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<project type="OPENMM_23" id="18215">
<stats-credit v="67168"/>
<deadline v="5"/>[GPU] project 18215 in full FAH!
Moderators: Site Moderators, FAHC Science Team
[GPU] project 18215 in full FAH!
[GPU] p18215 – Studies on Apolipoprotein E - https://stats.foldingathome.org/project?p=18215
Re: [GPU] project 18215 in full FAH!
I wanted to thank everyone who helped out with folding 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 ... 3.597137v1.
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!
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!
Re: [GPU] project 18215 in full FAH!
Wanted to let folks know that in some of our followup data analysis we noticed that one of our simulations led to a really interesting state which we'd not seen before. We have lots of hypotheses about what this state is and wanted to collect a bit more data on this state. I've released another ~800 WUs to probe this state in the 18215 project. Thanks all for folding!
Re: [GPU] project 18215 in full FAH!
Apologies for the crypticness of the above message- in our excitement to send out more WUs we neglected to add many details.
In one trajectory of our previously sampled dataset, we saw ApoE exhibit a partial unfolding transition from a fully packed structure to a partially unpacked structure. Our experimental collaborators have suggested motions of this type are likely necessary for ApoE to bind lipids (its primary task in the body). Indeed, initial structures of lipid-bound ApoE (https://www.cell.com/neuron/pdf/S0896-6 ... 0977-7.pdf) show that ApoE must exhibit a large amount of unfolding to reach the final, lipid-bound, state. However, how this transition happens, as well as how mutations in ApoE affect these transitions, remains unknown. We hypothesize that the transition we observed is an intermediate state towards accepting lipids. However, given the relative rarity of the event (happening once in > 35,000 simulations), we wanted to launch some additional simulations to check that 1) the states we observed and were excited about are "stable" and not simulation artifacts, as well as 2) see if we could observe the same transition more times to grow more confident about our observations. The simulations re-launched are likely a first step in exploring these processes and it's very likely additional simulations (or a different project number) will be coming down the pipeline.
As we feel more confident in our findings I'll update this thread further! As always, thank you for folding! Please feel free to poke with questions!
In one trajectory of our previously sampled dataset, we saw ApoE exhibit a partial unfolding transition from a fully packed structure to a partially unpacked structure. Our experimental collaborators have suggested motions of this type are likely necessary for ApoE to bind lipids (its primary task in the body). Indeed, initial structures of lipid-bound ApoE (https://www.cell.com/neuron/pdf/S0896-6 ... 0977-7.pdf) show that ApoE must exhibit a large amount of unfolding to reach the final, lipid-bound, state. However, how this transition happens, as well as how mutations in ApoE affect these transitions, remains unknown. We hypothesize that the transition we observed is an intermediate state towards accepting lipids. However, given the relative rarity of the event (happening once in > 35,000 simulations), we wanted to launch some additional simulations to check that 1) the states we observed and were excited about are "stable" and not simulation artifacts, as well as 2) see if we could observe the same transition more times to grow more confident about our observations. The simulations re-launched are likely a first step in exploring these processes and it's very likely additional simulations (or a different project number) will be coming down the pipeline.
As we feel more confident in our findings I'll update this thread further! As always, thank you for folding! Please feel free to poke with questions!