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systemsDock
A web service enabling drug developers to carry out network pharmacology-based prediction and analysis by integrating results from structural biology with systems biology. Its user-friendly GUI interface simplifies essential operations for large-scale screening. Using the predictive docking approach, systemsDock can test a large number of target proteins with good prediction accuracy. This will reduce the number of tests for bioassay. Together with a curated pathway map, systemsDock helps to comprehensively characterize the underlying mechanism of a drug candidate and to interpret its cascading effects, improving the prediction of drug efficacy and safety.
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TarNet
Obsolete
A manually curated database and platform of traditional medicinal plants with natural compounds that includes potential bio-target information. We gathered information on proteins that are related to or affected by medicinal plant ingredients and data on protein-protein interactions (PPIs). TarNet includes in-depth information on both plant-compound-protein relationships and PPIs. Additionally, TarNet can provide researchers with network construction analyses of biological pathways and PPIs associated with specific diseases. Researchers can upload a gene or protein list mapped to our PPI database that has been manually curated to generate relevant networks. Multiple functions are accessible for network topological calculations, subnetwork analyses, pathway analyses, and compound-protein relationships.
C(2)Maps
Obsolete
An online bioinformatics resource that provides biologists with directional relationships between drugs and genes/proteins in specific disease contexts based on network mining, literature mining, and drug effect annotating. C2Maps is based on the concept of network pharmacology by examining many drugs at the same time and studying the drug disease relationship based on the underlying protein interaction network instead of drugs' direct target. C2Maps provides quantitative measurements of protein's and drug's relevance to a specific disease by applying networking mining and the statistical testing methods in text mining and thus offers new insight to assess overall drug efficacy and toxicity. The case study on breast cancer correlates very well with the existing pharmacology of the two breast cancer drugs and highlights the significance of C2Maps database.
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