Study on analgesic effect of Shentong Zhuyu Decoction in neuropathic pain rats by network pharmacology and RNA-Seq.

ETHNOPHARMACOLOGICAL RELEVANCE: Shentong Zhuyu Decoction (STZYD) is a traditional prescription for promoting the flow of Qi and Blood which is often used in the treatment of low back and leg pain clinicall with unclear mechanism. Neuropathic pain (NP) is caused by disease or injury affecting the somatosensory system. LncRNAs may play a key role in NP by regulating the expression of pain-related genes through binding mRNAs or miRNAs sponge mechanisms. AIM OF THE STUDY: To investigate the effect and potential mechanism of STZYD on neuropathic pain. METHODS: Chronic constriction injury (CCI) rats, a commonly used animal model, were used in this study. The target of STZYD in NP was analyzed by network pharmacology, and the analgesic effect of STZYD in different doses (H-STZYD, M-STZYD, L-STZYD) on CCI rats was evaluated by Mechanical withdrawal thresholds (MWT) and thermal withdrawal latency (TWL). Meanwhile, RNA-seq assay was used to detect the changed mRNAs and lncRNAs in CCI rats after STZYD intervention. GO analysis, KEGG pathway analysis, and IPA analysis were used to find key target genes and pathways, verified by qPCR and Western Blot. The regulatory effect of lncRNAs on target genes was predicted by co-expression analysis and ceRNA network construction. RESULTS: We found that STZYD can improve hyperalgesia in CCI rats, and H-STZYD has the best analgesic effect. The results of network pharmacological analysis showed that STZYD could play an analgesic role in CCI rats through the MAPK/ERK/c-FOS pathway. By mRNA-seq and lncRNA-seq, we found that STZYD could regulate the expression of Cnr1, Cacng5, Gucy1a3, Kitlg, Npy2r, and Grm8, and inhibited the phosphorylation level of ERK in the spinal cord of CCI rats. A total of 27 lncRNAs were associated with the target genes and 30 lncRNAs, 83 miRNAs and 5 mRNAs participated in the ceRNA network. CONCLUSION: STZYD has the effect of improving hyperalgesia in CCI rats through the MAPK/ERK/c-FOS pathway, which is related to the regulation of lncRNAs to Cnr1 and other key targets.

Potential immune-related therapeutic mechanisms of multiple traditional Chinese medicines on type 2 diabetic nephropathy based on bioinformatics, network pharmacology and molecular docking.

BACKGROUND: The prevalence of type 2 diabetic nephropathy (T2DN) ranges from 20 % to 40 % among individuals with type 2 diabetes. Multiple immune pathways play a pivotal role in the pathogenesis of T2DN. This study aimed to investigate the immunomodulatory effects of active ingredients derived from 14 traditional Chinese medicines (TCMs) on T2DN. METHODS: By removing batch effect on the GSE30528 and GSE96804 datasets, we employed a combination of weighted gene co-expression network analysis, least absolute shrinkage and selection operator analysis, protein-protein interaction network analysis, and the CIBERSORT algorithm to identify the active ingredients of TCMs as well as potential hub biomarkers associated with immune cells. Functional analysis was conducted using Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene Ontology (GO), and gene set variation analysis (GSVA). Additionally, molecular docking was employed to evaluate interactions between active ingredients and potential immunotherapy targets. RESULTS: A total of 638 differentially expressed genes (DEGs) were identified in this study, comprising 5 hub genes along with 4 potential biomarkers. Notably, CXCR1, CXCR2, and FOS exhibit significant associations with immune cells while displaying robust or favorable affinities towards the active ingredients kaempferol, quercetin, and luteolin. Furthermore, functional analysis unveiled intricate involvement of DEGs, hub genes and potential biomarkers in pathways closely linked to immunity and diabetes. CONCLUSION: The potential hub biomarkers and immunotherapy targets associated with immune cells of T2DN comprise CXCR1, CXCR2, and FOS. Furthermore, kaempferol, quercetin, and luteolin demonstrate potential immunomodulatory effects in modulating T2DN through the regulation of CXCR1, CXCR2, and FOS expression.

Elucidating the molecular mechanisms of sepsis: Identifying key aging-related biomarkers and potential therapeutic targets in the treatment of sepsis.

BACKGROUND: Sepsis remains a crucial global health issue characterized by high mortality rates and a lack of specific treatments. This study aimed to elucidate the molecular mechanisms underlying sepsis and to identify potential therapeutic targets and compounds. METHODS: High-throughput sequencing data from the GEO database (GSE26440 as the training set and GSE13904 and GSE32707 as the validation sets), weighted gene co-expression network analysis (WGCNA), Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, alongside a combination of PPI and machine learning methods (LASSO and SVM) were utilized. RESULTS: WGCNA identified the black module as positively correlated, and the green module as negatively correlated with sepsis. Further intersections of these module genes with age-related genes yielded 57 sepsis-related genes. GO and KEGG pathway enrichment analysis, PPI, LASSO, and SVM selected six hub aging-related genes: BCL6, FOS, ETS1, ETS2, MAPK14, and MYC. A diagnostic model was constructed based on these six core genes, presenting commendable performance in both the training and validation sets. Notably, ETS1 demonstrated significant differential expression between mild and severe sepsis, indicating its potential as a biomarker of severity. Furthermore, immune infiltration analysis of these six core genes revealed their correlation with most immune cells and immune-related pathways. Additionally, compounds were identified in the traditional Chinese medicine Danshen, which upon further analysis, revealed 354 potential target proteins. GO and KEGG enrichment analysis of these targets indicated a primary enrichment in inflammation and immune-related pathways. A Venn diagram intersects these target proteins, and our aforementioned six core genes yielded three common genes, suggesting the potential efficacy of Danshen in sepsis treatment through these genes. CONCLUSIONS: This study highlights the pivotal roles of age-related genes in the molecular mechanisms of sepsis, offers potential biomarkers, and identifies promising therapeutic compounds, laying a robust foundation for future studies on the treatment of sepsis.

New Approach for Targeted Treatment of Mild COVID-19 by Honeysuckle through Network Pharmacology Analysis.

OBJECTIVE: To investigate the potential pharmacological value of extracts from honeysuckle on patients with mild coronavirus disease 2019 (COVID-19) infection. METHODS: The active components and targets of honeysuckle were screened by Traditional Chinese Medicine Database and Analysis Platform (TCMSP). SwissADME and pkCSM databases predict pharmacokinetics of ingredients. The Gene Expression Omnibus (GEO) database collected transcriptome data for mild COVID-19. Data quality control, differentially expressed gene (DEG) identification, enrichment analysis, and correlation analysis were implemented by R toolkit. CIBERSORT evaluated the infiltration of 22 immune cells. RESULTS: The seven active ingredients of honeysuckle had good oral absorption and medicinal properties. Both the active ingredient targets of honeysuckle and differentially expressed genes of mild COVID-19 were significantly enriched in immune signaling pathways. There were five overlapping immunosignature genes, among which RELA and MAP3K7 expressions were statistically significant (P < 0.05). Finally, immune cell infiltration and correlation analysis showed that RELA, MAP3K7, and natural killer (NK) cell are with highly positive correlation and highly negatively correlated with hematopoietic stem cells. CONCLUSION: Our analysis suggested that honeysuckle extract had a safe and effective protective effect against mild COVID-19 by regulating a complex molecular network. The main mechanism was related to the proportion of infiltration between NK cells and hematopoietic stem cells.

Pharmacological Effects of Cisplatin Combination with Natural Products in Cancer Chemotherapy.

Cisplatin and other platinum-based drugs, such as carboplatin, ormaplatin, and oxaliplatin, have been widely used to treat a multitude of human cancers. However, a considerable proportion of patients often relapse due to drug resistance and/or toxicity to multiple organs including the liver, kidneys, gastrointestinal tract, and the cardiovascular, hematologic, and nervous systems. In this study, we sought to provide a comprehensive review of the current state of the science highlighting the use of cisplatin in cancer therapy, with a special emphasis on its molecular mechanisms of action, and treatment modalities including the combination therapy with natural products. Hence, we searched the literature using various scientific databases., such as MEDLINE, PubMed, Google Scholar, and relevant sources, to collect and review relevant publications on cisplatin, natural products, combination therapy, uses in cancer treatment, modes of action, and therapeutic strategies. Our search results revealed that new strategic approaches for cancer treatment, including the combination therapy of cisplatin and natural products, have been evaluated with some degree of success. Scientific evidence from both in vitro and in vivo studies demonstrates that many medicinal plants contain bioactive compounds that are promising candidates for the treatment of human diseases, and therefore represent an excellent source for drug discovery. In preclinical studies, it has been demonstrated that natural products not only enhance the therapeutic activity of cisplatin but also attenuate its chemotherapy-induced toxicity. Many experimental studies have also reported that natural products exert their therapeutic action by triggering apoptosis through modulation of mitogen-activated protein kinase (MAPK) and p53 signal transduction pathways and enhancement of cisplatin chemosensitivity. Furthermore, natural products protect against cisplatin-induced organ toxicity by modulating several gene transcription factors and inducing cell death through apoptosis and/or necrosis. In addition, formulations of cisplatin with polymeric, lipid, inorganic, and carbon-based nano-drug delivery systems have been found to delay drug release, prolong half-life, and reduce systemic toxicity while other formulations, such as nanocapsules, nanogels, and hydrogels, have been reported to enhance cell penetration, target cancer cells, and inhibit tumor progression.

Reveals of quercetin's therapeutic effects on oral lichen planus based on network pharmacology approach and experimental validation.

Oral lichen planus (OLP) is a localized autoimmune disease of the oral mucosa, with an incidence of up to 2%. Although corticosteroids are the first-line treatment, they cause several adverse effects. Quercetin, a naturally occurring compound, has fewer side-effects and provides long-term benefits. Besides, it has powerful anti­inflammatory activities. Here, we combined network pharmacology with experimental verification to predict and verify the key targets of quercetin against OLP. First, 66 quercetin-OLP common targets were analyzed from various databases. The protein-protein interaction (PPI) network was constructed. Topology analysis and MCODE cluster analysis of common targets were conducted to identify 12 key targets including TP53, IL-6 and IFN-γ and their connections. Gene functions and key signaling pathways, including reactive oxygen species metabolism, IL-17 pathway and AGE-RAGE pathway, were enriched by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. Then, in vitro experiments showed that quercetin interfered with Th1/Th2 balance by acting on IL-6 and IFN-γ to modulate the immune system in treating OLP. Quercetin considerably affected the apoptosis and migration of T lymphocytes in OLP patients. Our study reveals the potential therapeutic targets and signaling pathways of quercetin associated with OLP, and establishes the groundwork for future clinical applications.

Essential oil from Lavandula angustifolia elicits expression of three SbWRKY transcription factors and defense-related genes against sorghum damping-off.

Sorghum damping-off, caused by Fusarium solani (Mart.) Sacc., is a serious disease which causes economic loss in sorghum production. In this study, antagonistic activity of lavender essential oil (EO) at 0.5, 0.75, 1.0, 1.25, 1.5, and 1.6% against F. solani was studied in vitro. Their effects on regulation of three SbWRKY transcription factors, the response factor JERF3 and eight defense-related genes, which mediate different signaling pathways, in sorghum were investigated. Effects of application under greenhouse conditions were also evaluated. The results showed that lavender EO possesses potent antifungal activity against F. solani. A complete inhibition in the fungal growth was recorded for lavender EO at 1.6%. Gas chromatography-mass spectrometric analysis revealed that EO antifungal activity is most likely attributed to linalyl anthranilate, α-terpineol, eucalyptol, α-Pinene, and limonene. Observations using transmission electron microscopy revealed many abnormalities in the ultrastructures of the fungal mycelium as a response to treating with lavender EO, indicating that multi-mechanisms contributed to their antagonistic behavior. Results obtained from Real-time PCR investigations demonstrated that the genes studied were overexpressed, to varying extents in response to lavender EO. However, SbWRKY1 was the highest differentially expressed gene followed by JERF3, which suggest they play primary role(s) in synchronously organizing the transcription-regulatory-networks enhancing the plant resistance. Under greenhouse conditions, treating of sorghum grains with lavender EO at 1.5% prior to infection significantly reduced disease severity. Moreover, the growth parameters evaluated, the activities of antioxidant enzymes, and total phenolic and flavonoid contents were all enhanced. In contrast, lipid peroxidation was highly reduced. Results obtained from this study support the possibility of using lavender EO for control of sorghum damping-off. However, field evaluation is highly needed prior to any usage recommendation.

Network Pharmacology Prediction: The Possible Mechanisms of Cinobufotalin against Osteosarcoma.

OBJECTIVE: To explore the active compounds and targets of cinobufotalin (huachansu) compared with the osteosarcoma genes to obtain the potential therapeutic targets and pharmacological mechanisms of action of cinobufotalin on osteosarcoma through network pharmacology. METHODS: The composition of cinobufotalin was searched by literature retrieval, and the target was selected from the CTD and TCMSP databases. The osteosarcoma genes, found from the GeneCards, OMIM, and other databases, were compared with the cinobufotalin targets to obtain potential therapeutic targets. The protein-protein interaction (PPI) network of potential therapeutic targets, constructed through the STRING database, was inputted into Cytoscape software to calculate the hub genes, using the NetworkAnalyzer. The hub genes were inputted into the Kaplan-Meier Plotter online database for exploring the survival curve. Functional enrichment analysis was identified using the DAVID database. RESULTS: 28 main active compounds of cinobufotalin were explored, including bufalin, adenosine, oleic acid, and cinobufagin. 128 potential therapeutic targets on osteosarcoma are confirmed among 184 therapeutic targets form cinobufotalin. The hub genes included TP53, ACTB, AKT1, MYC, CASP3, JUN, TNF, VEGFA, HSP90AA1, and STAT3. Among the hub genes, TP53, ACTB, MYC, TNF, VEGFA, and STAT3 affect the patient survival prognosis of sarcoma. Through function enrichment analysis, it is found that the main mechanisms of cinobufotalin on osteosarcoma include promoting sarcoma apoptosis, regulating the cell cycle, and inhibiting proliferation and differentiation. CONCLUSION: The possible mechanisms of cinobufotalin against osteosarcoma are preliminarily predicted through network pharmacology, and further experiments are needed to prove these predictions.

Integrative Bioinformatics approaches to therapeutic gene target selection in various cancers for Nitroglycerin.

Integrative Bioinformatics analysis helps to explore various mechanisms of Nitroglycerin activity in different types of cancers and help predict target genes through which Nitroglycerin affect cancers. Many publicly available databases and tools were used for our study. First step in this study is identification of Interconnected Genes. Using Pubchem and SwissTargetPrediction Direct Target Genes (activator, inhibitor, agonist and suppressor) of Nitroglycerin were identified. PPI network was constructed to identify different types of cancers that the 12 direct target genes affected and the Closeness Coefficient of the direct target genes so identified. Pathway analysis was performed to ascertain biomolecules functions for the direct target genes using CluePedia App. Mutation Analysis revealed Mutated Genes and types of cancers that are affected by the mutated genes. While the PPI network construction revealed the types of cancer that are affected by 12 target genes this step reveals the types of cancers affected by mutated cancers only. Only mutated genes were chosen for further study. These mutated genes were input into STRING to perform NW Analysis. NW Analysis revealed Interconnected Genes within the mutated genes as identified above. Second Step in this study is to predict and identify Upregulated and Downregulated genes. Data Sets for the identified cancers from the above procedure were obtained from GEO Database. DEG Analysis on the above Data sets was performed to predict Upregulated and Downregulated genes. A comparison of interconnected genes identified in step 1 with Upregulated and Downregulated genes obtained in step 2 revealed Co-Expressed Genes among Interconnected Genes. NW Analysis using STRING was performed on Co-Expressed Genes to ascertain Closeness Coefficient of Co-Expressed genes. Gene Ontology was performed on Co-Expressed Genes to ascertain their Functions. Pathway Analysis was performed on Co-Expressed Genes to identify the Types of Cancers that are influenced by co-expressed genes. The four types of cancers identified in Mutation analysis in step 1 were the same as the ones that were identified in this pathway analysis. This further corroborates the 4 types of cancers identified in Mutation analysis. Survival Analysis was done on the co-expressed genes as identified above using Survexpress. BIOMARKERS for Nitroglycerin were identified for four types of cancers through Survival Analysis. The four types of cancers are Bladder cancer, Endometrial cancer, Melanoma and Non-small cell lung cancer.

Antisense oligonucleotides for Alzheimer's disease therapy: from the mRNA to miRNA paradigm.

Alzheimer's disease (AD) represents a particular therapeutic challenge because its aetiology is very complex, with dynamic progression from preclinical to clinical stages. Several potential therapeutic targets and strategies were tested for AD, in over 2000 clinical trials, but no disease-modifying therapy exists. This failure indicates that AD, as a multifactorial disease, may require multi-targeted approaches and the delivery of therapeutic molecules to the right place and at the right disease stage. Opportunities to meet the challenges of AD therapy appear to come from recent progress in knowledge and methodological advances in the design, synthesis, and targeting of brain mRNA and microRNA with synthetic antisense oligonucleotides (ASOs). Several types of ASOs allow the utilisation of different mechanisms of posttranscriptional regulation and offer enhanced effects over alternative therapeutics. This article reviews ASO-based approaches and targets in preclinical and clinical trials for AD, and presents the future perspective on ASO therapies for AD.

Pharmacological Mechanism of Danggui-Sini Formula for Intervertebral Disc Degeneration: A Network Pharmacology Study.

BACKGROUND: Intervertebral disc degeneration (IVDD) is the most significant cause of low back pain, the sixth-largest disease burden globally, and the leading cause of disability. This study is aimed at investigating the molecular biological mechanism of Danggui-Sini formula (DSF) mediated IVDD treatment. METHODS: A potential gene set for DSF treatment of IVDD was identified through TCMSP, UniProt, and five disease gene databases. A protein interaction network of common targets between DSF and IVDD was established by using the STRING database. GO and KEGG enrichment analyses were performed using the R platform to discover the potential mechanism. Moreover, AutoDock Vina was used to verify molecular docking and calculate the binding energy. RESULTS: A total of 119 active ingredients and 136 common genes were identified, including 10 core genes (AKT1, IL6, ALB, TNF, VEGFA, TP53, MAPK3, CASP3, JUN, and EGF). Enrichment analysis results showed that the therapeutic targets of DSF for diseases mainly focused on the AGE-RAGE signaling pathway involved in diabetic complications, IL-17 signaling pathway, TNF signaling pathway, Toll-like receptor signaling pathway, apoptosis, cellular senescence, PI3K-Akt signaling pathway, and FoxO signaling pathway. These biological processes are induced mainly in response to oxidative stress and reactive oxygen species and the regulation of apoptotic signaling pathways. Molecular docking showed that there was a stable affinity between the core genes and the key components. CONCLUSIONS: The combination of network pharmacology and molecular docking provides a practical way to analyze the molecular biological mechanism of DSF-mediated IVDD treatment, which confirms the "multicomponent, multitarget and multipathway" characteristics of DSF and provides an essential theoretical basis for clinical practice.

Combining Network Pharmacology with Molecular Docking for Mechanistic Research on Thyroid Dysfunction Caused by Polybrominated Diphenyl Ethers and Their Metabolites.

Network pharmacology was used to illuminate the targets and pathways of polybrominated diphenyl ethers (PBDEs) causing thyroid dysfunction. A protein-protein interaction (PPI) network was constructed. Molecular docking was applied to analyze PBDEs and key targets according to the network pharmacology results. A total of 247 targets were found to be related to 16 PBDEs. Ten key targets with direct action were identified, including the top five PIK3R1, MAPK1, SRC, RXRA, and TP53. Gene Ontology (GO) functional enrichment analysis identified 75 biological items. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis identified 62 pathways mainly related to the regulation of the thyroid hormone signaling pathway, MAPK signaling pathway, PI3K-Akt signaling, pathways in cancer, proteoglycans in cancer, progesterone-mediated oocyte maturation, and others. The molecular docking results showed that BDE-99, BDE-153, 5-OH-BDE47, 5'-OH-BDE99, 5-BDE47 sulfate, and 5'-BDE99 sulfate have a good binding effect with the kernel targets. PBDEs could interfere with the thyroid hormone endocrine through multiple targets and biological pathways, and metabolites demonstrated stronger effects than the prototypes. This research provides a basis for further research on the toxicological effects and molecular mechanisms of PBDEs and their metabolites. Furthermore, the application of network pharmacology to the study of the toxicity mechanisms of environmental pollutants provides a new methodology for environmental toxicology.

Exploration of the anti-insomnia mechanism of Ganoderma by central-peripheral multi-level interaction network analysis.

BACKGROUND: Ganoderma (Lingzhi in Chinese) has shown good clinical outcomes in the treatment of insomnia, restlessness, and palpitation. However, the mechanism by which Ganoderma ameliorates insomnia is unclear. We explored the mechanism of the anti-insomnia effect of Ganoderma using systems pharmacology from the perspective of central-peripheral multi-level interaction network analysis. METHODS: The active components and central active components of Ganoderma were obtained from the TCMIP and TCMSP databases, then screened to determine their pharmacokinetic properties. The potential target genes of these components were identified using the Swiss Target Prediction and TCMSP databases. The results were matched with the insomnia target genes obtained from the GeneCards, OMIM, DisGeNET, and TCMIP databases. Overlapping targets were subjected to multi-level interaction network analysis and enrichment analysis using the STRING, Metascape, and BioGPS databases. The networks analysed were protein-protein interaction (PPI), drug-component-target gene, component-target gene-organ, and target gene-extended disease; we also performed gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. RESULTS: In total, 34 sedative-hypnotic components (including 5 central active components) were identified, corresponding to 51 target genes. Multi-level interaction network analysis and enrichment analysis demonstrated that Ganoderma exerted an anti-insomnia effect via multiple central-peripheral mechanisms simultaneously, mainly by regulating cell apoptosis/survival and cytokine expression through core target genes such as TNF, CASP3, JUN, and HSP90αA1; it also affected immune regulation and apoptosis. Therefore, Ganoderma has potential as an adjuvant therapy for insomnia-related complications. CONCLUSION: Ganoderma exerts an anti-insomnia effect via complex central-peripheral multi-level interaction networks.

Network Pharmacology-Based Identification of Potential Targets of Lonicerae japonicae Flos Acting on Anti-Inflammatory Effects.

Lonicerae japonicae flos (LJF) is widely used for the treatment of inflammation-related diseases in traditional Chinese medicine (TCM). To clarify the anti-inflammatory mechanism of LJF, 29 compounds with high content in LJF were selected for network pharmacology. Then, a comprehensive network pharmacology strategy was implemented, which involved compound-inflammation-target construction, protein-protein interaction (PPI) network analysis, and enrichment analysis. Finally, molecular docking and in vitro experiments were performed to verify the anti-inflammatory activity and targets of the key compound. As a result, 279 inflammation-associated proteins were identified, which are mainly involved in the AGE/RAGE signaling pathway in diabetic complications, the HIF-1 signaling pathway, the PI3K-AKT signaling pathway, and EGFR tyrosine kinase inhibitor resistance. A total of 12 compounds were linked to more than 35 targets, including apigenin, kaempferol, quercetin, luteolin, and ferulic acid. The results of molecular docking showed that AKT has the most binding activity, exhibiting certain binding activity with 10 compounds, including vanillic acid, protocatechuic acid, secologanic acid, quercetin, and luteolin; the results of qRT-PCR and WB confirmed that two key compounds, secologanic acid and luteolin, could significantly decrease the secretion of TNF-α and the AKT expression of RAW264.7 murine macrophages stimulated by LPS (lipopolysaccharide). These results demonstrate that the comprehensive strategy can serve as a universal method to illustrate the anti-inflammatory mechanisms of traditional Chinese medicine by identifying the pathways or targets.

Network Pharmacology-Based Study to Uncover Potential Pharmacological Mechanisms of Korean Thistle (Cirsium japonicum var. maackii (Maxim.) Matsum.) Flower against Cancer.

Cirsium japonicum var. maackii (Maxim.) Matsum. or Korean thistle flower is a herbal plant used to treat tumors in Korean folk remedies, but its essential bioactives and pharmacological mechanisms against cancer have remained unexplored. This study identified the main compounds(s) and mechanism(s) of the C. maackii flower against cancer via network pharmacology. The bioactives from the C. maackii flower were revealed by gas chromatography-mass spectrum (GC-MS), and SwissADME evaluated their physicochemical properties. Next, target(s) associated with the obtained bioactives or cancer-related targets were retrieved by public databases, and the Venn diagram selected the overlapping targets. The networks between overlapping targets and bioactives were visualized, constructed, and analyzed by RPackage. Finally, we implemented a molecular docking test (MDT) to explore key target(s) and compound(s) on AutoDockVina and LigPlot+. GC-MS detected a total of 34 bioactives and all were accepted by Lipinski's rules and therefore classified as drug-like compounds (DLCs). A total of 597 bioactive-related targets and 4245 cancer-related targets were identified from public databases. The final 51 overlapping targets were selected between the bioactive targets network and cancer-related targets. With Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment, a total of 20 signaling pathways were manifested, and a hub signaling pathway (PI3K-Akt signaling pathway), a key target (Akt1), and a key compound (Urs-12-en-24-oic acid, 3-oxo, methyl ester) were selected among the 20 signaling pathways via MDT. Overall, Urs-12-en-24-oic acid, 3-oxo, methyl ester from the C. maackii flower has potent anti-cancer efficacy by inactivating Akt1 on the PI3K-Akt signaling pathway.

Network pharmacology and molecular docking reveal the effective substances and active mechanisms of Dalbergia Odoriferain protecting against ischemic stroke.

Dalbergia Odorifera (DO) has been widely used for the treatment of cardiovascular and cerebrovascular diseasesinclinical. However, the effective substances and possible mechanisms of DO are still unclear. In this study, network pharmacology and molecular docking were used toelucidate the effective substances and active mechanisms of DO in treating ischemic stroke (IS). 544 DO-related targets from 29 bioactive components and 344 IS-related targets were collected, among them, 71 overlapping common targets were got. Enrichment analysis showed that 12 components were the possible bioactive components in DO, which regulating 9 important signaling pathways in 3 biological processes including 'oxidative stress' (KEGG:04151, KEGG:04068, KEGG:04915), 'inflammatory response'(KEGG:04668, KEGG:04064) and 'vascular endothelial function regulation'(KEGG:04066, KEGG:04370). Among these, 5 bioactive components with degree≥20 among the 12 potential bioactive components were selected to be docked with the top5 core targets using AutodockVina software. According to the results of molecular docking, the binding sites of core target protein AKT1 and MOL002974, MOL002975, and MOL002914 were 9, 8, and 6, respectively, and they contained 2, 1, and 0 threonine residues, respectively. And some binding sites were consistent, which may be the reason for the similarities and differences between the docking results of the 3 core bioactive components. The results of in vitro experiments showed that OGD/R could inhibit cell survival and AKT phosphorylation which were reversed by the 3 core bioactive components. Among them, MOL002974 (butein) had a slightly better effect. Therefore, the protective effect of MOL002974 (butein) against cerebral ischemia was further evaluated in a rat model of middle cerebral artery occlusion (MCAO) by detecting neurological score, cerebral infarction volume and lactate dehydrogenase (LDH) level. The results indicated that MOL002974 (butein) could significantly improve the neurological score of rats, decrease cerebral infarction volume, and inhibit the level of LDH in the cerebral tissue and serum in a dose-dependent manner. In conclusion, network pharmacology and molecular docking predicate the possible effective substances and mechanisms of DO in treating IS. And the results are verified by the in vitro and in vivo experiments. This research reveals the possible effective substances from DO and its active mechanisms for treating IS and provides a new direction for the secondary development of DO for treating IS.

High-Throughput Screen of Natural Compounds and Biomarkers for NSCLC Treatment by Differential Expression and Weighted Gene Coexpression Network Analysis (WGCNA).

Lung cancer is known as the leading cause which presents the highest fatality rate worldwide; non-small-cell lung cancer (NSCLC) is the most prevalent type of lung carcinoma with high severity and affects 80% of patients with lung malignancies. Up to now, the general treatment for NSCLC includes surgery, chemotherapy, and radiotherapy; however, some therapeutic drugs and approaches could cause side effects and weaken the immune system. The combination of conventional therapies and traditional Chinese medicine (TCM) significantly improves treatment efficacy in lung cancer. Therefore, it is necessary to investigate the chemical composition and underlying antitumor mechanisms of TCM, so as to get a better understanding of the potential natural ingredient for lung cancer treatment. In this study, we selected 78 TCM to treat NSCLC cell line (A549) and obtained 92 transcriptome data; differential expression and WGCNA were applied to screen the potential natural ingredient and target genes. The sample which was treated with A. pierreana generated the most significant DEG set, including 6130 DEGs, 2479 upregulated, and 3651 downregulated. KEGG pathway analyses found that four pathways (MAPK, NF-kappa B, p53, and TGF-beta signaling pathway) were significantly enriched; 16 genes were significantly regulated in these four pathways. Interestingly, some of them such as EGFR, DUSP4, IL1R1, IL1B, MDM2, CDKNIA, and IDs have been used as the target biomarkers for cancer diagnosis and therapy. In addition, classified samples into 14 groups based on their pharmaceutical effects, WGCNA was used to identify 27 modules. Among them, green and darkgrey were the most relevant modules. Eight genes in the green module and four in darkgrey were identified as hub genes. In conclusion, we screened out three new TCM (B. fruticose, A. pierreana, and S. scandens) that have the potential to develop natural anticancer drugs and obtained the therapeutic targets for NSCLC therapy. Our study provides unique insights to screen the natural components for NSCLC therapy using high-throughput transcriptome analysis.

Molecular Mechanism of Jinchan Oral Liquid in the Treatment of Children with Respiratory Syncytial Virus Pneumonia Based on Network Pharmacology and Molecular Docking Technology.

OBJECTIVE: Exploration of the underlying molecular mechanism of Jinchan Oral Liquid (JOL) in treating children with the respiratory syncytial virus (RSV) pneumonia to provide new evidence for the clinical application. METHODS: The active components and target genes of JOL were screened by the TCMSP database. The targets of RSV pneumonia were obtained from the GeneCards, OMIM, DrugBank, and PharmGKB database. Then, we constructed the active component-target network and screened the core genes. The overlaps were screened for PPI network analysis, GO analysis, and KEGG analysis. Finally, result validation was performed by molecular docking. RESULTS: According to the screening criteria of the ADME, 74 active compounds of JOL were obtained; after removing redundant targets, we selected 180 potential targets. By screening the online database, 893 RSV pneumonia-related targets were obtained. A total of 82 overlapping genes were chosen by looking for the intersection. The STRING online database was used to acquire PPI relationships, and 16 core genes were obtained. GO and KEGG analyses showed that the main pathways of JOL in treating RSV pneumonia include TNF signaling pathway and IL17 signaling pathway. The molecular docking results showed that the active compounds of JOL had a good affinity with the core genes. CONCLUSION: In this study, we preliminarily discussed the main active ingredients, related targets, and pathways of JOL and predicted the pharmacodynamic basis and the potential therapeutic mechanisms of RSV pneumonia. In summary, the network pharmacology strategy may be helpful for the discovery of multitarget drugs against complex diseases.

Identification of Key Candidate Genes and Chemical Perturbagens in Diabetic Kidney Disease Using Integrated Bioinformatics Analysis.

Globally, nearly 40 percent of all diabetic patients develop serious diabetic kidney disease (DKD). The identification of the potential early-stage biomarkers and elucidation of their underlying molecular mechanisms in DKD are required. In this study, we performed integrated bioinformatics analysis on the expression profiles GSE111154, GSE30528 and GSE30529 associated with early diabetic nephropathy (EDN), glomerular DKD (GDKD) and tubular DKD (TDKD), respectively. A total of 1,241, 318 and 280 differentially expressed genes (DEGs) were identified for GSE30258, GSE30529, and GSE111154 respectively. Subsequently, 280 upregulated and 27 downregulated DEGs shared between the three GSE datasets were identified. Further analysis of the gene expression levels conducted on the hub genes revealed SPARC (Secreted Protein Acidic And Cysteine Rich), POSTN (periostin), LUM (Lumican), KNG1 (Kininogen 1), FN1 (Fibronectin 1), VCAN (Versican) and PTPRO (Protein Tyrosine Phosphatase Receptor Type O) having potential roles in DKD progression. FN1, LUM and VCAN were identified as upregulated genes for GDKD whereas the downregulation of PTPRO was associated with all three diseases. Both POSTN and SPARC were identified as the overexpressed putative biomarkers whereas KNG1 was found as downregulated in TDKD. Additionally, we also identified two drugs, namely pidorubicine, a topoisomerase inhibitor (LINCS ID- BRD-K04548931) and Polo-like kinase inhibitor (LINCS ID- BRD-K41652870) having the validated role in reversing the differential gene expression patterns observed in the three GSE datasets used. Collectively, this study aids in the understanding of the molecular drivers, critical genes and pathways that underlie DKD initiation and progression.

The bioactive ingredients in Actinidia chinensis Planch. Inhibit liver cancer by inducing apoptosis.

ETHNOPHARMACOLOGICAL RELEVANCE: Actinidia chinensis Planch. (ACP) is a common traditional Chinese medicine, which is mostly used for cancer treatment clinically. Liver cancer is a refractory tumor with a high incidence. Although ACP has been reported in the treatment of liver cancer, its possible mechanism of action is little known. AIM OF STUDY: The aim of this paper was to investigate the active components of ACP in the treatment of liver cancer and the related mechanisms by a network pharmacology approach. METHODS: The active components of ACP and the corresponding targets were obtained from multiple databases. Cytoscape software and STRING database were used to build the "herb-component-target (H-C-T)" network and protein-protein interactions (PPI) network. The key components and targets were further predicted by the Cytohubba plug-in in Cytoscape. Then, experiments were carried out on HepG2 cell line and Huh7 cell line to verify the effects and related mechanisms of the key compounds in ACP. RESULTS: 28 active components in ACP and 1299 related targets were screened out according to two indicators, oral bioavailability (OB) and drug-likeness (DL). The key compounds predicted include rutinum, astragalin, and L-epicatechin, and the main signaling pathways focus on apoptosis. Astragalin, a key compound in ACP, could inhibit the expression of Bcl-2, up-regulate the expression of Bax, cleaved caspase 3, cleaved caspase 8, and cleaved caspase 9, and regulate the apoptosis signaling pathway to inhibit the proliferation of liver cancer cells to play a therapeutic role in anti-liver cancer. CONCLUSIONS: These results suggest that ACP can alleviate the progression of liver cancer through the mechanisms predicted by network pharmacology, and provide a basis for the further understanding of the application of ACP in anti-cancer.