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
Atreya V Ravi et al., Exploring drug-target interaction networks of illicit drugs Selected articles from the IEEE International Conference on Bioinformatics and Biomedicine 2012: Genomics IEEE International Conference on Bioinformatics and Biomedicine 2012. BMC Genomics (2013) doi:10.1186/1471-2164-14-S4-S1
Lee Minho et al., Interaction network among functional drug groups Twelfth International Conference on Bioinformatics (InCoB2013): Systems Biology Asia Pacific Bioinformatics Network (APBioNet) Twelfth International Conference on Bioinformatics (InCoB2013). BMC Systems Biology (2013) doi:10.1186/1752-0509-7-S3-S4
Ran Jihua et al., Construction and analysis of the protein-protein interaction network related to essential hypertension Networks and information flow. BMC Systems Biology (2013) doi:10.1186/1752-0509-7-32
Molineris Ivan et al., Drug repositioning for orphan genetic diseases through Conserved Anticoexpressed Gene Clusters (CAGCs) Transcriptome analysis. BMC Bioinformatics (2013) doi:10.1186/1471-2105-14-288
George Priya Doss C et al., Extrapolating the effect of deleterious nsSNPs in the binding adaptability of flavopiridol with CDK7 protein: a molecular dynamics approach. Human Genomics (2013) doi:10.1186/1479-7364-7-10
More about the resource:
DrugBank is developed by David Wishart’s 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.