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Drug discovery isn’t getting any easier. Development of new pharmaceuticals–and improvement of existing ones–is a time-consuming and expensive process. Therefore, maximizing benefits–and reducing side effects–from compounds that already have known medicinal, or proto-medicinal, properties is an attractive option.

Katherine Herbert and Nina Goodey of Montclair State University, New Jersey have used their expertise in bioinformatics and biological knowledge of dihydrofolate reductase (DHFR) respectively to test a new tool for looking at the relationships between proteins and their binding partners in an evolutionary context. DrugTree is a web-based tool integrating phylogenetic data and enzyme analysis with known information about ligands and inhibitors, and the prototype was reported at the recent Conference on Semantics in Healthcare and Life Sciences.

DrugTree combines information from the Binding DB protein binding database and UniProt curated databases with a modified version of the Interactive Tree of Life phylogenetic tool to visualize data. So at it’s heart DrugTree is a MySQL database of interactions, with phylogenetic trees drawn on top (according to the user’s input).

3KFY - Dynamic switching and partial occupancies of a small molecule inhibitor complex of DHFR

The motivation behind DrugTree stems from the lack of phylogenetic context in current pharmaceutical research, scientists often relying entirely on Clustal to obtain this information. The strength of DrugTree is its ability to enable users “to visualize the data while using multiple sequence alignment tools and phylogenetic reconstruction tools.” Why is this useful? Because as a protein evolves, its binding pocket (and therefore binding specificity) changes. So given known binding interactions within a protein family, evolutionary relationships can predict binding between a given ligand–a drug like methotrexate for example–and homologues of the target protein–in this case DHFR.

DHFR is the favoured test case because its structure is known and its inhibitors are well characterized. It’s also the target of the anti-cancer agent methotrexate, so apart from being useful for testing the new tool, any biological insights relevant to efficacy and specificity is likely to have immediate clinical benefit. However, despite its name, DrugTree should be able to give phylogenetic context to any protein where cross-referenced data are available. Herbert and Goodey plan on adding more phylogenetic reconstruction tools, and are talking with other potential collaborators in biology, ecology and environmental studies about its potential applications. DrugTree is currently in alpha test, and the plan is to release a public version in the middle of 2011.