Author Archives: luysii

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Amyloid structure at last !

As a neurologist, I’ve been extremely interested in amyloid  since I started in the late 60s.  The senile plaque of Alzheimers disease is made of amyloid.  The stuff was insoluble gunk. All we had back in the day was Xray diffraction patterns showing two prominent reflections at 4 and 9 Angstroms, so we knew there was some sort of repetitive structure.

My notes on papers on the subject over the past 20 years contain  about 100,000 characters (but relatively little enlightenment until recently).

A while ago I posted some more homework problems — https://luysii.wordpress.com/2021/09/30/another-homework-assignment/

Homework assignment #1:  design a sequence of 10 amino acids which binds to the same sequence in the reverse order forming a plane 4.8 Angstroms thick.

Homework assignment #2 design a sequence of 60 amino acids which forms a similar plane 4.8 Angstroms thick, such that two 60 amino acid monomers bind to each other.

Feel free to use any computational or theoretical devices currently at our disposal, density functional theory, force fields, rosetta etc. etc.

Answers to follow shortly

Hint:  hundreds to thousands of planes can stack on top of each other.

 

If you have a subscription to Cell take a look at a marvelous review full of great pictures and diagrams [ Cell vol. 184 pp. 4857 – 4873 ’21 ].

 

Despite all that reading I never heard anyone predict that a significantly long polypeptide chain could flatten out into a 4.8 Angstrom thick sheet, essentially living in 2 dimensions.  All the structures we had  (alpha helix, beta pleated sheet < they were curved >, beta barrel, solenoid, Greek key) live in 3 dimensions.

 

 

So amyloid is not a particular protein, but a type of conformation a protein can assume (like the structures mentioned above).

 

 

So start with NH – CO – CHR.  NH  CO and C in the structure all lie in the same plane (the H and the side chain of the amino acid < R >  project out of the plane).

 

Here’s a bit of elaboration for those of you whose organic chemistry is a distant memory.  The carbon in the carbonyl bond (CO) has 3 bonding orbitals in one plane 120 degrees apart, with the 4th orbital perpendicular to the plane — this is called sp2 hybridization.  The nitrogen can also be hybridized to sp2.  This lets the pair of electrons above the plane roam around moving toward the carbon.  Why is this good?  Because any time you let electrons roam around you increase their entropy (S) and anything increasing entropy lowers their free energy (F)which is given by the formula F = H – TS where H is enthalpy (a measure of bond strength, and T is the absolute temperature in Kelvin.

 

 

So N and CO are in one plane, and so are the bonds from  N and C to the adacent atoms (C in both cases).

 

You can fit the plane atoms into a  rectangle 4.8 Angstroms high.  Well that’s one 2 dimensional rectangle, but the peptide bond between NH and CO in adjacent rectangles allows you to tack NH – CO – C s together while keeping them in a 3 dimensional parallelopiped 4.8 Angstroms high.

 

 

Notice that in the rectangle the NH and CO bonds are projecting toward the top and bottom of the rectangle, which means that in each plane  NH – CO – CHR s, the NH and CO are pointing out of the 2 dimensional plane (and in opposite directions to boot). This is unlike protein structure in which the backbone NHs and COs hydrogen bond to each other.  There is nothing in this structure for them to bond to.

 

 

What they do is hydrogen bond to another 3 dimensional parallelopiped (call it a sheet, but keep in mind that this is NOT the beta sheet you know about from the 3 dimensional structures of proteins we’ve had for years).

 

 

So thousands of sheets stacked together form the amyloid fibril.

 

Where does the 9 Angstrom reflection of cross beta come from?  Consider the  [ NH – CHR – CO ]  backbone as it lies in the 4.8  thick plane (I never thought such a thing would be even possible ! ).  It curves around like a snake lying flat.  Where are the side chains?  They are in the 4.8 thick plane, separating parts of the meandering backbone from each other — by an average of 9 Angstroms

 

Here is an excellent picture of the Alzheimer culprit — the aBeta42 peptide as it forms the amyloid of the senile plaque

 

 

You can see the meandering backbone and the side chains keeping the backbone apart.

 

 

That’s just the beginning of the paper, and I’ll have lots more to say about amyloid as I read further.   Once again, biology instructs chemistry and biochemistry giving it more “things in heaven and earth, Horatio, than are dreamt of in your philosophy.”

The most interesting paper I’ve read this year

We all know what the estrogen receptor is and what it does.  It’s a large protein with 3  functional components.  Actually there are several estrogen receptor proteins, but I’m going to discuss just one — Estrogen Receptor alpha (ERalpha).

Here are the components:

a DNA binding domain (which binds to stretches of bases called the Estrogen Response Element (ERE))

a domain which binds estrogen changing the conformation of the third domain which is —

a domain which binds to RNA polymerase II activating it so it transcribes genes into mRNA.

Given the complexity of the hormonal cycles, it is far from surprising that the estrogen receptor controls the levels of 15% of all annotated protein coding genes < Cell vol. 145 pp. 622 – 634 ’11 >.

Given its importance in breast cancer, ERalpha has been intensively studied for years.

Now various regions of proteins have been assigned function, the SH2 domain binds to phosphotyrosine in proteins, SH3 binds to proline rich motifs, RNA Binding Domains (RBDs) bind to (what else?) RNAs.  Each of them has a characteristic sequence of amino acids allowing them to be picked out from DNA sequences.

Enter Cell vol. 184 pp. 5086 – 5088, 5215 – 5229 ’21 where ERalpha was found to bind to over 1,200 messenger RNAs (mRNAs).   It was not supposed to do that as it doesn’t contain any RBDs (well at least the RBDs we knew about — back to the drawing board on that one).  Even more interesting is the fact what most of the mRNAs bound by ERalpha aren’t from the genes whose ERE ERalpha binds.

Life is said to have originated in the RNA world.  We all know about the big 3 important RNAs for the cell, mRNA, ribosomal RNA and transfer RNA.  But just like the water, sewer, power and subway systems under Manhattan, there is another world down there in the cell which doesn’t much get talked about.  These areRNAs, whose primary (and possibly only) function is to interact with other RNAs.

The RNA world is still alive and well in all our cells.  It’s like DOS still out there under Windows, or Unix and its command line under the Apple interface. We studied proteins and DNA because they were (relatively) easy to study.

The papers go on to study how ERalpha RNA binding affects cancer (which it does).

But there are far larger questions the work brings forth.

l. ERalpha is just one nuclear hormone receptor and Estrogen is just one hormone.  Do the nuclear hormone receptor for other hormones also bind RNA? Have we been missing some of their actions inside cells and if so there are mechanisms to exploit?

2. Why stop at nuclear hormone receptors?  ERalpha binds RNA with no RNA binding  domains (RBDs) in sight.  Do other proteins also bind RNAs and if so what does it mean?

Fantastic stuff.  There is a whole world of possibilities opening before our eyes thanks to these papers.

It reminds me of what an anatomy professor told us when we were studying neuroanatomy — ‘unfortunately everything is connected to everything else’.

More homework assignments

Homework assignment #1:  design a sequence of 10 amino acids which binds to the same sequence in the reverse order forming a plane 4.8 Angstroms thick.

Homework assignment #2 design a sequence of 60 amino acids which forms a similar plane 4.8 Angstroms thick, such that two 60 amino acid monomers bind to each other.

Feel free to use any computational or theoretical devices currently at our disposal, density functional theory, force fields, rosetta etc. etc.

Answers to follow shortly

Hint:  hundreds to thousands of planes can stack on top of each other.

Also I’ve written about phase changes in the past — https://luysii.wordpress.com/2020/12/20/neuroscience-can-no-longer-ignore-phase-separation/

A superb review of the subject is available if you have a subscription to Neuron [ Neuron vol. 109 pp. 2663 – 2681 ’21 ]

Cassava Sciences — the clinical reality underneath the stock gyrations.

The stock of Cassava Sciences (symbol SAVA) has undergone some wild gyrations this year.  On 14 September it traded at 41.70, today just two weeks later it is trading in the upper 60s.

The important thing to keep in mind, is that 1 year out on treatment with SAVA’s drug Simufilam 50 patients with mild Alzheimer disease were (as a group) slightly improved.  This is absolutely unprecedented.  The best that previous therapy could accomplish was a slightly slower rate of decline — see arshttps://science.sciencemag.org/content/sci/373/6555/624.full.pdf — for a recent review of other therapy attempts.  So Cassava’s results are unprecedented.   While Alzheimer (and other dementia) patients fluctuate from day to day (like the tides from minute to minute) at the end of a year they are all worse.

These results have not been attacked, unlike their data on the effect of Simufilam on biomarkers which has been criticized by a person of standing — Elizabeth Bik — https://scienceintegritydigest.com/2021/08/27/cassava-sciences-of-stocks-and-blots/#more-2692.

But that’s irrelevant and guilt by association at best.  As a clinical neurologist, no one was ever brought to see me because of their biomarkers.

They have released part of their 1 year results — https://www.cassavasciences.com/news-releases/news-release-details/cassava-sciences-announces-top-line-results-12-month-interim.  There is a lot more that I’d like to know, but a press release is not a detailed scientific paper.

What follows is a lot of commentary and speculation about the 1 year data which we haven’t seen yet.

The results concern the first 50 patients to complete one year on the drug.  The dropout rate is stated to be under 10%.  Presumably this includes death, in a cohort (presently at around 200) with a significant mortality.  It would be interesting to know how many patients on entry made it to one year.

As a clinical neurologist I was particularly impressed with part of their data at 9 months.  Here’s a link — keep it handy — https://www.cassavasciences.com/static-files/13794384-53b3-452c-ae6c-7a09828ad389.

They measured cognitive changes by something called ADAS-Cog — a full description can be found in the following post — https://luysii.wordpress.com/2021/08/25/cassava-sciences-9-month-data-is-probably-better-than-they-realize/

ADAS-Cog score counts errors, so a perfect score would be 0, and a terrible score would be 70.  The range of deficit on entry was 16 – 26 (but possibly on something else called the MMSE) — this is what the 1 year results used.  The 9 month results used ADAS-Cog.  Perhaps they are actually the same thing — I don’t know.

On the link — https://www.cassavasciences.com/static-files/13794384-53b3-452c-ae6c-7a09828ad389 — look at the diagram titled “Individual Patient Changes in ADAS-Cog (N = 50).

There were 5 patients out of 50 at 9 months with improvements of 11 – 14, which would mean that they were pretty close to normal if their entry score was 16 and 50% improved if their score was 26.  From here out I’m just calling them ‘the 5’.

The 9 month report doesn’t discuss this, and only a clinician would know, but this is the way neurologic patients respond to treatment.  Some do extremely well while others have no effect.  Why?  It’s probably because not really understanding causation, we classify patients clinically (it’s all docs have after all).

I ran a Muscular Dystrophy Clinic for 15 years back in the day.  The Muscular Dystrophy Association was founded by parents of weak kids.  They didn’t know that some weakness was due to the muscle itself (what we’re now calling muscular dystrophy), some was due to disease affected the nerves from the spinal cord to the muscle (what we call a neuropathy now) and others were due to disease of the cells in the spinal cord giving rise to the nerves to the muscle (motor neuron disease).  That all came later.

It is quite presumptuous to say that Alzheimer’s disease is just one thing.  Perhaps the 5 patients doing so very well had it from a different (as yet unknown) cause than the other 45.  Even so such a treatment would be worth having.

So here are a few questions for the folks at Cassava about their data

l. Some 16 different sites were involved in the open label study.  Were all of ‘the 5’  from the same site (doubtful — but if true, perhaps they tested ADAS-Cog differently, casting doubt on these results).

2. What were the ADAS-Cog scores initially on ‘the 5’.

3. What happened to ‘the 5’ in the past 3 months (did they maintain improvement, slide back, or improve further?)

4. We must have lots more people passing the 3, 6, 9 month markers.  Have their results paralleled that of the first 50 reaching the mileposts?   It would be very useful to know if there are now more than 5 with improvements over 10 in ADAS-Cog at 9 months.

The slightly slowing of improvement at 1 year relative to 9 months is typical of neurologic disease.  When L-DOPA was first available in the USA in 1970, some patients because so normal that you couldn’t tell they had Parkinson’s disease, and for a few years, neurologists (myself included) thought we were actually curing the disease.  Of course we weren’t and the underlying pathology of Parkinsonism (death of neurons using dopamine) continued unabated.  The L-DOPA just helped the surviving neurons function more efficiently.  Something similar may be going on with Simufilam and Alzheimer’s.

Now for some blue sky about Simufilam. Just as the gray hair on the head of an 80 year old looks the same under the microscope as one from a prematurely gray 30 year old, the brain changes of Alzheimer’s disease (the senile plaque)  are the same regardless of the age of onset.  Assuming that the senile plaque is in someway related to dementia (despite the lack of effect of therapies trying to remove it) and given that we all accumulate a few as we age, could Simufilam improve cognition in the elderly?   Would it then be intellectual viagra and the blockbuster drug of all blockbuster drugs.

 

Spot the flaw in this argument — I didn’t

The following sentence appeared in an article in the latest (24 September ’21)  Science.   ” In mid-August, after vaccine efficacy had started to wane and before the effects of boosters had taken hold, 59% of severe patients were fully vaccinated.”

This is far worse than ’started to wane’, given the following sentence from the same article “Israel’s vaccination rate—64% of its population has received at least two doses”

Put the two together (which the article really didn’t do) and you see that at most the vaccine was giving at most 5% protection against severe infection, which is really no protection at all.

The null hypothesis is that the rates of severe COVID19 in the vaccinated and unvaccinated should be the same, and the percentages cited above seems to bear that out.  

What’s wrong?  Something called the Simpson paradox — https://en.wikipedia.org/wiki/Simpson%27s_paradox

Start by assuming 100% of the population vaccinated, then all breakthrough hospitalizations will be in the vaccinated group, which means nothing. The point is that the vaccinated groups of Israeli’s are much different than the unvaccinated.    Note the unstated assumption in the above paragraph in bold type — we’re assuming that vaccination in the Israeli population is a random event.

But of course vaccination was never random.  Those at higher risk (the elderly, the immunodeficient for whatever reason) were vaccinated first.  So there are a lot of them to have breakthroughs, and they will have more breakthroughs because their immune systems aren’t as strong.

“Among Israeli adults under 50, as of Aug. 15, 3.5 million were vaccinated and 1.1 million were not. That’s still a considerable number of vaccine holdouts. Among those 3.5 million vaccinated younger people, just 11 were hospitalized — about three per million. Meanwhile, of the unvaccinated in this age range, 43 were in the hospital, or 39 per million.

Note that hospitalizations of young people for both the vaccinated and unvaccinated are low, because younger people rarely suffer the severest illness from covid-19. (Their immune systems are stronger)l Still, vaccination reduced the rate of hospitalization more than 10-fold in the population under 50.

Now look at the population 50 and older. There are 2.1 million vaccinated Israelis over 50, and 290 were in the hospital Aug. 15. That’s 136 per million, a rate that dwarfs anything younger people are experiencing. And unvaccinated older Israelis? There are very few people in that category: just 186,000. But of that group, 171 were hospitalized — a grievously higher rate of 919 per million. In the older population, vaccinated people were less than one-sixth as likely to be hospitalized as the unvaccinated.”

I thank a friend for pointing out the error of my ways.

Even so only in the under 50 group can vaccination be said to provide > 90% protection against severe infection.  In the over 50 group the protection is 84% — still not bad

Long time no post

Switching to a new computer and a new eMail has been nothing short of a time consuming disaster, not to say expensive.  I should start posting again this week.  See the previous post for why you must continually update your data to keep it accessible.

I do recommend an excellent review article on phase transitions in the cell [ Neuron vol. 109 pp.. 2663 – 2681 ’21 ] which tries to make sense of the chemistry behind it, particularly focusing on RNA.  Unfortunately it is likely behind a paywall.  I have written on the subject a while back, so here’s a link — https://luysii.wordpress.com/2020/12/20/neuroscience-can-no-longer-ignore-phase-separation/.  Now that people are looking for it, new examples are constantly being found.  It’s in chromatin. It’s at the synapse etc. etc.

Now a plea for help.  The hardest thing about shifting my database to Mathematica is finding a way to sort it.  This was no problem at all for Filemaker or Hypercard.  All you had to do was type sort and the programs did the rest.  Well no I have to do it.

Does anyone out there have any ideas what sort of internal data structures are available to keep 22K cards coherent and search them, while modifying them by continuing to read the literature.

No one will be able to access your data in 20 years

Hardware changes all the time requiring new software to use it even for the ‘same’ program.

 

Consider my history with HyperCard, a great Apple program I started using in 1987.  Apple didn’t support it after it moved away from Operating system 9 — new hardware managed memory differently.  So I was left with OS  X which still had a way to access OS 9 even though the processor was a 2.1 GigaHertz PowerPC.

Then newer hardware no longer accessed even the power PC, so as long my iMac G5 held out I was OK.  But hardware doesn’t last forever, so I tried to migrate my database to FileMaker Pro, another Apple product (although they tried to keep this quiet).

Filemaker documentation is simply horrible. Example: they don’t tell you what the reserved words are believe it or not.

So I’m currently trying to migrate my HyperCard database to Mathematica.  I had bought Mathematica 10 and the computer it runs on in 2015.  It was a macBook Pro with a 2.2 GigaHertz Intel Core i7.  But this year the battery started swelling (which Apple offered to replace for free), and worrying about exploding batteries in cars, I decided to move on.

So I bought the latest macBook Pro, which has 64 bit hardware instead of the 32 bit hardware of the old macBook Pro.  This means that Mathematica10 won’t work on the new computer so I must upgrade to Mathematica 12.

Well  what you get when you actually try to open a Mathematica notebook written in Mathematica 10 on the new machine is something like this.

(* Content-type: application/vnd.wolfram.mathematica *)

(*** Wolfram Notebook File ***)
(* http://www.wolfram.com/nb *)

(* CreatedBy=’Mathematica 10.0′ *)

(*CacheID: 234*)
(* Internal cache information:
NotebookFileLineBreakTest
NotebookFileLineBreakTest
NotebookDataPosition[ 158, 7]
NotebookDataLength[ 69720, 1756]
NotebookOptionsPosition[ 63597, 1546]
NotebookOutlinePosition[ 64410, 1576]
CellTagsIndexPosition[ 64240, 1569]
WindowFrame->Normal*)

(* Beginning of Notebook Content *)
Notebook[{
Cell[BoxData[
RowBox[{“(*”, ” “, “W645″, ” “, “*)”}]], “Input”,
CellChangeTimes->{{3.8400255875558558`*^9, 3.840025593274387*^9}}],

Cell[CellGroupData[{

Cell[BoxData[
RowBox[{“newList”, ” “, “=”, ” “,
RowBox[{“ReadList”, ” “, “[“, ” “,
RowBox[{
“\”\</Users/lewisrobinson/Desktop/ Cards 9461 to 9462\>\””, ” “, “,”,
” “, “string”}], ” “, “]”}]}]], “Input”,
CellChangeTimes->{{3.8400252429862013`*^9, 3.840025260918976*^9}, {
3.840025304055138*^9, 3.840025325036539*^9}}],

Hardly readable or usable is it?  Presumably the as yet unpurchased Mathematica 12 will be able to read this notebook and put it into recognizable form on the new machine.

Now let’s move 20 years into the future.  Further new hardware, further new software.  Will you be able to find a machine like my new computer

  Model Name: MacBook Pro
  Model Identifier: MacBookPro16,1
  Processor Name: 6-Core Intel Core i7
  Processor Speed: 2.6 GHz
  Number of Processors: 1
  Total Number of Cores: 6
  L2 Cache (per Core): 256 KB
  L3 Cache: 12 MB
  Hyper-Threading Technology: Enabled
  Memory: 16 GB
  System Firmware Version: 1554.100.64.0.0 (iBridge: 18.16.14556.0.0,0)
  Serial Number (system): C02G8AS4MD6M
  Hardware UUID: 28C836B3-C406-5215-AB85-A25653ADF226
  Provisioning UDID: 28C836B3-C406-5215-AB85-A25653ADF226
  Activation Lock Status: Disabled

 

In 2041 will you (or your grandson) be able to find a copy of Mathematica 12 to run it on, as the newer versions are unlikely to run on such an old computer (as just happened).

 

I seriously doubt it, cloud or no cloud.   So maintaining your data is a never ending process.

We’re not as protected as we thought we were

We all know that the only people hospitalized and dying of COVID-19 are lower forms of animal life such as the rednecked Trumpenproletariat from the deep South.  Here’s the New York Times of less than a month ago — https://www.nytimes.com/interactive/2021/08/10/us/covid-breakthrough-infections-vaccines.html

“Serious coronavirus infections among vaccinated people have been relatively rare since the start of the vaccination campaign, a New York Times analysis of data from 40 states and Washington, D.C., shows. Fully vaccinated people have made up as few as 0.1 percent of and as many as 5 percent of those hospitalized with the virus in those states, and as few as 0.2 percent and as many as 6 percent of those who have died.”

Nothing to worry about up here in Massachusetts where roughly 2/3 of the population have been vaccinated.  Well that’s what I thought until Friday 3 September — when I saw this from the Massachusetts department of public health — https://www.masslive.com/coronavirus/2021/09/massachusetts-reports-1703-covid-cases-as-percentage-of-breakthrough-hospitalizations-continues-to-drop.html

149 of 609 hospitalizations (24%) with COVID19 had been fully vaccinated.  That is far from the protection we had been led to believe.  It could have been worse.  If the vaccination was totally useless,  the fully vaccinated should have made up 66% of the cases.  So there was some protection, but nothing like the New York Times and others were talking about a few weeks ago.

 

Addendum 26 September — There is a serious flaw in the above argument — for details please see — https://luysii.wordpress.com/2021/09/26/spot-the-flaw-in-this-argument-i-didnt/

So for the elderly, it’s back to restricted social contact and masks.

On a more personal note, I proved Richard Feynman right again.  He famously said ”

“The first principle is that you must not fool yourself — and you are the easiest person to fool.”

Well I certainly did.  I read the following article in the 27 August Science –https://www.science.org/content/article/grim-warning-israel-vaccination-blunts-does-not-defeat-delt

It contained the following statement. ” As of 15 August, 514 Israelis were hospitalized with severe or critical COVID-19, a 31% increase from just 4 days earlier. Of the 514, 59% were fully vaccinated.”

I even took notes on the article.  Yet somehow I chose to ignore it.  Why?  Too threatening?  Didn’t fit with what I’d been told?  Kahneman has shown just how irrational, those who call themselves rational turn out to be.  Mea Culpa.

Addendum  7 September — https://www.masslive.com/coronavirus/2021/09/breakthrough-covid-cases-in-massachusetts-up-to-about-40-while-unvaccinated-people-dominate-hospitalizations.html

“The state reported a total of 601 COVID hospitalizations Tuesday 7 September ’21. Data shows that 160 of the 601 hospitalizations are people who were fully vaccinated — about 26% of all COVID hospitalizations. ”

So the data of 3 September referred to earlier are to be believed and likely NOT a statistical fluke as they are essentially the same as today’s.

What controls should Cassava Sciences use for their open label trial?

MDs gradually woke up to the fallacy of using historical rather than concurrent controls particularly in studies of therapies to prevent heart attack and stroke, as the rates of both dropped significantly in the past 50 years, and survival from individual heart attacks and strokes also improved.

An open label trial is just that, no placebo, no controls.  Such trials are done in the exploratory phase of drug development to look for side effects and (hopefully) therapeutic effects.

Cassava Sciences has been attacked because their open label study of Simufilam had no controls.  Duh !

Here is a suggestion for the concurrent controls for the Cassava study:  the Biogen study leading to approval of aducanumab (Aduhelm).  It’s a little hard to find out exactly when it was done, but it certainly was within the past 10 years. Here is a link to an article on Alzheimer therapy from Science — https://science.sciencemag.org/content/sci/373/6555/624.full.pdf

Cassava’s work is nowhere to be found.  The article contains the following

“Although the marked decrease in amyloid deposits can be viewed as biological evidence of disease modification, this was accompanied by a decidedly mixed outcome on cognitive testing, with one aducanumab trial (EMERGE, NCT02484547) meeting its prespecified primary and secondary endpoints at the highest dose, whereas the other (ENGAGE, NCT02477800) did not achieve them.”

So use Biogen’s data on aducanumab as the placebo control (which I and the FDA advisory committee think it is).  There is a reason the entire committee resigned after the FDA approved the drug.