A chemoinformatics and bioinformatics resource
Tutorial and training materials by OpenHelix
|Learn to use DrugBank, a free, web-based tool that combines chemoinformatics with bioinformatics. Explore both the chemical and biological nature of drugs in silico using DrugCards, the functional units of DrugBank. Each DrugCard represents a unique drug in the database and contains over 100 information fields collated from numerous scientific sources. DrugCards provide extensive information on approved drugs, biotech drugs, small molecules, experimental drugs, and nutraceuticals, yet DrugCards are easy to read and shuffle through. You can query DrugBank with either chemical or biological terms, including the protein targets of drugs or the enzymes that metabolize them. A new feature correlates genetic single nucleotide polymorphisms with adverse drug reactions and drug effectiveness. Ideal for the student, scientist, drug discoverer, clinician, pharmacist, or general public, DrugBank will help you find the answers to your questions about pharmaceuticals and their underlying biological effects.|
- to understand and interpret DrugCard data
- how to query and browse through DrugBank information
- how to perform basic searches for specific drug information
- to perform advanced queries via text, sequence, chemistry, structure, and other parameters
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Recent BioMed Central research articles citing this resource
Russo Francesco et al., A knowledge base for the discovery of function, diagnostic potential and drug effects on cellular and extracellular miRNAs Italian Society of Bioinformatics (BITS): Annual Meeting 2013: Genomics Tenth Annual Meeting of the Italian Society of Bioinformatics (BITS). BMC Genomics (2014) doi:10.1186/1471-2164-15-S3-S4
Liu Ruifeng et al., Exploiting large-scale drug-protein interaction information for computational drug repurposing Knowledge-based analysis. BMC Bioinformatics (2014) doi:10.1186/1471-2105-15-210
Baier Herbert et al., ISAAC - InterSpecies Analysing Application using Containers Sequence analysis (applications). BMC Bioinformatics (2014) doi:10.1186/1471-2105-15-18
Srinivasan Bharath et al., Experimental validation of FINDSITE comb virtual ligand screening results for eight proteins yields novel nanomolar and micromolar binders. Journal of Cheminformatics (2014) doi:10.1186/1758-2946-6-16
Mesiti Marco et al., Think globally and solve locally: secondary memory-based network learning for automated multi-species function prediction. GigaScience (2014) doi:10.1186/2047-217X-3-5
More about the resource:
DrugBank is developed by David Wisharts group in the Departments of Computing Science and Biological Sciences at the University of Alberta in Edmonton, Alberta. One of the most unique features of DrugBank is that it combines detailed drug information with drug target information. It contains nearly 5000 drug entries including FDA-approved drugs, nutraceuticals, and experimental drugs. This comprehensive resource bridges the gap between clinically-oriented and chemically-oriented drug databases by combining in depth knowledge about drugs and their targets with more chemical-based tools allowing for image, sequence and structure analysis.
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Copyright 2009, OpenHelix, LLC.