mTOR 2016 paper (rapamycin analog sensitivity prediction)

[zeglet]

Came across the 2016 Chodera/Hsieh paper predicting mTOR mutant sensitivity to rapamycin analogues. Very nice work!
(I worked on mTOR (it had a different name back than) pathways for my thesis just under 20 years ago. Nice to see an old friend again.)

How did you use folding@home in this work?

[JohnChodera]

Awesome! It's always exciting to hear from other researchers that have worked on mTOR.

You can find the whole paper on our website:
http://www.choderalab.org/publications/ ... -rapamycin

The graduate student who did this work, Steven Albanese, also wrote a nice short blog post on how he used Folding@home for this paper:
http://folding.stanford.edu/2016/10/21/new-paper-mtor/

~The Chodera Lab

[zeglet]

So you in a wet-lab you tested the activity of a wild-type mTOR and a number of mutant mTORs each in an environment with S6 kinase.
And for mutants where activity was higher, you were able to look at structure difference versus wild-type via folding@home? (Used in a structure-prediction role?)

From your paper: "mTOR-activating mutants from different clusters display functional synergism"
Wild that that's the case; maybe expected, but still wild.

"Importantly, all activating mutations are sensitive to rapamycin treatment."
+1.

[JohnChodera]

Ongoing research is trying to determine whether we can predict which mutations will be activating (and hence may be cancer drivers) and may respond to mTOR inhibitor treatment. If we can figure this out, we might be able to help determine which of the two million cancer patients harboring MTOR mutations might benefit from mTOR inhibitor treatment!