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.

Systems Pharmacology Dissection of the Integrated Treatment for Cardiovascular and Gastrointestinal Disorders by Traditional Chinese Medicine.

Though cardiovascular diseases (CVDs) and gastrointestinal disorders (GIDs) are different diseases associated with different organs, they are highly correlated clinically. Importantly, in Traditional Chinese Medicine (TCM), similar treatment strategies have been applied in both diseases. However, the etiological mechanisms underlying them remain unclear. Here, an integrated systems pharmacology approach is presented for illustrating the molecular correlations between CVDs and GIDs. Firstly, we identified pairs of genes that are associated with CVDs and GIDs and found that these genes are functionally related. Then, the association between 115 heart meridian (HM) herbs and 163 stomach meridian (SM) herbs and their combination application in Chinese patent medicine was investigated, implying that both CVDs and GIDs can be treated by the same strategy. Exemplified by a classical formula Sanhe Decoration (SHD) treating chronic gastritis, we applied systems-based analysis to introduce a drug-target-pathway-organ network that clarifies mechanisms of different diseases being treated by the same strategy. The results indicate that SHD regulated several pathological processes involved in both CVDs and GIDs. We experimentally confirmed the predictions implied by the effect of SHD for myocardial ischemia. The systems pharmacology suggests a novel integrated strategy for rational drug development for complex associated diseases.

A novel systems pharmacology platform to dissect action mechanisms of traditional Chinese medicines for bovine viral diarrhea disease.

Due to the large direct and indirect productivity losses in the livestock industry caused by bovine viral diarrhea (BVD) and the lack of effective pharmacological therapies, developing an efficient treatment is extremely urgent. Traditional Chinese medicines (TCMs) that simultaneously address multiple targets have been proven to be effective therapies for BVD. However, the potential molecular action mechanisms of TCMs have not yet been systematically explored. In this work, take the example of a herbal remedy Huangqin Zhizi (HQZZ) for BVD treatment in China, a systems pharmacology approach combining with the pharmacokinetics and pharmacodynamics evaluation was developed to screen out the active ingredients, predict the targets and analyze the networks and pathways. Results show that 212 active compounds were identified. Utilizing these lead compounds as probes, we predicted 122 BVD related-targets. And in vitro experiments were conducted to evaluate the reliability of some vital active compounds and targets. Network and pathway analysis displayed that HQZZ was effective in the treatment of BVD by inhibiting inflammation, enhancing immune responses in hosts toward virus infection. In summary, the analysis of the complete profile of the pharmacological activities, as well as the elucidation of targets, networks and pathways can further elucidate the underlying anti-inflammatory, antiviral and immune regulation mechanisms of HQZZ against BVD.

Polypharmacology in Drug Discovery: A Review from Systems Pharmacology Perspective.

BACKGROUND: The complexity of diseases has led to recent interest in polypharmacology, which suggests that many effective drugs specially modulate multiple targets. Drugs with multiple targets can provide a superior therapeutic effect and decrease in side effect profile compared to ligands with single target, especially in the treatment of complex diseases, such as tumors, nervous system diseases and inflammatory diseases. The network-based polypharmacology holds the promise of expanding the opportunity for novel targets and drug identification. However, it faces considerable challenges to how multi-target drugs can be rationally designed from the network pharmacology perspective, particularly for combinations of targets that are structurally divergent. METHODS: In this review, we focus on the pharmacological properties of current polypharmacology, discuss potential novel drug indication arising from drug repurposing, and introduce approaches to the rational design of multi-target drugs. RESULTS: As a result, we highlighted the features of polypharmacology. Also, we have presented some computational methods to predict the potential novel multi-target drugs with lower toxicity and higher efficacy. Moreover, network analysis might play important role in repositioning drugs that modulate targets involved in different pathologies. CONCLUSION: This perspective aims to provide a global view on polypharmacology, which is the foundation of the next paradigm in drug discovery.

Pred-binding: large-scale protein-ligand binding affinity prediction.

Drug target interactions (DTIs) are crucial in pharmacology and drug discovery. Presently, experimental determination of compound-protein interactions remains challenging because of funding investment and difficulties of purifying proteins. In this study, we proposed two in silico models based on support vector machine (SVM) and random forest (RF), using 1589 molecular descriptors and 1080 protein descriptors in 9948 ligand-protein pairs to predict DTIs that were quantified by Ki values. The cross-validation coefficient of determination of 0.6079 for SVM and 0.6267 for RF were obtained, respectively. In addition, the two-dimensional (2D) autocorrelation, topological charge indices and three-dimensional (3D)-MoRSE descriptors of compounds, the autocorrelation descriptors and the amphiphilic pseudo-amino acid composition of protein are found most important for Ki predictions. These models provide a new opportunity for the prediction of ligand-receptor interactions that will facilitate the target discovery and toxicity evaluation in drug development.

CancerHSP: anticancer herbs database of systems pharmacology.

The numerous natural products and their bioactivity potentially afford an extraordinary resource for new drug discovery and have been employed in cancer treatment. However, the underlying pharmacological mechanisms of most natural anticancer compounds remain elusive, which has become one of the major obstacles in developing novel effective anticancer agents. Here, to address these unmet needs, we developed an anticancer herbs database of systems pharmacology (CancerHSP), which records anticancer herbs related information through manual curation. Currently, CancerHSP contains 2439 anticancer herbal medicines with 3575 anticancer ingredients. For each ingredient, the molecular structure and nine key ADME parameters are provided. Moreover, we also provide the anticancer activities of these compounds based on 492 different cancer cell lines. Further, the protein targets of the compounds are predicted by state-of-art methods or collected from literatures. CancerHSP will help reveal the molecular mechanisms of natural anticancer products and accelerate anticancer drug development, especially facilitate future investigations on drug repositioning and drug discovery. CancerHSP is freely available on the web at http://lsp.nwsuaf.edu.cn/CancerHSP.php.