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I read about this new study with interest and then wondered whether the Gaf1 protein might make a good foldit puzzle:

skovz99's picture
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Interesting article. Gaf1 is

Interesting article.
Gaf1 is a TF that normally resides in the cytoplasm. When TOR is inactivated, Gaf1 is recommissioned to the nucleus to silence all genes related to making tRNAs. Organisms with a Gaf1 KO, do not live that long.

Based on that little summary, there are a few things fold-it could do to make such a puzzle possible:

1. How is Gaf1 relocated? In some articles that I read on the topic, de-phosphorylation of Gaf1 is what causes its nuclear localization. So designing a protein binder to this will not aid in its nuclear localization (anti-aging consequences) unless the designed protein is a kinase.

2. Inactivation of TOR would be a possible protein design competition such that the designed inhibitor creates the same inactivation of TOR that nitrogen depletion does. This would be a sort of upstream regulation of Gaf1.

Both of these possibilities require some extensive regulation of Gaf1 in order to produce the desired result (anti-aging). I think a better opportunity for this type of article would be to create a protein logic gate or to use the LOCKR concept which would take this type of regulation into account in their designs.

Possible ideas: design TOR inhibitor that is placed under the control of a specific synthetic promoter that only the researcher could regulate. This would control the aging process from a medical perspective.
This would get around the need to design a protein that needs to survive extracellular physiologies, to bind to certain cell receptors and then influence the target TOR.

LOCKR idea: latch, cage + sequestered peptide. Upon binding of a Key, the sequestered peptide becomes activated. This now active peptide could either inhibit TOR or activate the kinase that phosphorylates Gaf1. Both the key and the sequestered peptide could be designed by fold-it players.

References for further reading
1. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7068653/
2. https://www.nature.com/articles/s41586-019-1432-8
3. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4686964/
4. https://www.bakerlab.org/wp-content/uploads/2020/04/Chen2020_DeNovoProteinLogicGates.pdf


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