provides navigation hyperlinks to >70 drug classes, which in turn list the FDA-approved drugs associated with the drugs. Each drug name is then linked to its respective DrugCard. A key distinguishing feature of DrugBank from other on- line drug resources is its extensive support for higher level database searching and selecting functions. In addition to the data viewing and sorting features already described, Drug- Bank also offers a local BLAST (8) search that supports both single and multiple sequence queries, a boolean text search [using GLIMPSE; (9)], a chemical structure search utility and a relational data extraction tool (10). These can all be accessed via the database navigation bar located at the top of every DrugBank page. The BLAST search (SeqSearch) is particularly useful as it can potentially allow users to quickly and simply identify drug leads from newly sequenced pathogens. Speciﬁcally, a new sequence, a group of sequences or even an entire proteome can be searched against DrugBank’s database of known drug target sequences by pasting the FASTA formatted sequence (or sequences) into the SeqSearch query box and pressing the ‘submit’ button. A signiﬁcant hit reveals, through the associ- ated DrugCard hyperlink, the name(s) or chemical structure(s) of potential drug leads that may act on that query protein (or proteome). DrugBank’s structure similarity search tool (ChemQuery) can be used in a similar manner to its sequence search tools. Users may sketch (through ACD’s freely available chemical sketching applet) or paste a SMILES string (11) of a possible lead compound into the ChemQuery window. Submitting the query launches a structure similarity search tool that looks for common substructures from the query compound that match DrugBank’s database of known drug or drug-like compounds. High scoring hits are presented in a tabular format with hyper- links to the corresponding DrugCards (which in turn links to the protein target). The ChemQuery tool allows users to quickly determine whether their compound of interest acts on the desired protein target. This kind of chemical structure search may also reveal whether the compound of interest may unexpectedly interact with unintended protein targets. In addi- tion to these structure similarity searches, the ChemQuery utility also supports compound searches on the basis of chem- ical formula and molecular weight ranges. DrugBank’s data extraction utility (Data Extractor) employs a simple relational database system that allows users to select one or more data ﬁelds and to search for ranges, occurrences or partial occurrences of words, strings or numbers. The data extractor uses clickable web forms so that users may intuit- ively construct SQL-like queries. Using a few mouse clicks, it is relatively simple to construct very complex queries (‘ﬁnd all drugs less than 600 daltons with LogPs less than 3.2 that are antihistamines’) or to build a series of highly customized tables. The output from these queries is provided as an HTML format with hyperlinks to all associated DrugCards. QUALITY ASSURANCE, COMPLETENESS AND CURATION Every effort is made to ensure that DrugBank is as complete, correct and current as possible. Each DrugCard is entered or prepared by one member of the curation team and separately validated by second member of the curation team. Additional Nucleic Acids Research, 2006, Vol. 34, Database issue D671 spot checks are routinely performed on each entry by senior members of the curation group, including a physician, an accredited pharmacist and two PhD-level biochemists. Several software packages including text mining tools, chemical para- meter calculators and protein annotation tools (10) have been modiﬁed or speciﬁcally developed to aid in DrugBank’s data entry and data validation. These tools collate and display text (and images) from multiple sources allowing the curators to compare, assess, enter and correct drug or drug target informa- tion. In addition to using a CVS (Current Versioning System), all changes and edits to the central database are monitored, dated and displayed on the DrugBank ‘download’ page using a specially developed text tracking system. A second text track- ing system has been implemented to monitor the completeness (0–100%) of each ﬁeld (for all approved drugs) and to display up-to-date statistics on the number of drugs, drug targets and non-redundant sequences in various drug categories. This information is also displayed in the ‘download’ page. To ensure DrugBank is current, new drugs (approved and experi- mental) are identiﬁed using continuously running screen- scraping tools linked to the FDA, the PDB and RxList web- sites. Backﬁlling of older, more obscure and orphan drugs is ongoing and done manually. Drug targets are identiﬁed and conﬁrmed using multiple sources (PubMed, TTD, FDA labels, RxList, PharmGKB, textbooks) as are all drug structures (KEGG, PubChem, images from FDA labels). CONCLUSION In summary, DrugBank is a comprehensive, web-accessible database that brings together quantitative chemical, physical, pharmaceutical and biological data about thousands of well- studied drugs and drug targets. DrugBank is primarily focused on providing the kind of detailed molecular data needed to facilitate drug discovery and drug development. This includes physical property data, structure and image ﬁles, pharmaco- logical and physiological data about thousands of drug pro- ducts as well as extensive molecular biological information about their corresponding drug targets. DrugBank is unique, not only in the type of data it provides but also in the level of integration and depth of coverage it achieves. In addition to its extensive small molecule drug coverage, DrugBank is cer- tainly the only public database we are aware of that provides any signiﬁcant information about the 110+ approved biotech drugs. DrugBank also supports an extensive array of visual- izing, querying and search options including a structure sim- ilarity search tool and an easy-to-use relational data extraction system. It is hoped that DrugBank will serve as a useful resource to not only members of the pharmaceutical research community but to educators, students, clinicians and the general public. ACKNOWLEDGEMENTS The authors wish to thank Genome Prairie, a division of Genome Canada for financial support. Funding to pay the Open Access publication charges for this article was provided by Genome Canada. Conflict of interest statement. None declared.