Meet the speaker: Dr Richard Edwards
Inventor of the acronym SLiM (short linear motifs) Dr Richard Edwards took time out to answer some of our questions about his work.
What do you think are the most interesting “big questions” in your field?
We know that many protein-protein interactions are mediated via short linear motifs (SLiMs) but we still don’t really how many nor what proportion of SLiM-mediated interactions are specific to a single pair of proteins. Two of the most interesting big questions is therefore: (1) how widespread are competitive SLiM-mediated interactions, i.e. where multiple proteins use the same motif for interaction? (2) How much are those interactions driven purely by presence/absence of the SLiM itself versus other factors such as coexpression or colocalisation? A third is whether bacteria use SLiMs much, or are they predominantly a eukaryotic innovation? Not really a “big question” but the biggest challenge in the field at present is how to reliably detect SLiM-mediated interactions at high throughput so that we can feed our programs high quality data.
Please tell us about your research interests and what you are currently working on.
My core research interest is whether we can predict sites of protein-protein interaction directly from protein sequences and knowledge of their interaction partners. In a wider setting, this is an important aspect of adding spatial and temporal information to protein-protein interaction networks. Only then will we be able to understand/model cooperative and competitive interactions and start predicting the functional consequences of mutations. More generally, I love applying sequence analysis to all manner of biological problems. Being a geneticist by training, I am currently getting very excited by the new world of possibilities being opened up by long-read sequencing. We are currently working on a few functional genomics projects using PacBio sequencing for de novo whole genome sequencing. The new technology shifts the focus from technical questions to scientific ones, which is fantastic.
Do you have favourite applications of your work and what is the impact of these applications?
My favourite application of SLiM discovery so far is the investigation of molecular mimicry in pathogens. Viruses often hijack host cells by copying host motifs to control or interfere with host protein-protein interactions. Not only is this a fascinating evolutionary system to study, it has big implications for drug design, both for targeting/blocking viral interactions but also providing new mechanisms for manipulating host (i.e. human) cell function.
Why did you chose this career?
I’ve always been fascinated by both evolution and how complex living beings can be “programmed” by the genetic code they carry. I also always enjoyed logic puzzles, problem solving and tinkering with computers. Bioinformatics is fantastic as it lets me investigate fascinating questions using methods that I enjoy. I was lucky enough to get into the field reasonably early and have always managed to find someone willing to hire me, so I’ve never really considered another career.
Can you tell us about the highlight of your career so far?
I’d describe my career as more of a slow burn than a big bang – and I hope that the best is still to come – so it’s tough to pick one stand-out event. I guess my biggest claim to fame is coming up with the term “SLiM” (short linear motif) for the kind of interaction motif I work on, which seems to have caught on in the literature. My career highlight is probably making SLiMFinder, which is still the de novo SLiM prediction tool to beat. I do enjoy reading other people’s papers where it performs best in benchmarking! Although a bit more mundane, my biggest kick probably comes from revisiting an old program and finding that (a) it still works and (b) it’s still useful.