Tag Archives: P300

The Dr. Jekyll and Mr. Hyde protein

If there ever was a protein with a Dr. Jekyll and Mr. Hyde character (https://en.wikipedia.org/wiki/Dr._Jekyll_and_Mr._Hyde_(character))it is EZH2, a protein whose function we thought we knew.

EZH2 is an enzyme which puts methyl groups on lysine #27 of histone H3 (forming H3K27Me3).     So as good chemists that tells you that it removes the positive charge usually found on the amine group lysine at physiological pH.  But chemistry is helpless here unless you know what histone H3 does.  Addendum 27 July — clearly I’m not a good chemist when I write late at night.  Ashutosh points out that the positive charge on nitrogen at physiologic pH remains even when one, two or all the hydrogens are replaced by methyl groups.  Acetylation of the amino group of lysine removes the positive charge.  The methylation of lysine #27 is just one part of the histone code allowing other proteins to specifically bind here. As of 2013 some 130 different post-translational histone modifications were known.  

The DNA in each of our cells is just over a yard long.  To fit inside it must be compacted down.  4 different histone proteins get together to form an octomer around which DNA wraps in nearly two complete turns, compacting DNA down by a factor of ten.  The details of the further compaction have been studied for 50 years and are still under debate.

You’d think that the methylation of lysine #27 and loss of the positive charge would make it less likely to bind to the negative phosphates of the DNA chain.  This should free up the DNA so it can be transcribed to RNA and make proteins.

That’s not at all what happens. There are other proteins which bind H3K27Me3 and compact the DNA down so it becomes inactive (unable to be transcribed into mRNA).

Well that was the state of play until Proc. Natl. Acad. Sci. vol. 117 pp. 16992 – 17002 ’20.  So much for Dr. Jekyll.

Some forms of cancer activate kinase enzymes (AKT, JAK3) which place phosphates on serine #21 or tyrosine #244 of EZH2 respectively.   This causes a giant structural arrangement of amino acids #135  to #195.  Now the protein interacts with another enzyme p300 (a histone acetyl transferase) whose net effect is to UNcompact DNA and activate gene transcription.  Even worse, the transcription products of the genes help the cancer along.  Definitely Mr. Hyde.

This is a radically different function for EZH2 and you have to wonder how many other proteins lead double lives like EZH2.

The classic examples of a huge structural shift in a protein complex are the spike proteins of viruses (notably SARS-CoV-2), which unfold to form a needle piercing a cell allowing injection of the viral genetic material. Here are some nice pictures of the fusion protein of influenza virus in action — http://faculty.washington.edu/kklee/Influenza_SAXS.html.  But this is structural change in pursuit of a known physiological effect.

The double life of EZH2 is remarkable.   Some proteins have more than one effect in the cell — this is called moonlighting.  One example is cytochrome c, which is normally found in the intermembrane space of the mitochondrion where it is involved in electron transport.  When it is released into the cell cytoplasm due to mitochondrial damage, the cell quietly kills itself (apoptosis) — definitely a moonlighting function.  But the structure of cytochrome c doesn’t change to accomplish this, just its location.

Fascinating stuff, and the paper should be read to see just how profound the shift in structure that EZH2 undergoes actually is.

This is just a small window into the intricacy (and beauty if you will) of the cellular and biochemical events underlying our existence.  There is far more to discover, so stay tuned.

For some further musings on this point — https://luysii.wordpress.com/2009/09/17/the-solace-of-molecular-biology/

Why we imperfectly understand randomness the way we do.

The cognoscenti think the average individual is pretty dumb when it comes to probability and randomness. Not so, says a fascinating recent paper [ Proc. Natl. Acad. Sci. vol. 112 pp. 3788 – 3792 ’15 ] http://www.pnas.org/content/112/12/3788.abstract. The average joe (this may mean you) when asked to draw a random series of fifty or so heads and tails never puts in enough runs of heads or runs of tails. This leads to the gambler’s fallacy, that if an honest coin gives a run of say 5 heads, the next result is more likely to be tails.

There is a surprising amount of structure lurking within purely random sequences such as the toss of a fair coin where the probability of heads is exactly 50%. Even with a series with 50% heads, the waiting time for two heads (HH) or two tails (TT) to appear is significantly longer than for an alternation (HT or TH). On average 6 tosses will be required for HH or TT to appear while only an average of 4 are needed for HT or TH.

This is why Joe SixPack never puts in enough runs of Hs or Ts.

Why should the wait be longer for HH or TT even when 50% of the time you get a H or T. The mean time for HH and TT is the same as for HT and TH. The variance is different because the occurrences of HH and TT are bunched in time, while the HT and TH are spread evenly.

It gets worse for longer repetitions — they can build on each other. HHH contains two instances of HH, while alterations do not. Repetitions bunch together as noted earlier. We are very good at perceiving waiting times, and this is probably why we think repetitions are less likely and soon to break up.

The paper goes a lot farther constructing a neural model, based on the way our brains integrate information over time when processing sequences of events. It takes into consideration our perceptions of mean time AND waiting times. We average the two. This produces the best fitting bias gain parameter for an existing Bayesian model of randomness.

See, you’re not as dumb as they thought you were.

Another reason for our behavior comes from neuropsychology and physiological psychology. We have ways to watch the electrical activity of your brain and find out when you perceive something as different. It’s called mismatch negativity (see http://en.wikipedia.org/wiki/Mismatch_negativity for more detail). It a brain potential (called P300) peaking .1 -.25 seconds after a deviant tone or syllable.

Play 5 middle c’s in a row followed by a d than c’s again. The potential doesn’t occur after any of the c’s just after the d. This has been applied to the study of infant perception long before they can speak.

It has shown us that asian and western newborn infants both hear ‘r’ and ‘l’ quite well (showing mismatch negativity to a sudden ‘r’ or ‘l’ in a sequence of other sounds). If the asian infant never hears people speaking words with r and l in them for 6 months, it loses mismatch negativity to them (and clinical perception of them). So our brains are literally ‘tuned’ to understand the language we hear.

So we are more likely to notice the T after a run of H’s, or an H after a run of T’s. We are also likely to notice just how long it has been since it last occurred.

This is part of a more general phenomenon — the ability of our brains to pick up and focus on changes in stimuli. Exactly the same phenomenon explains why we see edges of objects so well — at least here we have a solid physiologic explanation — surround inhibition (for details see — http://en.wikipedia.org/wiki/Lateral_inhibition). It happens in the complicated circuitry of the retina, before the brain is involved.

Philosophers should note that this destroys the concept of the pure (e.g. uninterpreted) sensory percept — information is being processed within our eyes before it ever gets to the brain.

Update 31 Mar — I wrote the following to the lead author

” Dr. Sun:

Fascinating paper. I greatly enjoyed it.

You might be interested in a post from my blog (particularly the last few paragraphs). I didn’t read your paper carefully enough to see if you mention mismatch negativity, P300 and surround inhibition. if not, you should find this quite interesting.


And received the following back in an hour or two

“Hi, Luysii- Thanks for your interest in our paper. I read your post, and find it very interesting, and your interpretation of our findings is very accurate. I completely agree with you making connections to the phenomenon of change detection and surround inhibition. We did not spell it out in the paper, but in the supplementary material, you may find some relevant references. For example, the inhibitory competition between HH and HT detectors is a key factor for the unsupervised pattern association we found in the neural model.


Nice ! ! !