Hi everyone! Does anyone else use the Therapeutic Target Database (TTD) as a source of data for their work? I have been using it for a number of years, and while it is a great resource, it also has some quirks to be aware of. I would love to hear if others use this or similar data!
In short, the TTD is a database linking compounds to gene targets. This is useful for target research, if we want to understand whether a target already has known compounds that interact with it, and what stage of approval they are (investigative, phase 1, etc through to approved). It is also useful to explore whether a compound may have off-target effects, if it is known to hit multiple targets/pathways in the body.
As an example, if we search for Selegiline, we can see that it is an approved drug for Parkinson’s, and that the known target is MAO-B in the Dopamine receptor mediated signalling pathway (below).
On the other hand, if we search for the common PD-associated gene LRRK2, we can see that it has been associated with 3 drugs for PD which passed phase 1 clinical trial, but nothing is yet approved.
The main caveat I have discovered when using the TTD is that you have to double-check the original references to validate any links, especially for earlier-stage associations between compound and target. The link between Selegiline and MAO-B is backed by two references which look solid (below), but I have seen Phase 1 and 2 associations backed by company reports instead of peer-reviewed papers, and even sometimes papers which make no mention of the purported target. It makes sense that earlier research is less well validated, but I always consider the TTD as a starting point to a hypothesis rather than cast iron proof.
One of the best things about the TTD is that all the data can be downloaded in bulk, and integrated into your own systems for off-line use. This is particularly useful for running large numbers of queries, such as finding all compounds associated with all targets with any level of association with Parkinson’s (many 100s of genes!).
I hope this dataset can be useful to others in their work!