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.

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.

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.

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.

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.

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.