Hey all! I'm Justin, a postdoc in Greg Bowman's group at UPenn.
I wanted to thank everyone who helped out on project 18215 - we’ve just released a preprint (scientific article before peer review) that makes use of the data collected. Here is the link to the preprint:
https://www.biorxiv.org/content/10.1101/2024.06.03.597137v1.
In summary, we’ve been interested in comparing simulation data to an experimental technique called single molecule Förster Resonance Energy Transfer (smFRET), which effectively measures distances between two pairs of residues on a protein. This is a relatively new biophysical technique and is quite nice because it tells us about states of proteins that may be quite low abundance. Unfortunately, comparing simulations with these experiments has been quite difficult. We present an algorithm that allows us to make direct comparisons between these types of experiments and simulations and find that our simulations match experiments quite well! Ultimately this makes us feel more confident about drawing conclusions from our simulations and using them to design novel therapies as well as understand how mutations might cause disease.
This also isn’t the last time we’ll be using this data- our long term interest is understanding differences between apolipoprotein E (ApoE) isoforms which are one of the strongest predictors of Alzheimer’s disease. We’ve simulated other isoforms of ApoE in projects 18215-18223 and are actively working on analyzing these data. Some projects, 18221-18223, are still under data collection. In parallel in the wet lab, we’ve been making similar style smFRET measurements for all of these isoforms. Stay tuned!