Thank you for setting this up.
How hard is it to find functional proteins?
Contrary to the claims of Axe and Gauger that enzymatic activity is tough to find in the protein sequence landscape–
Axe DD, Estimating the prevalence of protein sequences adopting functional enzyme folds.
J Mol Biol. 2004 Aug 27;341(5):1295-315.
DOI: 10.1016/j.jmb.2004.06.058 PMID: 15321723
Axe DD, Gauger AK (2015) Model and laboratory demonstrations that evolutionary optimization works well only if preceded by invention—Selection itself is not inventive.
BIO-Complexity 2015 (2):1–13. doi:10.5048/BIO-C.2015.2
(and others)
I’d like to present a summary of our work for discussion.
This has the same general thrust as Art Hunt’s critique–
https://discourse.peacefulscience.org/t/art-hunt-to-doug-axe-invitation-to-discuss/
https://discourse.peacefulscience.org/t/side-comments-on-hunt-to-axe/
but is a series of empirical demonstrations to complement Art’s more theoretical criticisms.
It’s also relevant to this other discussion:
https://discourse.peacefulscience.org/t/the-probability-of-a-bifunctional-protein/
as we made bifunctional proteins very easily.
Our goal was not to learn anything about evolution, but to address a problem in biology caused by evolution: there are huge multigene families that according to sequence relationships and everything else, are the result of gene duplications and diversifications of function. However, contrary to the machine-like picture painted by the ID folks, these functional diversifications are rarely complete, leaving us with schmeers of partially overlapping functions, something we simply don’t see in designed machines. It just screams that it could only have been designed by the iterative process of evolution, much louder than the ID refrain that life is like some sort of human-designed machine.
The practical issue for biologists and biochemists is that partially-overlapping functions make it hard to figure out what a single one of these family members really does. It’s the likely reason why many gene knockouts don’t do much. It also causes problems for biochemical inhibition/activation of specific proteins in cell biology and pharmacology (think drug side effects).
In late 1990s pharmacology, the brilliant Kevan Shokat developed a chemical-genetic method for inhibiting individual tyrosine kinases, which has enormous implications for cancer treatment, since so many oncogenes are tyrosine kinases. With the help of Kevan and his postdoc Kavita Shah, Peter Gillespie and I set out to use this method to study a suspect for the adaptation motor myosin-1c in inner-ear hair cells, a interesting biophysical and physiological system that provides an enormous dynamic range for our hearing.
The above three paragraphs are provided just to establish the relevance of this work outside of any evolutionary context, and to show how evolution impacts our ability to assess functions of proteins in complex critters like mice and humans. I will get to the conflict, in terms of what it says about the sequence landscape, in the next post. You can ignore all of the rationale above if you are only interested in the conflict. 