and a multi-pathway mechanism.

Integrated network pharmacology, bioinformatics, and molecular docking to explore the mechanisms of berberine regulating autophagy in breast cancer

Berberine exhibits anticancer efficacy against a variety of malignancies, including breast cancer (BRCA). However, the underlying mechanism is ambiguous. This study sought to explore the targets and the probable mechanism of berberine regulating autophagy in BRCA through network pharmacology, bioinformatics, and molecular docking. The targets of berberine and autophagy-modulated genes were derived from online databases, and the Cancer Genome Atlas database was used to identify the differentially expressed genes of BRCA. Then, through intersections, the autophagy-modulated genes regulated by berberine (AMGRBs) in BRCA were obtained. Next, we established a protein-protein interaction network using the Search Tool for the Retrieval of Interacting Genes database. Afterward, gene ontology and Kyoto encyclopedia of genes and genomes enrichment analyses were employed to explore the targets' biological functions. Additionally, molecular docking was conducted to verify the binding ability of berberine to the targets. Finally, to determine the prognostic value of AMGRBs in BRCA, we performed overall survival analyses. We identified 29 AMGRBs in BRCA, including CASP3, MTOR, AKT1, GSK3B, PIK3CA, and others. Gene ontology enrichment analysis showed that the AMGRBs in BRCA were associated with autophagy regulation, negative regulation of catabolic process, macroautophagy, and other biological processes. Kyoto encyclopedia of genes and genomes enrichment analyses indicated that AMGRBs in BRCA were involved in epidermal growth factor receptor tyrosine kinase inhibitor resistance, PI3K/Akt signaling pathway, JAK-STAT signaling pathway, and others. Molecular docking results proved that berberine had strong binding affinities with AMGRBs in BRCA. Survival analyses indicated that ATM, HTR2B, LRRK2, PIK3CA, CDK5, and IFNG were associated with the prognosis of BRCA. This study identified the targets and pathways of berberine for regulating autophagy in BRCA, which contributed to a better understanding of berberine's function in BRCA and serve as a foundation and reference for further study and therapeutic application of berberine.

Integrating animal experiments, mass spectrometry and network-based approach to reveal the sleep-improving effects of Ziziphi Spinosae Semen and γ-aminobutyric acid mixture

BACKGROUND

Ziziphi Spinosae Semen (ZSS) is a plant widely used as medicine and food in Asian countries due to its numerous health benefits. γ-aminobutyric acid (GABA), a non-proteinaceous amino acid, is one of the major inhibitory neurotransmitters with a relaxant function. In this study, a system pharmacology approach was employed to assess the effects of a mixture composed of ZSS and GABA (ZSSG) on sleep improvement.

METHODS

Mice were divided into five groups (n = 10) and received either no treatment, sodium pentobarbital, or sodium barbital with diazepam or ZSSG. The effects of ZSSG on sleep quality were evaluated in mice, and differential metabolites associated with sleep were identified among the control, ZSS, GABA, and ZSSG groups. Additionally, network-based ingredient-insomnia proximity analysis was applied to explore the major ingredients.

RESULTS

ZSSG significantly improved sleep quality by decreasing sleep latency and prolonging sleep duration in sodium pentobarbital-induced sleeping mouse model (P < 0.05). ZSSG significantly enhanced the brain content of GABA in mice. Furthermore, ZSSG also significantly decreased sleep latency-induced by sodium barbital in mice (P < 0.05). Metabolic analysis revealed significant differences in 10 metabolites between ZSSG group and the groups administering ZSS or GABA. Lastly, using the network-based ingredient screening model, we discovered potential four active ingredients and three pairwise ingredient combinations with synergistic effect on insomnia from ZSSG among 85 ingredients identified by UPLC-Q/TOF-MS. Also, we have constructed an online computation platform.

CONCLUSION

Our data demonstrated that ZSSG improved the sleeping quality of mice and helped to balance metabolic disorders-associated with sleep disorders. Moreover, based on the network-based prediction method, the four potential active ingredients in ZSSG could serve as quality markers-associated with insomnia. The network-based framework may open up a new avenue for the discovery of active ingredients of herbal medicine for treating complex chronic diseases or symptoms, such as insomnia.

Identifying target organ location of Radix Achyranthis Bidentatae: a bioinformatics approach on active compounds and genes

Background: Herbal medicines traditionally target organs for treatment based on medicinal properties, and this theory is widely used for prescriptions. However, the scientific evidence explaining how herbs act on specific organs by biological methods has been still limited. This study used bioinformatic tools to identify the target organ locations of Radix Achyranthis Bidentatae (RAB), a blood-activating herb that nourishes the liver and kidney, strengthens bones, and directs prescription to the lower body. Methods: RAB's active compounds and targets were collected and predicted using databases such as TCMSP, HIT2.0, and BATMAN-TCM. Next, the RAB's target list was analyzed based on two approaches to obtain target organ locations. DAVID and Gene ORGANizer enrichment-based approaches were used to enrich an entire gene list, and the BioGPS and HPA gene expression-based approaches were used to analyze the expression of core genes. Results: RAB's targets were found to be involved in whole blood, blood components, and lymphatic organs across all four tools. Each tool indicated a particular aspect of RAB's target organ locations: DAVID-enriched genes showed a predominance in blood, liver, and kidneys; Gene ORGANizer showed the effect on low body parts as well as bones and joints; BioGPS and HPA showed high gene expression in bone marrow, lymphoid tissue, and smooth muscle. Conclusion: Our bioinformatics-based target organ location prediction can serve as a modern interpretation tool for the target organ location theory of traditional medicine. Future studies should predict therapeutic target organ locations in complex prescriptions rather than single herbs and conduct experiments to verify predictions.

Comprehensive survey of target prediction web servers for Traditional Chinese Medicine

Traditional Chinese medicine (TCM) is characterized by multi-components, multiple targets, and complex mechanisms of action and therefore has significant advantages in treating diseases. However, the clinical application of TCM prescriptions is limited due to the difficulty in elucidating the effective substances and the lack of current scientific evidence on the mechanisms of action. In recent years, the development of network pharmacology based on drug systems research has provided a new approach for understanding the complex systems represented by TCM. The determination of drug targets is the core of TCM network pharmacology research. Over the past years, many web tools for drug targets with various features have been developed to facilitate target prediction, significantly promoting drug discovery. Therefore, this review introduces the widely used web tools for compound-target interaction prediction databases and web resources in TCM pharmacology research, and it compares and analyzes each web tool based on their basic properties, including the underlying theory, algorithms, datasets, and search results. Finally, we present the remaining challenges for the promising future of compound-target interaction prediction in TCM pharmacology research. This work may guide researchers in choosing web tools for target prediction and may also help develop more TCM tools based on these existing resources.

Systems pharmacology-based mechanism exploration of Acanthopanax senticosusin for Alzheimer's disease using UPLC-Q-TOF-MS, network analysis, and experimental validation

BACKGROUND

Alzheimer's disease (AD) is a neurodegenerative disease, characterized by progressive cognitive dysfunction and memory loss. However, the disease-modifying treatments for AD are still lacking. Traditional Chinese herbs, have shown their potentials as novel treatments for complex diseases, such as AD.

PURPOSE

This study was aimed at investigating the mechanism of action (MOA) of Acanthopanax senticosusin (AS) for treatment of AD.

METHODS

In this study, we firstly identified the chemical constituents in Acanthopanax senticosusin (AS) utilizing ultra-high performance liquid chromatography coupled with Q-TOF-mass spectrometry (UPLC-Q-TOF-MS), and next built the drug-target network of these compounds. We next performed the systems pharmacology-based analysis to preliminary explore the MOA of AS against AD. Moreover, we applied the network proximity approach to identify the potential anti-AD components in AS. Finally, experimental validations, including animal behavior test, ELISA and TUNEL staining, were conducted to verify our systems pharmacology-based analysis.

RESULTS

60 chemical constituents in AS were identified via the UPLC-Q-TOF-MS approach. The systems pharmacology-based analysis indicated that AS might exert its therapeutic effects on AD via acetylcholinesterase and apoptosis signaling pathway. To explore the material basis of AS against AD, we further identified 15 potential anti-AD components in AS. Consistently, in vivo experiments demonstrated that AS could protect cholinergic nervous system damage and decrease neuronal apoptosis caused by scopolamine.

CONCLUSION

Overall, this study applied systems pharmacology approach, via UPLC-Q-TOF-MS, network analysis, and experimental validation to decipher the potential molecular mechanism of AS against AD.

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.

Discovering Potential Anti-Oral Squamous Cell Carcinoma Mechanisms from Kochiae Fructus Using Network-Based Pharmacology Analysis and Experimental Validation

The natural product Kochiae Fructus (KF) is the ripe fruit of Kochia scoparia (L.) Schrad and is renowned for its anti-inflammatory, anticancer, anti-fungal, and anti-pruritic effects. This study examined the anticancer effect of components of KF to assess its potential as an adjuvant for cancer treatment. Network-based pharmacological and docking analyses of KF found associations with oral squamous cell carcinoma. The molecular docking of oleanolic acid (OA) with LC3 and SQSTM1 had high binding scores, and hydrogen binding with amino acids of the receptors suggests that OA is involved in autophagy, rather than the apoptosis pathway. For experimental validation, we exposed SCC-15 squamous carcinoma cells derived from a human tongue lesion to KF extract (KFE), OA, and cisplatin. The KFE caused SCC-15 cell death, and induced an accumulation of the autophagy marker proteins LC3 and p62/SQSTM1. The novelty of this study lies in the discovery that the change in autophagy protein levels can be related to the regulatory death of SCC-15 cells. These findings suggest that KF is a promising candidate for future studies to provide insight into the role of autophagy in cancer cells and advance our understanding of cancer prevention and treatment.

Therapeutic effects and mechanisms of Ku-Gan formula on atopic dermatitis: A pilot clinical study and modular pharmacology analysis with animal validation

ETHNOPHARMACOLOGICAL RELEVANCE

Atopic dermatitis (AD) is a persistent, recurrent inflammatory skin disorder with a rapid upward trend worldwide. The first-line treatment for AD consists of topical medicines such as topical corticosteroids (TCSs). However, long-term use of conventional topical medicine results in side effects and recurrence, presenting therapeutic challenges for the management of AD. Ku-Gan formula (KG) has been extensively used to treat skin diseases since the Song dynasty. In particular, topical administration of the KG alleviates the cutaneous symptoms of AD and reduces recurrence rates with a good safety profile; however, the mechanisms of the KG's action remain unknown.

AIM OF THE STUDY

The current study aimed to evaluate the efficacy and safety of KG in AD patients and to investigate the molecular mechanisms that underlie the efficacy of KG in the treatment of AD.

MATERIALS AND METHODS

A single-arm prospective pilot study with historical controls was conducted. This study evaluated 11 patients with mild to moderate AD, who underwent topical KG treatment. The primary outcome was the change in local eczema area and severity index (EASI) scores. The secondary outcomes included the recurrence rate and safety. The recurrence rate were compared to those of a matched historical control group. Secondly, modular pharmacology analysis was used to elucidate the therapeutic mechanism of KG in AD treatment by identifying the hub genes and kernel pathways. Moreover, we evaluated treatment effects and verified modular pharmacology-based findings using the calcipotriol (MC903)-induced mouse model and bioinformatics analysis.

RESULTS

Our clinical pilot study demonstrated that the KG wet wrapping could effectively ameliorate skin lesions in AD patients with a significant drop from 4.18 to 1.63 in local EASI. Compared to the historical controls, KG had a reduced recurrence rate (36%) and a longer median time to relapse (>12 weeks). Modular pharmacology analysis identified the hub genes including IL6, IL1B, VEGFA, STAT3, JUN, TIMP1 and ARG1, and kernel pathway including IL-17 signaling pathway of KG. Pharmacodynamic results suggested that KG ameliorated skin symptoms and demonstrated no less efficacy than halcinonide (HC) in MC903-induced AD-like mice. In addition, KG regulated the mRNA expression of hub genes as well as the related genes involved in IL-17 signaling pathway including Il25, Il17a,Traf3ip2, and Traf6, in skin lesions of AD-like mice.

CONCLUSION

These results showed that KG is a safe and effective topical treatment for AD with low recurrence. In addition, our study identified potential molecular pathways and therapeutic candidate targets of the KG formula, providing evidence for its clinical applicability in AD.

Network pharmacology approaches for research of Traditional Chinese Medicines

Pharmacodynamics material basis and effective mechanisms are the two main issues to decipher the mechnisms of action of Traditional Chinese medicines (TCMs) for the treatment of diseases. TCMs, in "multi-component, multi-target, multi-pathway" paradigm, show satisfactory clinical results in complex diseases. New ideas and methods are urgently needed to explain the complex interactions between TCMs and diseases. Network pharmacology (NP) provides a novel paradigm to uncover and visualize the underlying interaction networks of TCMs against multifactorial diseases. The development and application of NP has promoted the safety, efficacy, and mechanism investigations of TCMs, which then reinforces the credibility and popularity of TCMs. The current organ-centricity of medicine and the "one disease-one target-one drug" dogma obstruct the understanding of complex diseases and the development of effective drugs. Therefore, more attentions should be paid to shift from "phenotype and symptom" to "endotype and cause" in understanding and redefining current diseases. In the past two decades, with the advent of advanced and intelligent technologies (such as metabolomics, proteomics, transcriptomics, single-cell omics, and artificial intelligence), NP has been improved and deeply implemented, and presented its great value and potential as the next drug-discovery paradigm. NP is developed to cure causal mechanisms instead of treating symptoms. This review briefly summarizes the recent research progress on NP application in TCMs for efficacy research, mechanism elucidation, target prediction, safety evaluation, drug repurposing, and drug design.

Systematic Description of the Content Variation of Natural Products (NPs): To Prompt the Yield of High-Value NPs and the Discovery of New Therapeutics

Natural products (NPs) have long been associated with human production and play a key role in the survival of species. Significant variations in NP content may severely affect the "return on investment" of NP-based industries and render ecological systems vulnerable. Thus, it is crucial to construct a platform that relates variations in NP content to their corresponding mechanisms. In this study, a publicly accessible online platform, NPcVar (http://npcvar.idrblab.net/), was developed, which systematically described the variations of NP contents and their corresponding mechanisms. The platform comprises 2201 NPs and 694 biological resources, including plants, bacteria, and fungi, curated using 126 diverse factors with 26,425 records. Each record contains information about the species, NP, and factors involved, as well as NP content data, parts of the plant that produce NPs, the location of the experiment, and reference information. All factors were manually curated and categorized into 42 classes which belong to four mechanisms (molecular regulation, species factor, environmental condition, and combined factor). Additionally, the cross-links of species and NP to well-established databases and the visualization of NP content under various experimental conditions were provided. In conclusion, NPcVar is a valuable resource for understanding the relationship between species, factors, and NP contents and is anticipated to serve as a promising tool for improving the yield of high-value NPs and facilitating the development of new therapeutics.

A Network Pharmacology Method Combined with Molecular Docking Verification to Explore the Therapeutic Mechanisms Underlying Simiao Pill Herbal Medicine against Hyperuricemia

Objective

Hyperuricemia (HUA) is a common metabolic disease caused by disordered purine metabolism. We aim to reveal the mechanisms underlying the anti-HUA function of Simiao pill and provide therapeutic targets.

Methods

Simiao pill-related targets were obtained using Herbal Ingredients' Targets (HIT), Traditional Chinese Medicine Systems Pharmacology (TCMSP), and Traditional Chinese Medicine Integrated Database (TCMID). HUA-associated targets were retrieved from GeneCards, DisGeNET, and Therapeutic Targets Database (TTD). Protein-protein interaction (PPI) network was constructed using the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database, ggraph and igraph R packages. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed using ClusterProfiler. The top 10 core targets were identified through cytoHubba. Molecular docking was conducted using PyMOL and AutoDock high-performance liquid chromatograph (HPLC) analysis was performed to identify effective compounds of Simiao pill.

Results

Simiao pill-HUA target network contained 80 targets. The key targets were mainly involved in inflammatory responses. Insulin (INS), tumor necrosis factor (TNF), interleukin-6 (IL6), interleukin 1 beta (IL1B), vascular endothelial growth factor A (VEGFA), leptin (LEP), signal transducer and activator of transcription 3 (STAT3), C-C motif chemokine ligand 2 (CCL2), interleukin-10 (IL10), and toll like receptor 4 (TLR4) were the top 10 targets in the PPI network. GO analysis demonstrated the main implication of the targets in molecular responses, production, and metabolism. KEGG analysis revealed that Simiao pill might mitigate HUA through advanced glycation end-product- (AGE-) receptor for AGE- (RAGE-) and hypoxia-inducible factor-1- (HIF-1-) associated pathways. IL1B, IL6, IL10, TLR4, and TNF were finally determined as the promising targets of Simiao pill treating HUA. Through molecular docking and HPLC analysis, luteolin, quercetin, rutaecarpine, baicalin, and atractylenolide I were the main active compounds.

Conclusions

Simiao pill can mitigate HUA by restraining inflammation, mediating AGE-RAGE- and HIF-1-related pathways, and targeting IL1B, IL6, IL10, TLR4, and TNF.

Study of Therapeutic Mechanisms of Puerarin against Sepsis-Induced Myocardial Injury by Integrating Network Pharmacology, Bioinformatics Analysis, and Experimental Validation

Myocardial injury is the most prevalent and serious complication of sepsis. The potential of puerarin (Pue) to treat sepsis-induced myocardial injury (SIMI) has been recently reported. Nevertheless, the specific anti-SIMI mechanisms of Pue remain largely unclear. Integrating network pharmacology, bioinformatics analysis, and experimental validation, we aimed to clarify the anti-SIMI mechanisms of Pue, thereby furnishing novel therapeutic targets. Pue-associated targets were collected from HIT, GeneCards, SwissTargetPrediction, SuperPred, and CTD databases. SIMI-associated targets were acquired from GeneCards and DisGeNET. Differentially expressed genes (DEGs) were identified from GEO database. Potential anti-SIMI targets of Pue were determined using VennDiagram. ClusterProfiler was employed for GO and KEGG analyses. STRING database and Cytoscape were used for protein-protein interaction (PPI) network construction, and cytoHubba was used for hub target screening. PyMOL and AutoDock were utilized for molecular docking. An in vitro SIMI model was built to further verify the therapeutic mechanisms of Pue. Seventy-three Pue-SIMI-DEG intersecting target genes were obtained. GO and KEGG analyses revealed that the targets were principally concentrated in cellular response to chemical stress, response to oxidative stress (OS), and insulin and neurotrophin signaling pathways. Through PPI analysis and molecular docking, AKT1, CASP3, TP53, and MAPK3 were identified as the pivotal targets. In vivo experiments indicated that Pue promoted cell proliferation, downregulated AKT1, CASP3, TP53, and MAPK3, and inhibited inflammation, myocardial injury, OS, and apoptosis in the cell model. Pue might inhibit inflammation, myocardial injury, OS, and apoptosis to treat SIMI by reducing AKT1, CASP3, TP53, and MAPK3.

Identification of Potential Targets and Mechanisms of Sinomenine in Allergic Rhinitis Treatment Based on Network Pharmacology and Molecular Docking

This study aimed to investigate the potential targets and molecular mechanism of sinomenine in treating allergic rhinitis (AR) using network pharmacology and molecular docking. Relevant targets of sinomenine and AR were obtained from public databases, and differentially expressed genes (DEGs) for AR were identified in the Gene Expression Omnibus database. Using VennDiagram, we identified 22 potential targets of sinomenine against AR by crossing disease targets, drug targets, and DEGs. Functional analysis revealed that sinomenine may act via its anti-inflammatory and immunosuppressive effects, and its action pathways may include the MAPK, HIF-1, and JAK-STAT pathways. Furthermore, hub targets were identified using EPC, MCC, and MNC algorithms, and six hub targets (STAT3, EGFR, NFKB1, HIF1A, PTGS2, and JAK1) were selected by integrating the top 10 hub genes and 22 potential targets. Molecular docking analysis indicated that STAT3, EGFR, PTGS2, and JAK1 may be key targets of sinomenine against AR. Overall, our results suggest that sinomenine has potential therapeutic effects against AR, and its mechanism of action may involve the regulation of key targets and pathways related to inflammation and immunity.

Flavonoids and saponins: What have we got or missed?

BACKGROUND

Flavonoids and saponins are important bioactive compounds that have attracted wide research interests. This review aims to summarise the state of the art of the pharmacology, toxicology and clinical efficacy of these compounds.

METHODS

Data were retrieved from PubMed, Cochrane Library, Web of Science, Proquest, CNKI, Chongqing VIP, Wanfang, NPASS and HIT 2.0 databases. Meta-analysis and systematic reviews were evaluated following the PRISMA guideline. Statistical analyses were conducted using SPSS23.0.

RESULTS

Rising research trends on flavonoids and saponins were observed since the 1990s and the 2000s, respectively. Studies on pharmacological targets and activities of flavonoids and saponins represent an important area of research advances over the past decade, and these important resources have been documented in open-access specialised databases and can be retrieved with ease. The rising research on flavonoids and saponins can be attributed, at least in part, to their links with some highly investigated fields of research, e.g., oxidative stress, inflammation and cancer; i.e., 6.88% and 3.03% of publications on oxidative stress cited by PubMed in 1990 - 2021 involved flavonoids and saponins, respectively, significantly higher than the percentage involving alkaloids (1.88%). The effects of flavonoids concern chronic venous insufficiency, cervical lesions, diabetes, rhinitis, dermatopathy, prostatitis, menopausal symptoms, angina pectoris, male pattern hair loss, lymphocytic leukaemia, gastrointestinal diseases and traumatic cerebral infarction, etc, while those of saponins may have impact on venous oedema in chronic deep vein incompetence, erectile dysfunction, acute impact injuries and systemic lupus erythematosus, etc. The volume of in vitro research appears way higher than in vivo and clinical studies, with only 10 meta-analyses and systematic reviews (involving 290 interventional and observational studies), and 36 clinical studies on flavonoids and saponins. Data are sorely needed on pharmacokinetics, in vitro pan-assay interferences, purity of tested compounds, interactions in complex herbal extracts, real impact of anti-oxidative strategies, and mid- and long-term toxicities. To fill these important gaps, further investigations are warranted. On the other hand, drug interactions may cause adverse effects but might also be useful for synergism, with the goals of enhancing effects or of detoxifying. Furthermore, the interactions between phytochemicals and the intestinal microbiota are worth investigating as the field may present a promising potential for novel drug development.

Multi-omics approaches for in-depth understanding of therapeutic mechanism for Traditional Chinese Medicine

Traditional Chinese Medicine (TCM) is extensively utilized in clinical practice due to its therapeutic and preventative treatments for various diseases. With the development of high-throughput sequencing and systems biology, TCM research was transformed from traditional experiment-based approaches to a combination of experiment-based and omics-based approaches. Numerous academics have explored the therapeutic mechanism of TCM formula by omics approaches, shifting TCM research from the "one-target, one-drug" to "multi-targets, multi-components" paradigm, which has greatly boosted the digitalization and internationalization of TCM. In this review, we concentrated on multi-omics approaches in principles and applications to gain a better understanding of TCM formulas against various diseases from several aspects. We first summarized frequently used TCM quality assessment methods, and suggested that incorporating both chemical and biological ingredients analytical methods could lead to a more comprehensive assessment of TCM. Secondly, we emphasized the significance of multi-omics approaches in deciphering the therapeutic mechanism of TCM formulas. Thirdly, we focused on TCM network analysis, which plays a vital role in TCM-diseases interaction, and serves for new drug discovery. Finally, as an essential source for storing multi-omics data, we evaluated and compared several TCM databases in terms of completeness and reliability. In summary, multi-omics approaches have infiltrated many aspects of TCM research. With the accumulation of omics data and data-mining resources, deeper understandings of the therapeutic mechanism of TCM have been acquired or will be gained in the future.

Methodology of network pharmacology for research on Chinese herbal medicine against COVID-19: A review

Traditional Chinese medicine, as a complementary and alternative medicine, has been practiced for thousands of years in China and possesses remarkable clinical efficacy. Thus, systematic analysis and examination of the mechanistic links between Chinese herbal medicine (CHM) and the complex human body can benefit contemporary understandings by carrying out qualitative and quantitative analysis. With increasing attention, the approach of network pharmacology has begun to unveil the mystery of CHM by constructing the heterogeneous network relationship of "herb-compound-target-pathway," which corresponds to the holistic mechanisms of CHM. By integrating computational techniques into network pharmacology, the efficiency and accuracy of active compound screening and target fishing have been improved at an unprecedented pace. This review dissects the core innovations to the network pharmacology approach that were developed in the years since 2015 and highlights how this tool has been applied to understanding the coronavirus disease 2019 and refining the clinical use of CHM to combat it.

Prevention of polycystic ovary syndrome and postmenopausal osteoporosis by inhibiting apoptosis with Shenling Baizhu powder compound

Objective

Shenling Baizhu powder (SBP) has been shown to reverse the abnormal expression of the aromatic hydrocarbon receptor (AHR) mediated by air pollution. Our study aimed to understand the main ingredient of SBP and investigate its action mechanism in preventing polycystic ovary syndrome (POCS) and postmenopausal osteoporosis (PMO).

Methods

The active ingredients of SBP with the highest binding affinity to AHR were screened using a Chinese medicine database, and their binding mechanism was simulated using molecular dynamics simulation (MDS). Rutin was utilized to treat ovarian granulosa cell lines and osteoblast cell lines. The cell lines were treated with a gradient of rutin concentration (0.01 mmol/L, 0.05 mmol/L and 0.1 mmol/L) to find the optimal drug dose. PCR was used to detect AHR and apoptosis-related proteins, and WB to detect the expression of AHR, caspase-3 and cleaved-caspase-3. Finally, the CCK-8 cell proliferation assay detected the proliferation of cells.

Results

We obtained Rutin through the Chinese medicine database, and dynamics simulation determined its binding sites. Ovarian granulosa cell lines and osteoblast cell lines were treated with Rutin. RT-PCR and western blotting revealed that the expression of apoptosis-associated protein Bcl-2 was elevated, and the expression of AHR, Bax, caspase-3 and PARP were decreased. CCK-8 results showed accelerated proliferation in both cell types.

Conclusion

Rutin, the main ingredient of SBP compound, works by binding to AHR, which can improve POCS and PMO by inhibiting cell apoptosis and by promoting cell proliferation.

Network Pharmacology and Molecular Docking Analysis Explores the Mechanisms of Cordyceps sinensis in the Treatment of Oral Lichen Planus

Objective

Oral lichen planus (OLP) is the most common potentially malignant disorder of the oral cavity. This study aimed to investigate the mechanism of action of Cordyceps sinensis in the treatment of OLP and provides a theoretical support for improving current treatment regimens for OLP.

Methods

The active components and therapeutic targets of Cordyceps sinensis were predicted and screened using the TCMSP, SymMap, PubMed, HIT 2.0, and PharmMapper databases, while the relevant OLP targets were predicted and screened using the DisGeNET and GeneCards databases. Protein-protein interactions (PPI) were examined using the String database, and Cytoscape was used to combine and illustrate the findings. GO and KEGG pathway enrichment analyses were carried out using RStudio, and AutoDock Vina and Pymol were used for molecular docking and visualization, respectively.

Results

A total of 404 potential target genes were discovered after evaluating 21 active compounds from Cordyceps sinensis. Potential therapeutic targets included 67 targets that matched and overlapped with OLP, including TNF, IL-6, CD4, EGFR, and IL1B. Key targets were predominantly engaged in the PI3K-Akt signaling pathway and the MAPK signaling pathway, according to the GO and KEGG analyses. These targets have a connection to biological processes including apoptosis signaling pathway regulation, T cell activation, and oxidative stress response. The molecular docking results showed that TNF, IL-6, CD4, EGFR, and IL1B could bind to their corresponding active components.

Conclusions

Cordyceps sinensis contains multiple components and acts on multiple targets and multiple pathways. Particularly, Cordyceps sinensis targets TNF, IL-6, CD4, EGFR, and IL1B, regulates PI3K-Akt and MAPK signaling pathways, as well as takes part in biological processes including apoptosis, T cell activation, and oxidative stress. Cordyceps sinensis could be a crucial choice in the therapy of OLP.

CPMCP: a database of Chinese patent medicine and compound prescription

Although several traditional Chinese medicine (TCM)-related databases have emerged, they focus on researching single medicinal materials, which is far from sufficient for clinical research and application. In comparison, compound prescriptions are more informative and meaningful in TCM, for they embody the information on the compatibility of TCM besides the relatively isolated information about single medicinal materials. The compatibility information is essential in TCM because it conveys not only what components are involved to treat special diseases but also how to combine these single medical materials. We established a database of Chinese patent medicine and compound prescription (CPMCP). It demonstrates the prescription information of Chinese patent medicines (CPMs) and ancient Chinese medicine prescriptions (CMPs). CPMCP reports their comprehensive and standardized information such as the components, indications and contraindications. It is worth mentioning that we organized relevant experts and spent lots of time manually mapping the functions of compound prescriptions in ancient Chinese to the standardized TCM symptom vocabularies, obtaining a total of 71 414 associations between compound prescriptions and TCM symptoms. In this way, CPMCP established the associations between TCM and modern medicine (MM) according to the associations between TCM symptoms and MM symptoms. In addition, to further exhibit the compatibility mechanism of compound prescriptions, CPMCP summarizes a set of common drug combination principles by analyzing the existing prescriptions. We believe that CPMCP can promote the modernization of TCM and make greater contributions to MM.

Database URL http://cpmcp.top

Antifibrotic activities of Scutellariae Radix extracts and flavonoids: Comparative proteomics reveals distinct and shared mechanisms

BACKGROUND

Scutellariae Radix (SR), the root of Scutellaria baicalensis Georgi, and SR flavonoids have antifibrotic activities. It remains obscure, however, amongst SR aqueous extract (SRA), SR methanolic extract (SRM) and five major SR flavonoids (baicalein, baicalin, wogonoside, wogonin and oroxyloside), which ones are the most promising antifibrotics and what their mechanisms are.

PURPOSE

To compare the antifibrotic activities of SR extracts and flavonoids, and the proteomic signatures of selected SR extract and flavonoid, versus IN1130 phosphate, an antifibrotic positive control (abbreviated as IN1130), in TGF-β1-induced in vitro model of fibrosis in NRK-49F renal fibroblasts.

METHODS

Isobaric labelling-based mass spectrometry was used for proteomic studies. Differentially expressed proteins were further analyzed using Gene Ontology annotation enrichment, protein-protein interaction network analysis and pathway analysis. Selected proteins of interest were validated by enzyme-linked immunosorbent assay (ELISA).

RESULTS

Baicalein was the SR flavonoid with the best efficacy-toxicity ratio. SRM contained 8-fold more flavonoids and was more potently antifibrotic than SRA. Proteomic analysis of cells treated by TGF-β1, with or without baicalein (40 and 80 μM), SRM (40 and 80 μg/ml) and IN1130 (1 μM) suggested that baicalein, SRM and IN1130 all repressed TGF-β1-induced ribosomal proteins in cell lysates, while baicalein and SRM, but not IN1130, regulated the intracellular lysosome pathway; secretomic analysis suggested that 40 and 80 μg/ml SRM and 80 μM baicalein, but not IN1130 and 40 μM baicalein increased ribosomal proteins in conditioned media, whereas only baicalein regulated the lysosome pathway. ELISA verified secretomic findings that baicalein, SRM and IN1130 repressed TGF-β1-induced PAI-1 (Serpine1), Plod2, Ctgf (Ccn2), Ccl2 and Ccl7; baicalein and IN1130, but not SRM, reversed TGF-β1-induced Cyr61 (Ccn1) and Tsku; only baicalein reversed TGF-β1 repression of Mmp3; only IN1130 reversed TGF-β1-repressed Nov (Ccn3). ELISA validated cell-lysate proteomic findings that baicalein, SRM and IN1130 all reversed TGF-β1-induced Enpp1; only IN1130 reversed TGF-β1-induced Impdh2 and Sqstm1 and TGF-β1-repressed Aldh3a1. Baicalein and SRM induced Ccdc80, while only baicalein induced Tfrc.

CONCLUSION

Baicalein, SRM and IN1130 repress TGF-β1-induced fibrogenesis in renal fibroblasts by regulating overlapping protein targets and biological pathways. Our findings offer a comprehensive view of shared, drug- and dose-specific pharmacological and toxicological mechanisms and provide a valuable resource for further research and development of more efficacious and safer antifibrotics.