Unraveling the mechanism of alkaloids from Sophora alopecuroides Linn combined with immune checkpoint blockade in the treatment of non-small cell lung cancer based on systems pharmacology.

Quinolizidine alkaloids, as essential active ingredients extracted from Sophora alopecuroides Linn (SAL), have been proven to be pharmacologically active in a variety of cancers including non-small cell lung cancer (NSCLC). However, whether these alkaloids have substantial benefits in combination with immune checkpoint blockade (ICB) for the treatment of NSCLC is unknown. Here, we explore the potential of these alkaloids in combination with ICB therapy based on a systems pharmacology and bioinformatics approach. We found that 37 alkaloids in SAL have highly similar characteristics in the molecular skeleton, pharmacological properties, and targets. The expression of targets of these alkaloids are significantly correlated with the infiltration level of tumor infiltrating lymphocytes and the expression levels of multiple immune checkpoints in NSCLC. They share similar molecular mechanisms in antitumor immunity. Sophocarpine (Sop) is one of the most representative constituents of these alkaloids. We demonstrated that the Sop promotes PD-L1 expression to improve the effects of PD-L1 blockade treatment via the ADORA1-ATF3 axis. In conclusion, our study identified these alkaloids as promising candidates for the treatment of NSCLC, either alone or in combination with ICB, with potential value for drug development and may provide a promising strategy for improving the survival of NSCLC patients.

Systems-level analysis identifies key regulators driving epileptogenesis in temporal lobe epilepsy.

Temporal lobe epilepsy (TLE) is the most prevalent and often devastating form of epilepsy. The molecular mechanism underlying the development of TLE remains largely unclear, which hinders the discovery of effective antiepileptogenic drugs. Here we adopted a systems-level approach integrating transcriptomic profiles of three epileptogenesis stages to identify key regulators underlying epilepsy progression. Associating stage-specific gene meta-signatures with brain cell-specialized modules revealed positive regulation of glial migration and adhesion, cytokine production, and neuron death, and downregulation of synaptic transmission and ion transport during epileptogenesis. We identified 265 key regulators driving these processes and 72 of them were demonstrated associating with seizure frequency and/or hippocampal sclerosis in human TLE. Importantly, the upregulation of FAM107A, LAMB2, LTBP1 and TGIF1, which are mainly involved in nervous system development, were found contributing to both conditions. Our findings present the evolution landscape of epileptogenesis and provide candidate regulators that may serve as potential antiepileptogenic targets.

Weak-binding molecules are not drugs?-toward a systematic strategy for finding effective weak-binding drugs.

Designing maximally selective ligands that act on individual drug targets with high binding affinity has been the central dogma of drug discovery and development for the past two decades. However, many low-affinity drugs that aim for several targets at the same time are found more effective than the high-affinity binders when faced with complex disease conditions, such as cancers, Alzheimer's disease and cardiovascular diseases. The aim of this study was to appreciate the importance and reveal the features of weak-binding drugs and propose an integrated strategy for discovering them. Weak-binding drugs can be characterized by their high dissociation rates and transient interactions with their targets. In addition, network topologies and dynamics parameters involved in the targets of weak-binding drugs also influence the effects of the drugs. Here, we first performed a dynamics analysis for 33 elementary subgraphs to determine the desirable topology and dynamics parameters among targets. Then, by applying the elementary subgraphs to the mitogen-activated protein kinase (MAPK) pathway, several optimal target combinations were obtained. Combining drug-target interaction prediction with molecular dynamics simulation, we got two potential weak-binding drug candidates, luteolin and tanshinone IIA, acting on these targets. Further, the binding affinity of these two compounds to their targets and the anti-inflammatory effects of them were validated through in vitro experiments. In conclusion, weak-binding drugs have real opportunities for maximum efficiency and may show reduced adverse reactions, which can offer a bright and promising future for new drug discovery.

System-Pharmacology Dissection of Traditional Chinese herbs SINI Decoction for Treatment of Cardiovascular Diseases.

Abstract: Cardiovascular diseases (CVDs) are leading causes of death in the world, owing to noticeable incidence and mortality. Traditional Chinese Medicine (TCM) SINI Decoction (SND) is used to prevent and treat CVDs, which has attracted extensive attention for its moderate and little side effects. However, the involved molecular mechanisms are exceedingly complicated and remain unclear. Systems pharmacology, as a novel approach that integrates systems biology and pharmacology plays a significant role in investigating the molecular mechanism of TCM. In systems pharmacology approach, we use to systematically uncover the mechanisms of action in Chinese medicinal formula SND as an effective treatment for CVDs, which mainly includes:1) molecular database building; 2) ADME evaluation; 3) target-fishing 4) network construction and analysis. The results show that 78 underlying valid ingredients and their corresponding 71 direct targets of SND were obtained. And SND take part in cardiomyocyte protection, blood pressure regulation, and lipid regulation module in treatment of CVDs by cooperative way. Systems pharmacology as an emerging field that investigates the molecular mechanisms of TCM through pharmacokinetic evaluation target prediction, and pathway analysis, which will facilitate the development of traditional Chinese herbs in modern medicine.

Identification of Early Salinity Stress-Responsive Proteins in Dunaliella salina by isobaric tags for relative and absolute quantitation (iTRAQ)-Based Quantitative Proteomic Analysis.

Salt stress is one of the most serious abiotic factors that inhibit plant growth. Dunaliella salina has been recognized as a model organism for stress response research due to its high capacity to tolerate extreme salt stress. A proteomic approach based on isobaric tags for relative and absolute quantitation (iTRAQ) was used to analyze the proteome of D. salina during early response to salt stress and identify the differentially abundant proteins (DAPs). A total of 141 DAPs were identified in salt-treated samples, including 75 upregulated and 66 downregulated DAPs after 3 and 24 h of salt stress. DAPs were annotated and classified into gene ontology functional groups. The Kyoto Encyclopedia of Genes and Genomes pathway analysis linked DAPs to tricarboxylic acid cycle, photosynthesis and oxidative phosphorylation. Using search tool for the retrieval of interacting genes (STRING) software, regulatory protein⁻protein interaction (PPI) networks of the DAPs containing 33 and 52 nodes were built at each time point, which showed that photosynthesis and ATP synthesis were crucial for the modulation of early salinity-responsive pathways. The corresponding transcript levels of five DAPs were quantified by quantitative real-time polymerase chain reaction (qRT-PCR). These results presented an overview of the systematic molecular response to salt stress. This study revealed a complex regulatory mechanism of early salt tolerance in D. salina and potentially contributes to developing strategies to improve stress resilience.

Elucidation of the Anti-Inflammatory Mechanisms of Bupleuri and Scutellariae Radix Using System Pharmacological Analyses.

Objective. This study was aimed at elucidating the molecular mechanisms underlying the anti-inflammatory effect of the combined application of Bupleuri Radix and Scutellariae Radix and explored the potential therapeutic efficacy of these two drugs on inflammation-related diseases. Methods. After searching the databases, we collected the active ingredients of Bupleuri Radix and Scutellariae Radix and calculated their oral bioavailability (OB) and drug-likeness (DL) based on the absorption-distribution-metabolism-elimination (ADME) model. In addition, we predicted the drug targets of the selected active components based on weighted ensemble similarity (WES) and used them to construct a drug-target network. Gene ontology (GO) analysis and KEGG mapper tools were performed on these predicted target genes. Results. We obtained 30 compounds from Bupleuri Radix and Scutellariae Radix of good quality as indicated by ADME assays, which possess potential pharmacological activity. These 30 ingredients have a total of 121 potential target genes, which are involved in 24 biological processes related to inflammation. Conclusions. Combined application of Bupleuri Radix and Scutellariae Radix was found not only to directly inhibit the synthesis and release of inflammatory cytokines, but also to have potential therapeutic effects against inflammation-induced pain. In addition, a combination therapy of these two drugs exhibited systemic treatment efficacy and provided a theoretical basis for the development of drugs against inflammatory diseases.

Large-scale exploration and analysis of drug combinations.

MOTIVATION: Drug combinations are a promising strategy for combating complex diseases by improving the efficacy and reducing corresponding side effects. Currently, a widely studied problem in pharmacology is to predict effective drug combinations, either through empirically screening in clinic or pure experimental trials. However, the large-scale prediction of drug combination by a systems method is rarely considered. RESULTS: We report a systems pharmacology framework to predict drug combinations (PreDCs) on a computational model, termed probability ensemble approach (PEA), for analysis of both the efficacy and adverse effects of drug combinations. First, a Bayesian network integrating with a similarity algorithm is developed to model the combinations from drug molecular and pharmacological phenotypes, and the predictions are then assessed with both clinical efficacy and adverse effects. It is illustrated that PEA can predict the combination efficacy of drugs spanning different therapeutic classes with high specificity and sensitivity (AUC = 0.90), which was further validated by independent data or new experimental assays. PEA also evaluates the adverse effects (AUC = 0.95) quantitatively and detects the therapeutic indications for drug combinations. Finally, the PreDC database includes 1571 known and 3269 predicted optimal combinations as well as their potential side effects and therapeutic indications. AVAILABILITY AND IMPLEMENTATION: The PreDC database is available at http://sm.nwsuaf.edu.cn/lsp/predc.php.

Molecular interactions between metformin and D-limonene inhibit proliferation and promote apoptosis in breast and liver cancer cells.

BACKGROUND: Cancer is a fatal disease that severely affects humans. Designing new anticancer strategies and understanding the mechanism of action of anticancer agents is imperative. HYPOTHESIS/PURPOSE: In this study, we evaluated the utility of metformin and D-limonene, alone or in combination, as potential anticancer therapeutics using the human liver and breast cancer cell lines HepG2 and MCF-7. STUDY DESIGN: An integrated systems pharmacology approach is presented for illustrating the molecular interactions between metformin and D-limonene. METHODS: We applied a systems-based analysis to introduce a drug-target-pathway network that clarifies different mechanisms of treatment. The combination treatment of metformin and D-limonene induced apoptosis in both cell lines compared with single drug treatments, as indicated by flow cytometric and gene expression analysis. RESULTS: The mRNA expression of Bax and P53 genes were significantly upregulated while Bcl-2, iNOS, and Cox-2 were significantly downregulated in all treatment groups compared with normal cells. The percentages of late apoptotic HepG2 and MCF-7 cells were higher in all treatment groups, particularly in the combination treatment group. Calculations for the combination index (CI) revealed a synergistic effect between both drugs for HepG2 cells (CI = 0.14) and MCF-7 cells (CI = 0.22). CONCLUSION: Our data show that metformin, D-limonene, and their combinations exerted significant antitumor effects on the cancer cell lines by inducing apoptosis and modulating the expression of apoptotic genes.

Santalum album L. alleviates cardiac function injury in heart failure by synergistically inhibiting inflammation, oxidative stress and apoptosis through multiple components.

BACKGROUND: Heart failure (HF) is a complex cardiovascular syndrome with high mortality. Santalum album L. (SAL) is a traditional Chinese medicine broadly applied for various diseases treatment including HF. However, the potential active compounds and molecular mechanisms of SAL in HF treatment are not well understood. METHODS: The active compounds and possible mechanisms of action of SAL were analyzed and validated by a systems pharmacology framework and an ISO-induced mouse HF model. RESULTS: We initially confirmed that SAL alleviates heart damage in ISO-induced HF model. A total of 17 potentially active components in SAL were identified, with Luteolin (Lut) and Syringaldehyde (SYD) in SAL been identified as the most effective combination through probabilistic ensemble aggregation (PEA) analysis. These compounds, individually and in their combination (COMB), showed significant therapeutic effects on HF by targeting multiple pathways involved in anti-oxidation, anti-inflammation, and anti-apoptosis. The active ingredients in SAL effectively suppressed inflammatory mediators and pro-apoptotic proteins while enhancing the expression of anti-apoptotic factors and antioxidant markers. Furthermore, the synergistic effects of SAL on YAP and PI3K-AKT signaling pathways were further elucidated. CONCLUSIONS: Mechanistically, the anti-HF effect of SAL is responsible for the synergistic effect of anti-inflammation, antioxidation and anti-apoptosis, delineating a multi-targeted therapeutic strategy for HF.

High dose isoleucine stabilizes nuclear PTEN to suppress the proliferation of lung cancer.

PURPOSE: Cancer cells require a supply of amino acids, particularly essential amino acids such as branched-chain amino acids (BCAAs, i.e., valine, leucine, and isoleucine), to meet the increased nutrient demands of malignant tumors. The cell-autonomous and non-autonomous roles of altered BCAA supply have been implicated in cancer progression. The critical proteins involved in BCAA uptake, transport, metabolism, etc. serve as potential therapeutic biomarkers in human cancers. Here, we summarize the potential anti-tumor mechanism of BCAA by exploring the chain reaction triggered by increased BCAA supply in the tumor. METHOD: A system-wide strategy was employed to provide a generic solution to establish the links between BCAA and cancer based on comprehensive omics, molecular experimentation, and data analysis. RESULTS: BCAA over-supplementation (900 mg/kg) significantly inhibited tumor growth and reduced tumor burden, with isoleucine having the most pronounced effect. Surprisingly, isoleucine inhibited tumor growth independently of mTORC1 activation, a classical amino acid sensor. Exploratory transcriptome analysis revealed that Phosphatase and tensin homolog (PTEN) is the critical factor in the anti-tumor effect of isoleucine. By inhibiting PTEN ubiquitination, isoleucine can promote PTEN nuclear import and maintain PTEN nuclear stability. Interestingly, this process was regulated by isoleucine-tRNA ligase, cytoplasmic (IARS), a direct target of isoleucine. We demonstrated the enhanced interaction between IARS and PTEN in the presence of excess isoleucine. At the same time, IARS knockout leads to loss of isoleucine tumor suppressor ability. CONCLUSION: Overall, our results provide insights into the regulation of the IARS-PTEN anti-tumor axis by isoleucine and reveal a unique therapeutic approach based on enhancing cellular isoleucine supply.

Centella asiatica (L.) Urb. attenuates cardiac hypertrophy and improves heart function through multi-level mechanisms revealed by systems pharmacology.

ETHNOPHARMACOLOGICAL RELEVANCE: Cardiac hypertrophy (CH) is an incurable heart disease, contributing to an increased risk of heart failure due to the lack of safe and effective strategies. Therefore, searching for new approaches to treat CH is urgent. Centella asiatica (L.) Urb. (CA), a traditional food and medicinal natural plant, has been turned out to be effective in the treatment of cardiovascular disease, but its efficacy and potential mechanisms in alleviating CH have not yet been investigated. AIM OF STUDY: In this study, we aimed to elucidate the multi-level mechanisms underlying the effect of CA against CH. STUDY DESIGN AND METHODS: A systems pharmacology approach was employed to screen active ingredients, identify potential targets, construct visual networks and systematically investigate the pathways and mechanisms of CA for CH treatment. The cardiac therapeutic potential and mechanism of action of CA on CH were verified with in vivo and in vitro experiments. RESULTS: Firstly, we demonstrated the therapeutic effect of CA on CH and then screened 13 active compounds of CA according to the pharmacokinetic properties. Then, asiatic acid (AA) was identified as the major active molecule of CA for CH treatment. Afterwards, network and functional enrichment analyses showed that CA exerted cardioprotective effects by modulating multiple pathways mainly involved in anti-apoptotic, antioxidant and anti-inflammatory processes. Finally, in vivo, the therapeutic effects of AA and its action on the YAP/PI3K/AKT axis and NF-κB signaling pathway were validated using an isoproterenol-induced CH mouse model. In vitro, AA decreased ROS levels in hydrogen peroxide-treated HL-1 cells. CONCLUSION: Overall, the multi-level mechanisms of CA for CH treatment were demonstrated by systems pharmacology approach, which provides a paradigm for systematically deciphering the mechanisms of action of natural plants in the treatment of diseases and offers a new idea for the development of medicinal and food products.

Pan-Cancer Analyses Reveal Oncogenic Role and Prognostic Value of F-Box Only Protein 22.

The F-box protein 22 (FBXO22), an F-box E3 ligase, has been identified to be critically involved in carcinogenesis. However, a systematic assessment of the role of FBXO22 across human cancers is lacking. Here, we performed a pan-cancer analysis to explore the role of FBXO22 in 33 cancer types using multiomic data from The Cancer Genome Atlas (TCGA). First, we found that high FBXO22 expression in multiple cancers was closely associated with poor overall survival and relapse-free survival. Next, we identified ten proteins that interact with FBXO22 and 13 of its target substrates using the STRING database and a literature search to explore the regulatory role of FBXO22 in tumorigenesis. Genes encoding these proteins were found to be significantly enriched in cell cycle negative regulation and ubiquitination pathways. This was confirmed in nonsmall cell lung cancer A549 cells, where FBXO22 overexpression enhanced cyclin-dependent kinase 4 (CDK4) protein levels and promoted cell proliferation. Similarly, overexpression or interference of FBXO22 changed the protein level of one of its substrates, PTEN. Additionally, we found that FBXO22 mutations were accompanied by altered substrate expression, especially in uterine corpus endometrial carcinoma and lung adenocarcinoma; endometrial carcinoma patients with FBXO22 genetic alterations also had better overall and relapse-free survival. Notably, FBXO22 methylation levels were also decreased in most tumors, and hypomethylation of FBXO22 was associated with poor overall survival, relapse-free interval, and progression-free interval in pancreatic adenocarcinoma. Finally, we analyzed the correlation between the abundance of tumor infiltrating lymphocytes (TILs) and FBXO22 expression, copy number variation, and methylation. Multiple algorithms revealed that high FBXO22 expression was associated with lower TIL levels, especially in lung adenocarcinoma, lung squamous cell carcinoma, and sarcoma. Taken together, our findings demonstrate that FBXO22 degrades tumor suppressor genes by ubiquitination and inhibits the cell cycle to promote nonsmall cell lung cancer progression. Our study also provides a relatively comprehensive understanding of the oncogenic role of FBXO22 in different tumors.

NOGEA: A Network-oriented Gene Entropy Approach for Dissecting Disease Comorbidity and Drug Repositioning.

Rapid development of high-throughput technologies has permitted the identification of an increasing number of disease-associated genes (DAGs), which are important for understanding disease initiation and developing precision therapeutics. However, DAGs often contain large amounts of redundant or false positive information, leading to difficulties in quantifying and prioritizing potential relationships between these DAGs and human diseases. In this study, a network-oriented gene entropy approach (NOGEA) is proposed for accurately inferring master genes that contribute to specific diseases by quantitatively calculating their perturbation abilities on directed disease-specific gene networks. In addition, we confirmed that the master genes identified by NOGEA have a high reliability for predicting disease-specific initiation events and progression risk. Master genes may also be used to extract the underlying information of different diseases, thus revealing mechanisms of disease comorbidity. More importantly, approved therapeutic targets are topologically localized in a small neighborhood of master genes in the interactome network, which provides a new way for predicting drug-disease associations. Through this method, 11 old drugs were newly identified and predicted to be effective for treating pancreatic cancer and then validated by in vitro experiments. Collectively, the NOGEA was useful for identifying master genes that control disease initiation and co-occurrence, thus providing a valuable strategy for drug efficacy screening and repositioning. NOGEA codes are publicly available at https://github.com/guozihuaa/NOGEA.

Effects of seasonal variation on the biology and morphology of the dusky cotton bug, Oxcarenus laetus (Kirby).

The dusky cotton bug (Oxycarenus laetus, KIRBY) a pest of several crops. The effects of winter and summer on the biology and morphology was investigated. The sampled eggs of dusky cotton bug (DCB) were kept under controlled environment for biological and morphological investigations. In winter, the mating duration of DCB was observed longer significantly (74.2 days), egg development period (3.93 days), an egg laying period (3.6 days) and hatching period (6.66 days) noted longer in winter season. Interestingly, average number of hatched egg (16.8 days) observed significantly higher in summer and the percentage of the hatching of eggs (81.95%) were also observed higher in summer as compare to winter. Whereas, the longevity of all nymph stages in winter longer days as compare to summer nymph stages. Moreover, differences were also observed between male and female development days between winter and summer. In the winter, female DCB development was suggestively higher as compare to summer (24 days). Whereas, the developmental days were noted considerably more in winter for males as compare to summer (14.93 days). On other hand, for morphological parameters, no differences were observed between winter and summer population of DCB.

Systems pharmacology reveals the multi-level synergetic mechanism of action of Ginkgo biloba L. leaves for cardiomyopathy treatment.

ETHNOPHARMACOLOGICAL RELEVANCE: Cardiomyopathy is a common cause of heart failure and may lead to increased risk of sudden cardiac death, lacking simple, safe and effective treatment strategies due to unclear pathogenesis. Ginkgo biloba L. leaves (GBLs), a traditional Chinese medicine (TCM), has been widely used in clinical medicine for improving blood circulation, and was demonstrated to be effective on cardiomyopathy in preclinical studies. However, because of the widely known holistic therapeutic philosophy via multi-target and multi-pathway effect for most TCMs, to explore its underlying molecular mechanisms of action (MoA) remains a great challenge. AIM OF STUDY: Decipher the underlying MoA of GBLs for cardiomyopathy treatment: Study design and methods: An integrated systems pharmacology framework was employed to screen potential active compounds, identify therapeutic targets, explore the action pathways and verify mechanisms of GBLs with in vitro experiments. RESULTS: We firstly confirmed the therapeutic effect of GBLs on cardiomyopathy and subsequently screened 27 active compounds from GBLs according to their pharmacokinetic properties. Then Probability Ensemble Approach was applied to identify the compound combinations that exert synergetic effect from GBLs. Network analysis and functional enrichment analysis demonstrated that these compounds exhibit synergistic therapeutic effect by acting on multiple targets and thereby regulating multiple pathways mainly involved in pro-survival, anti-apoptotic and anti-inflammatory processes. Finally, using a doxorubicin-induced myocardial injury model, therapeutic effect of ginkgolide A, ginkgolide B, isorhamnetin, as well as their synergistic effect on PI3K-AKT and NF-κB signaling pathways were validated in vitro. Importantly, we demonstrated that Ginkgo diterpene lactone meglumine injection (GDJ), an approved injection derived from GBLs, could be a promising agent for cardiomyopathy treatment. CONCLUSION: Collectively, the multi-level synergetic mechanism of GBLs on cardiomyopathy treatment was demonstrated with systems pharmacology approach, providing a paradigm for deciphering the complicated MoA of TCMs.

Systematic Evaluation of the Diagnostic and Prognostic Significance of Competitive Endogenous RNA Networks in Prostate Cancer.

Long non-coding RNA (lncRNA)-mediated competitive endogenous RNA (ceRNA) networks act as essential mechanisms in tumor initiation and progression, but their diagnostic and prognostic significance in prostate cancer (PCa) remains poorly understood. Presently, using the RNA expression data derived from multiple independent PCa-related studies, we constructed a high confidence and PCa-specific core ceRNA network by employing three lncRNA-gene inference approaches and key node filter strategies and then established a logistic model and risk score formula to evaluate its diagnostic and prognostic values, respectively. The core ceRNA network consists of 10 nodes, all of which are significantly associated with clinical outcomes. Combination of expression of the 10 ceRNAs with a logistic model achieved AUC of ROC and PR curve up to ∼96 and 99% in excluding normal prostate samples, respectively. Additionally, a risk score formula constructed with the ceRNAs exhibited significant association with disease-free survival. More importantly, utilizing the expression of RNAs in the core ceRNA network as a molecular signature, the TCGA-PRAD cohort was divided into four novel clinically relevant subgroups with distinct expression patterns, highlighting a feasible way for improving patient stratification in the future. Overall, we constructed a PCa-specific core ceRNA network, which provides diagnostic and prognostic value.

Systems-Mapping of Herbal Effects on Complex Diseases Using the Network-Perturbation Signatures.

The herbs have proven to hold great potential to improve people's health and wellness during clinical practice over the past millennia. However, herbal medicine for the personalized treatment of disease is still under investigation owing to the complex multi-component interactions in herbs. To reveal the valuable insights for herbal synergistic therapy, we have chosen Traditional Chinese Medicine (TCM) as a case to illustrate the art and science behind the complicated multi-molecular, multi-genes interaction systems, and how the good practices of herbal combination therapy are applicable to personalized treatment. Here, we design system-wide interaction map strategy to provide a generic solution to establish the links between diseases and herbs based on comprehensive testing of molecular signatures in herb-disease pairs. Firstly, we integrated gene expression profiles from 189 diseases to characterize the disease-pathological feature. Then, we generated the perturbation signatures from the huge chemical informatics data and pharmacological data for each herb, which were represented the targets affected by the ingredients in the herb. So that we could assess the effects of herbs on the individual. Finally, we integrated the data of 189 diseases and 502 herbs, yielding the optimal herbal combinations for the diseases based on the strategy, and verifying the reliability of the strategy through the permutation testing and literature verification. Furthermore, we propose a novel formula as a candidate therapeutic drugs of rheumatoid arthritis and demonstrate its therapeutic mechanism through the systematic analysis of the influencing targets and biological processes. Overall, this computational method provides a systematic approach, which blended herbal medicine and omics data sets, allowing for the development of novel drug combinations for complex human diseases.

Clarifying of the potential mechanism of Sinisan formula for treatment of chronic hepatitis by systems pharmacology method.

Chronic hepatitis is a general designation class of diseases, which results in different degrees of liver necrosis and inflammatory reaction, followed by liver fibrosis, may eventually develop into cirrhosis. However, the molecular pathogenesis of chronic hepatitis is too complex to elucidate. Herbal medicines, featured with multiple targets and compounds, have long displayed therapeutic effect in treating chronic hepatitis, though their molecular mechanisms of contribution remain indistinct. This research utilized the network pharmacology to confirm the molecular pathogenesis of chronic hepatitis through providing a comprehensive analysis of active chemicals, drug targets and pathways' interaction of Sinisan formula for treating chronic hepatitis. The outcomes showed that 80 active ingredients of Sinisan formula interacting with 91 therapeutic proteins were authenticated. Sinisan formula potentially participates in immune modulation, anti-inflammatory and antiviral activities, even has regulating effects on lipid metabolism. These mechanisms directly or indirectly are involved in curing chronic hepatitis by an interaction way. The network pharmacology based analysis demonstrated that Sinisan has multi-scale curative activity in regulating chronic hepatitis related biological processes, which provides a new potential way for modern medicine in the treatment of chronic diseases.

Correction to: dengue virus causes changes of MicroRNA-genes regulatory network revealing potential targets for antiviral drugs.

After publication of the article [1], it has been brought to our attention that an author's name was spelt incorrectly in the original published article. Yonghua Wang was previously spelt "Yonghua Wan". This has now been corrected in the revised version of the article.

Dengue virus causes changes of MicroRNA-genes regulatory network revealing potential targets for antiviral drugs.

BACKGROUND: Dengue virus (DENV) is an increasing global health threat and associated with induction of both a long-lived protective immune response and immune-suppression. So far, the potency of treatment of DENV via antiviral drugs is still under investigation. Recently, increasing evidences suggest the potential role of microRNAs (miRNAs) in regulating DENV. The present study focused on the function of miRNAs in innate insusceptible reactions and organization of various types of immune cells and inflammatory responses for DENV. Three drugs were tested including antiviral herbal medicine ReDuNing (RDN), Loratadine (LRD) and Acetaminophen. RESULTS: By the microarray expression of miRNAs in 165 Patients. Results showed that 89 active miRNAs interacted with 499 potential target genes, during antiviral treatment throughout the critical stage of DENV. Interestingly, reduction of the illness threats using RDN combined with LRD treatment showed better results than Acetaminophen alone. The inhibitions of DENV was confirmed by decrease concentrations of cytokines and interleukin parameters; like TNF-α, IFN-γ, TGF-ß1, IL-4, IL-6, IL-12, and IL-17; after treatment and some coagulants factors increased. CONCLUSIONS: This study showed a preliminary support to suggest that the herbal medicine RDN combined with LRD can reduce both susceptibility and the severity of DENV.