More mature readers may remember
a column by Daedalus, aka David E. H. Jones, which used to run in Nature. Sadly he passed away last year,
but his company, DREADCO, is still going strong. They have just launched a new
product that should be of wide interest.
Our poll last year found that
nearly a third of respondents would not begin fragment optimization without a
crystal structure. Although there are successful counterexamples, it is fair to
say that just about everyone would like a crystal structure if possible. Thus
DREADCO has launched UniC, their Universal Crystallography platform.
The idea is based on previous
work in which “crystalline sponges” can be used to absorb small molecules.
X-ray data are collected on the sponge-molecule complex, and since the sponge
structure is already known, the small molecule structure can be readily determined
(see here for a nice summary by Derek Lowe). This is a powerful approach for
small molecules, but the metal-organic frameworks used for the crystalline
sponges are too small for proteins.
DREADCO researchers have solved
this problem by using DNA origami to construct a cage-like structure that
contains large pores yet is incredibly rigid, and therefore diffracts to high
resolution. They have also inserted binding sites for a variety of DNA-binding
proteins. All you need to do is generate a fusion between your protein and a
DNA-binding protein and soak this into the crystallized DNA cages. Then soak in
your fragment, and collect diffraction data to your heart’s content.
UniC is similar to the
well-established method of tackling difficult-to-crystallize proteins by
generating fusion proteins with antibodies or maltose-binding protein, but
there you still need to find and optimize crystallization conditions for the
construct. Here, since crystals of the DNA cage can be pre-grown, the time from
construct generation to structure determination is dramatically shortened. Whatever
the specifics of your protein of interest, all the world’s a cage.
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2 comments:
Hi Dan, I've been waiting all day for this post. I think this can potentially disrupt FBDD if used with LELP and deep learning. The most exciting opportunity opened by these cages is that they eliminate the deep to define a standard state for thermodynamic analysis and I also see potential for using thermodynamic proxies to renormalize molecular obesity.
A couple of our previous April 1 posts have anticipated later developments (such as FIB and Ben Cravatt's recent work). Although UniC is currently just a fantasy, a related approach was recently published for cryo-EM. To extend Teddy's prediction, perhaps the crystallographers will soon be following the NMR spectroscopists to Valinor!
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