The druggable genome can be defined as the genes or gene products that are known or predicted to interact with drugs, ideally with a therapeutic benefit to patients. We developed the Drug Gene Interaction database (DGIdb) to help researchers interpret the results of genome-wide studies in the context of the druggable genome. DGIdb organizes genes of the druggable genome into two main classes. The first class includes genes with known drug interactions obtained by literature mining or by parsing publicly available reviews and databases. The second class includes genes that may not currently be targeted therapeutically but are 'potentially' druggable according to their membership in gene categories associated with druggability (e.g., kinases). DGIdb integrates data from 15 primary sources covering disease-relevant human genes, drugs, drug-gene interactions, and potential druggability. Currently, DGIdb contains 2,611 genes and 6,307 drugs involved in over 14,144 drug-gene interactions and 6,761 genes belonging to one or more of 39 potentially druggable gene categories. A total of 7,668 unique genes have either known or potential druggability. Each drug-gene or gene-category association is linked to its primary database or literature source. By intersecting the current knowledge of known and potentially druggable genes, DGIdb provides a unique resource for surveying the state of the field of targeted therapies.
Potential use cases for DGIdb are abundant. A user may enter a single gene to explore the current state of knowledge regarding druggability of that gene. Alternatively they might input a large list of genes to identify the subset with potential druggability. In another use case, researchers may simply want a list of genes belonging to druggable categories of interest (e.g., all known kinases). DGIdb provides a bridge between previously inaccessible data on gene druggability and those seeking to understand the significance of genomic variation in human disease. DGIdb can be accessed at dgidb.org.
Griffith M, Griffith OL, Coffman AC, Weible JV, McMichael JF, Spies NC, Koval J, Das I, Callaway MB, Eldred JM, Miller CA, Subramanian J, Govindan R, Kumar RD, Bose R, Ding L, Walker JR, Larson DE, Dooling DJ, Smith SM, Ley TJ, Mardis ER and Wilson RK. DGIdb - Mining the druggable genome. Nature Methods. Oct. 13, 2013. *These authors contributed equally to the research.
Nice work! I'm excited to have a look at it.
I had a look at the database. I have a question about companion diagnostics e.g. mutations of relevance for e.g. EGFR treatment or ALK treatment. For EGFR, KRAS mutations have proven to infer resistance to EGFR inhibition. For ALK, a couple of mutations have been reported to infer resistance to crizotinib.
Is this information available in the database?
Johan. Thanks for the kind words. Unfortunately the mutation-specific information you describe is not yet in the database. But, that is one of a few key features that we hope to tackle next. Until then, I think "My Cancer Genomes" is one of the best sources for that type of information.