Why you do and don’t need chemistry to understand why we have big brains

You need some serious molecular biological chops to understand why primates such as ourselves have large brains. For this you need organic chemistry. Or do you? Yes and no. Yes to understand how the players are built and how they interact. No because it can be explained without any chemistry at all. In fact, the mechanism is even clearer that way.

It’s an exercise in pure logic. David Hilbert, one of the major mathematicians at the dawn of the 20th century famously said about geometry — “One must be able to say at all times–instead of points, straight lines, and planes–tables, chairs, and beer mugs”. The relationships between the objects of geometry were far more crucial to him than the objects themselves. We’ll take the same tack here.

So instead of the nucleotides Uridine (U), Adenine (A), Guanine (G), Cytosine (C), we’re going to talk about lock and key and hook and eye.

We’re going to talk about long chains of these four items. The order is crucial Two long chains of them can pair up only only if there are segments on each where the locks on one pair with the keys on the other and the hooks with the eyes. How many possible combinations of the four are there on a chain of 20 — just 4^20 or 2^40 = 1,099,511,621,776. So to get two randomly chosen chains to pair up exactly is pretty unlikely, unless in some way you or the blind Watchmaker chose them to do so.

Now you need a Turing machine to take a long string of these 4 items and turn it into a protein. In the case of the crucial Notch protein the string of locks, keys, hooks and eyes contains at least 5,000 of them, and their order is important, just as the order of letters in a word is crucial for its meaning (consider united and untied).

The cell has tons of such Turing machines (called ribosomes) and lots of copies of strings coding for Notch (called Notch mRNAs).

The more Notch protein around in the developing brain, the more the proliferating precursors to neurons proliferate before differentiating into neurons, resulting in a bigger brain.

The Notch string doesn’t all code for protein, at one end is a stretch of locks, keys, hooks and eyes which bind other strings, which when bound cause the Notch string to be degraded, mean less Notch and a smaller brain. The other strings are about 20 long and are called microRNAs.

So to get more Notch and a bigger brain, you need to decrease the number of microRNAs specifically binding to the Notch string. One particular microRNA (called miR-143-3p) has it in for the Notch string. So how did primates get rid of miR-143-3p they have an insert (unique to them) in another string which contains 16 binding sites for miR-143-3p. So this string called lincND essentially acts as a sponge for miR-143-3p meaning it can’t get to the Notch string, meaning that neuronal precursor cells proliferate more, and primate brains get bigger.

So can you forget organic chemistry if you want to understand why we have big brains? In the above sense you can. Your understanding won’t be particularly rich, but it will be at a level where chemical explanation is powerless.

No amount of understanding of polyribonucleotide double helices will tell you why a particular choice out of the 1,099,511,621,776 possible strings of 20 will be important. Literally we have moved from physicality to the realm of pure ideas, crossing the Cartesian dichotomy in the process.

Here’s a copy of the original post with lots of chemistry in it and all the references you need to get the molecular biological chops you’ll need.

Why our brains are large: the elegance of its molecular biology

Primates have much larger brains in proportion to their body size than other mammals. Here’s why. The mechanism is incredibly elegant. Unfortunately, you must put a sizable chunk of recent molecular biology under your belt before you can comprehend it. Anyone can listen to Mozart without knowing how to read or write music. Not so here.

I doubt that anyone can start from ground zero and climb all the way up, but here is all the background you need to comprehend what follows. Start here — https://luysii.wordpress.com/2010/07/07/molecular-biology-survival-guide-for-chemists-i-dna-and-protein-coding-gene-structure/
and follow the links (there are 5 more articles).

Also you should be conversant with competitive endogenous RNA (ceRNA) — here’s a link — https://luysii.wordpress.com/2014/01/20/why-drug-discovery-is-so-hard-reason-24-is-the-3-untranslated-region-of-every-protein-a-cerna/

Also you should understand what microRNAs are — we’re still discovering all the things they do — here’s the background you need — https://luysii.wordpress.com/2015/03/22/why-drug-discovery-is-so-hard-reason-26-were-discovering-new-players-all-the-time/weith.

Still game?

Now we must delve into the embryology of the brain, something few chemists or nonbiological type scientists have dealt with.

You’ve probably heard of the term ‘water on the brain’. This refers to enlargement of the ventricular system, a series of cavities in all our brains. In the fetus, all nearly all our neurons are formed from cells called neuronal precursor cells (NPCs) lining the fetal ventricle. Once formed they migrate to their final positions.

Each NPC has two choices — Choice #1 –divide into two NPCs, or Choice #2 — divide into an NPC and a daughter cell which will divide no further, but which will mature, migrate and become an adult neuron. So to get a big brain make NPCs adopt choice #1.

This is essentially a choice between proliferation and maturation. It doesn’t take many doublings of a NPC to eventually make a lot of neurons. Naturally cancer biologists are very interested in the mechanism of this choice.

Well to make a long story short, there is a protein called NOTCH — vitally important in embryology and in cancer biology which, when present, causes NPCs to make choice #1. So to make a big brain keep Notch around.

Well we know that some microRNAs bind to the mRNA for NOTCH which helps speed its degradation, meaning less NOTCH protein. One such microRNA is called miR-143-3p.

We also know that the brain contains a lncRNA called lncND (ND for Neural Development). The incredible elegance is that there is a primate specific insert in lncND which contains 16 (yes 16) binding sites for miR-143-3p. So lncND acts as a sponge for miR-143-3p meaning it can’t bind to the mRNA for NOTCH, meaning that there is more NOTCH around. Is this elegant or what. Let’s hear it for the Blind Watchmaker, assuming you have the faith to believe in such things.

Fortunately lncND is confined to the brain, otherwise we’d all be dead of cancer.

Should you want to read about this, here’s the reference [ Neuron vol. 90 pp. 1141 – 1143, 1255 – 1262 ’16 ] where there’s a lot more.

Historically, this was one of the criticisms of the Star Wars Missile Defense — the Russians wouldn’t send over a few missles, they’d send hundreds which would act as sponges to our defense. Whether or not attempting to put Star Wars in place led to Russia’s demise is debatable, but a society where it was a crime to own a copying machine, could never compete technically to produce such a thing.

Where did this quote appear?

The following quote appeared in a major newspaper the day before the Brexit vote. Guess which one.

“David Cameron, the British prime minister has no one to blame but himself… made a promise … if re-elected, he would hold an in or out referendum on continued British membership” (in the EU).

The article goes on in this vein about what a mistake this was. Allowing people to actually vote, or as the article says “what many consider to be a wholly unnecessary roll of the dice”.

Various British mandarins are quoted as to the wisdom of Cameron’s decision, and a variety of arguments against Brexit are trotted out “sharp tones of xenophobia, racism, nativism and Islamophobia” — this by the authors of the article. No arguments for Brexit are given (as if any reasonable person could be in favor).

So where was it published? Pravda? Granma? People’s Daily?

No, the front page of the New York Times.

It’s the typical New York Times ploy of masquerading an opinion piece as a news article.

This is something I despise (see — https://luysii.wordpress.com/2016/02/03/helping-hillary-along/).

Not this time though. It is a perfect example of the elitist (and leftist) impulse of the Times in full cry. We know what’s best. The people are not to be trusted, but ruled by decree by their betters (vide Obama’s 13 million amnesty, and the BLM’s attempt to control fracking despite a law passed by congress).

It’s very good to see elite opinion lose. Americans should be aware that Brexit was opposed by the heads of all political parties, business elites, academic elites, Nature and the scientific elites, the church — essentially every class of elite imaginable. Perhaps this was its high tide.

Why our brains are large: the elegance of its molecular biology

Primates have much larger brains in proportion to their body size than other mammals. Here’s why. The mechanism is incredibly elegant. Unfortunately, you must put a sizable chunk of recent molecular biology under your belt before you can comprehend it. Anyone can listen to Mozart without knowing how to read or write music. Not so here.

I doubt that anyone can start from ground zero and climb all the way up, but here is all the background you need to comprehend what follows. Start here — https://luysii.wordpress.com/2010/07/07/molecular-biology-survival-guide-for-chemists-i-dna-and-protein-coding-gene-structure/
and follow the links (there are 5 more articles).

Also you should be conversant with competitive endogenous RNA (ceRNA) — here’s a link — https://luysii.wordpress.com/2014/01/20/why-drug-discovery-is-so-hard-reason-24-is-the-3-untranslated-region-of-every-protein-a-cerna/

Also you should understand what microRNAs are — we’re still discovering all the things they do — here’s the background you need — https://luysii.wordpress.com/2015/03/22/why-drug-discovery-is-so-hard-reason-26-were-discovering-new-players-all-the-time/weith.

Still game?

Now we must delve into the embryology of the brain, something few chemists or nonbiological type scientists have dealt with.

You’ve probably heard of the term ‘water on the brain’. This refers to enlargement of the ventricular system, a series of cavities in all our brains. In the fetus, all nearly all our neurons are formed from cells called neuronal precursor cells (NPCs) lining the fetal ventricle. Once formed they migrate to their final positions.

Each NPC has two choices — Choice #1 –divide into two NPCs, or Choice #2 — divide into an NPC and a daughter cell which will divide no further, but which will mature, migrate and become an adult neuron. So to get a big brain make NPCs adopt choice #1.

This is essentially a choice between proliferation and maturation. It doesn’t take many doublings of a NPC to eventually make a lot of neurons. Naturally cancer biologists are very interested in the mechanism of this choice.

Well to make a long story short, there is a protein called NOTCH — vitally important in embryology and in cancer biology which, when present, causes NPCs to make choice #1. So to make a big brain keep Notch around.

Well we know that some microRNAs bind to the mRNA for NOTCH which helps speed its degradation, meaning less NOTCH protein. One such microRNA is called miR-143-3p.

We also know that the brain contains a lncRNA called lncND (ND for Neural Development). The incredible elegance is that there is a primate specific insert in lncND which contains 16 (yes 16) binding sites for miR-143-3p. So lncND acts as a sponge for miR-143-3p meaning it can’t bind to the mRNA for NOTCH, meaning that there is more NOTCH around. Is this elegant or what. Let’s hear it for the Blind Watchmaker, assuming you have the faith to believe in such things.

Fortunately lncND is confined to the brain, otherwise we’d all be dead of cancer.

Should you want to read about this, here’s the reference [ Neuron vol. 90 pp. 1141 – 1143, 1255 – 1262 ’16 ] where there’s a lot more.

Historically, this was one of the criticisms of the Star Wars Missile Defense — the Russians wouldn’t send over a few missles, they’d send hundreds which would act as sponges to our defense. Whether or not attempting to put Star Wars in place led to Russia’s demise is debatable, but a society where it was a crime to own a copying machine, could never compete technically to produce such a thing.

Overweight is Good, Obesity is not.

“The attached article from the latest edition of Science News reports on a new study showing that the BMI associated with lowest mortality is 27 — FAT!” If a Berkeley PhD can be led astray by such an article, it’s time to set the record straight. The problem comes from conflating a term of art (overweight — BMI { Body Mass Index } between 25 and 30) with another (obese — BMI over 30). A BMI of 27 isn’t FAT but a BMI of 30 is. But normal people (even a Berkeley PhD) use the words fat and overweight interchangeably. To an obesity researcher they are not (in fact they don’t use the term fat at all).

To get started, calculate your own BMI– http://bmicalculator.cc/?gclid=CM66rIG2tc0CFYQ2gQodOdINEg. Don’t worry that BMI is usually given in kiloGrams and Meters, the site lets you put in your weight in pounds and your height in feet and inches. A 6 footer would have to weigh 222 pounds to be obese.

I’ve been posting that something is wrong with our model of obesity and mortality for years. The Nation continues to get fatter and fatter, and yet lifespan continues to increase. After *** you’ll find a post of 2013 about a paper showing that as we get older, the lowest mortality is with a BMI over 25, increasing each decade.

The new paper cited is interesting, as several different cohorts of the (rather homogeneous) Danish population were studied over time. The BMI of least mortality changed depending on when the cohort was recruited (1976 to 1978) vs. 2003 to 2013. The minimum mortality was 23.7 for the first cohort and 27 for the second.

Should you gain or lose weight to get to a BMI of 27? Not at all, although every continuous curve must have one low point, the mortality rate is pretty much the same between BMIs of 25 and 30. It would be like not going to Yellowstone to increase your chance of survival. Granted road travel has a risk and there are probably no bears where you live, but the increment in survival is not worth tying yourself in knots about.

What you should absolutely not conclude, is that if a BMI of 27 is OK, a BMI 30 and over is as well.  It most certainly is not, and mortality rapidly increases with BMIs over 30.  The higher you go the worse it gets.

Here’s the older post with a lot more discussion of these matters.

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Something is wrong with the model — take 2

Nearly 4 years ago I wrote a post about the disconnect between the increasing longevity of the US population and its increasing obesity. You can read the whole thing after the ****. The post was titled “Something is Wrong with the Model”. Indeed something is. It doesn’t fit with a lot of data. Those proposing the model don’t like this at all. You can read all about the brouhaha in the 23 May issue of Nature (pp. 428 – 430).

In general I tend to skip medical articles involving meta-analysis under the garbage in garbage out theory. The most egregious example was Women’s Health Initiative when 3 separate meta-analyses of a bunch of uncontrolled studies concluded that estrogen replacement therapy decreased the risk of coronary heart disease by 35 – 50%. The gigantic (161,100 women followed for 12 years, with 1,000,000 clinic visits) Women’s Health Initiative trial of hormone therapy to prevent coronary disease was halted earlier than planned when it was found estrogen based therapies increasedthe risk of coronary heart disease, stroke and breast cancer.

The excitement was over a paper [ J. Am. Med. Assoc. vol. 309 pp. 71 – 82 ’13 ] which performed a meta-analysis on 97 studies of body weight and mortality which in aggregate involved nearly 3 million people.

A popular measure of weight is the body mass index (BMI) which is weight in kiloGrams divided by your height in Meters squared. Not something which is obvious. If you want to figure yours know that a kiloGram is 2.2 pounds, and a meter is 39.37 inches.

At any rate a BMI over 25 is considered overweight, and one over 30 is considered obese. At 6 feet 1+ (which I used to be) a weight of 190 puts me at 24.69. To be obese (BMI over 30) I’d need to weight 228 (which I almost did 50 years ago).

When you plot BMI vs. probability of death you get a U shaped cure, with the very thin and the very fat showing increased risk of dying (mortality). The Nature paper is interesting as it shows 6 curves for people at ages 20, 30, 40, 50, 60, 70. As one might expect the curves for each age lie below the next oldest. All of them rise with BMIs under 20 and over 30, so there’s no argument about whether obesity is bad for longevity.

Well, if the curve is U shaped, it has a minimum. The excitement comes in because the healthiest weight (the minimum) is a BMI of just over 25 for those in their 60s and around 26 for those in their 70s. Also in ALL 6 age groups the curve is pretty flat between 25 and 30, rising on either side of the range.

Naturally people who’ve invested their research careers in telling everyone to diet and that weight is bad, don’t like this, and a symposium involving 200 unhappy people convened 20 February at the Harvard School of Public Health is described, along with a lot of the back and forth between the authoress of the study (Flegel) and Willett of Harvard who didn’t like it one bit. The best comment IMHO is from Robert Eckel “We’re scientists. We pay attention to data, we don’t try to un-explain them.” Read the article, it’s well written and there’s a lot more.

One final point, which might explain why the minima of the curves shift to higher BMIs at older age — which the article didn’t contain. People lose height as they age, yet the BMI is quite sensitive to it (remember the denominator has height squared). The great thing about BMI is that it’s easily measured, and doesn’t rely on what people remember about their weight or their height. Well as a high school basketball player my height was 6′ 1”+, now (at age 75) its 6’0″. So even with constant weight my BMI goes up.

Well it’s time to do the calculation to see what a fairly common shrinkage from 73.5 inches to 72 would to to the BMI (at a constant weight). Surprisingly it is not trivial — (72/73.5) * (72/73.5) = .9596. So the divisor is 4% less meaning the BMI is 4% more, which is almost exactly what the low point on the curve does with each passing decade after 50 ! ! ! This might even be an original observation, and it would explain a lot.

****
Something is wrong with the model

Back in grad school when a theory came up with a wrong prediction, we all clapped hands because it showed us exactly where a new theory was needed, and just how it failed. No casting about for something to work on. A program that crashes intermittently is very hard to fix. Once you’ve found input that consistently makes it crash the job becomes much easier.

The Center for Disease Control released new data for 2007 (based on 90% of all USA death certificiates) showing that mortality rates dropped again (by over 2%) to 760/100,000 population. It’s been dropping for the past 8 years, and viewed longer term is half of what it was 60 years ago. Interestingly death rates from heart disease dropped a staggering 5% and even cancer dropped 2%.

But the populace is fat and getting fatter. This has been going on for 30 years. You can Google NHANES for the gory details, but the following should be enough. [ Science vol. 299 pp. 853 – 855, 856 – 858 ’03 ] The data from a recent NHANES (’99 – ’00) shows that the percentage of obese (as opposed just overweight) increased from 23% in the surveys from ’88 to ’94 to 31%. This is based on the body mass index (BMI). Someone 6′ 1″ would have to weigh 225 pounds to be obese.

We are told to be prepared for an epidemic of diabetes, high blood pressure, elevated blood lipids because of this. Every doc has seen blood sugar drop, blood pressure lowered, lipids come down in people with any/all of the above when they are able to lose a significant amount of weight. These diseases are significant only if they kill people, which they certainly seem to do in my experience. The next time you’re visiting a friend in the hospital, look at what’s lying in the beds. Very likely, many more than 31% of them are obese.

So why are death rates dropping and people living longer? Something must be wrong with the model — it’s pretty hard to quarrel with the data as being inadequate. Certainly the increased incidence of obesity should have produced something by this time (it started 30 years ago).

Well, the self serving answer for the drug developers is that their drugs are better. MDs would like to think it’s due to better care. Possibly. Here’s some detail.

#1: More people are exercising than they used to. How many joggers and walkers did you see on the streets 20, 30 years ago?

#2: Fewer people are smoking. Forget lung cancer (if you can). The big risk for smokers is premature vascular disease. Normally we all have carbon monoxide in our blood (it comes from the breakdown of hemoglobin). [ Brit. Med. J. vol. 296 pp. 78 – 79 ’88 ] Natural carbon monoxide production would lead to a carboxyhemoglobin level of .4 – .7%, but normal levels in nonsmokers in urban areas are 1 – 2%. Cigarette smoke contains 4% carbon monoxide, so smokers have levels of 5 – 6%. This can’t be good for their blood vessels.

#3: Doctors know more than they did. My brother is a very competent internist. He took over the practice of a similarly competent internist after his very untimely many death years ago. Naturally he got all the medical records on the patients. He found letters (now over 25 years old) from the late MD to his patients informing them of their lab results, and assuring them that their cholesterol was just fine at 250 mg%.

#4: The drugs are better. In addition they may be working in ways that we have yet to fathom. Consider the statins — their effect on vascular disease is far greater than their effect on blood lipids (cholesterol, triglycerides) — particularly when compared to other agents that lower blood lipids to the same extent.

The impeccable timing of the New York Times

After putting ex-Weatherman Bill Ayers on page 1 saying he wished he’d ‘bombed more’ the day of the attack on the World Trade Center in 2001, the New York Times kept its unenviable timing record intact by posting “Dreams of my Muslim Son” about Islamophobia on the editorial page the day of the Orlando massacre. Usually they run their invariable innocent Muslims fearing hate crimes by American rednecks story a day or so after the latest atrocity.

Unfortunately Orlando can’t be camouflaged as workplace violence or the response to some video or other a la Benghazi. The perp was far too explicit. Nor can it be blamed on the failure of ‘the MidEast Peace Process’ or Israel, although undoubtedly some will try.

If I were the Muslim leadership in this country, I’d try to put together a Million Muslim March on Washington to protest the Orlando, San Bernadino, Boston etc. etc. massacres, as blots on the name of Islam. ISIS would probably try to kill a few, but it’s time for them to stand up, assuming there are large numbers of US Muslims that actually think this way.

Reproducibility and its discontents

“Since the launch of the clinicaltrials.gov registry in 2000, which forced researchers to preregister their methods and outcome measures, the percentage of large heart-disease clinical trials reporting significant positive results plummeted from 57% to a mere 8%”. I leave it to you to speculate why this happened, but my guess is that probably the data were sliced and diced until something of significance was found. I’d love to know what the comparable data is on anti-depressant trials. The above direct quote is from Proc. Natl. Acad. Sci. vol. 113 pp. 6454 – 6459 ’16. The article looked at the 100 papers published in ‘top’ psychology journals, about which much has been written — here’s the reference to the actual paper — Open Science Collaboration (2015) Psychology. Estimating the reproducibility of psychological science. Science 349(6251):aac4716.

The sad news is that only 39% of these studies were reproducible. So why beat a dead horse? The authors came up with something quite useful — they looked at how sensitive to context each of the 100 studies actually was. By context they mean the time of the study (e.g., pre- vs. post-Recession), culture (e.g., individualistic vs. collectivistic culture), the location (e.g., rural vs. urban setting), or the population (e.g., a racially diverse population vs. a predominantly White or Black or Latino population). Their conclusions were that the contextual sensitivity of the research topic was associated with replication success (e.g. the more context sensitive, the less likely it was that the study could be reproduced). This was even after statistically adjusting for several methodological characteristics (e.g., statistical power, effect size, etc. etc). The association between contextual sensitivity and replication success did not differ across psychological subdisciplines.

Addendum 15 June ’16 — Sadly, the best way to say this is — The more likely a study is to be true (replicable) the more likely it is to be not generally applicable (e.g. useful).

So this is good. Up to now the results of psychology studies have been reported in the press as of general applicability (particularly those which enforce the writer’s preferred narrative). Caveat emptor is two millenia old. Carl Sagan said it best — “Extraordinary claims require extraordinary evidence.”

For an example data slicing and dicing, please see — https://luysii.wordpress.com/2009/10/05/low-socioeconomic-status-in-the-first-5-years-of-life-doubles-your-chance-of-coronary-artery-disease-at-50-even-if-you-became-a-doc-or-why-i-hated-reading-the-medical-literature-when-i-had-to/

ONTX Good news and semibad news.

The stock I recommended 1 June (ONTX) was up 11% today on a fourfold increase in volume. The rationale based on a Cell paper (vol. 165 pp. 643 – 655 ’16 ) will be found in a copy of the entire post below the ****

It is worth looking at the chart — https://finance.yahoo.com/echarts?s=ONTX+Interactive#{“range”:”1d”,”allowChartStacking”:true}

After a delay in opening, it exploded most of the way up on high volume (for it). Why? My guess is that people looked at the poster of the study in progress using their Ras blocking drug Rigosertib. Who looked? Why some of the 30,000 attendees at the 2016 American Society of Clinical Oncology Annual Meeting in Chicago, Illinois.

Why is this good (aside from the rise)? Assuming the people who bought ONTX were attendees at the convention, these are very informed buyers (e.g. professional oncologists) laying down their long green (e.g. very smart money).   In one of the many books I read about the Bernie Madoff Ponzi scheme, the people who invested with him were described as ‘dumb money’. They’d made their pile elsewhere and were babes in the woods when it came to investing.

Why is this also bad for what I predicted? Have a look at the abstract of one of the posters. Here’s a link to it —
http://meetinglibrary.asco.org/content/165681-176

The skinny is that the phase III study I was so excited about began only last December. It likely will be years before the results will be in. So goodbye 10x – 100x pop in the stock right away. Possibly big pharma will be impressed with their work and buy out the company which should also mean a significant gain.

Now 30,000 people can’t crowd around a single poster presentation. The stock is likely to continue moving up on volume this week as word spreads from the people who’ve already bought it and more people see the possibilities.

Here’s the post of 1 June — note that I didn’t own ONTX when I wrote the first post 3 May ’16, but did when I wrote the 1 June post.

*****

In a gambling mood?

If a pair of posters to be presented Monday 6 June at the 2016 American Society of Clinical Oncology Annual Meeting in Chicago, Illinois, contains the results of a phase III clinical trial of rigosertib, and if the results are as good as a paper discussed below the stock Onconova Therapeutics (ONTX) will jump by a factor of 10 to 100.

Full disclosure: I own some. The posters may just describe the clinical trial rather than report the results in which case all bets are off. In that case, I’ll just hold the stock until the results are in. This isn’t the ‘pump and dump’ beloved of boiler room operators everywhere. The rationale for the drug and my take on the original paper (3 May ’16) are reproduced below.

Has the great white whale of oncology finally been harpooned?

The ras oncogene is the great white whale of oncology. Mutations in 20 – 40% of cancer turn its activity on so that nothing can turn it off, resulting in cellular proliferation. People have been trying to turn mutated ras off for years with no success.

A current paper [ Cell vol. 165 pp. 643 – 655 ’16 ] describes a new and different way to attack it. Once ras is turned on (either naturally or by mutation) many other proteins must bind to it, to produce their effects — they are called RAS effectors, among which are the uneuphoniously named RAF, RalGDS and PI3K. They bind to activated ras by the cleverly named Ras Binding Domain (RBD) which has 78 amino acids.

The paper describes rigosertib, a not that complicated molecule to the chemist, which inhibits the binding (by resembling the site on ras that the RBD binds to). It is a styryl benzyl sulfone and you can see the structure here — https://en.wikipedia.org/wiki/Rigosertib.

What’s good about it? Well it is in phase III trials for a fairly uncommon form of cancer (myelodysplastic syndrome). That means it isn’t horribly toxic or it wouldn’t have made it out of phase I.

Given the mechanism described, it is possible that Rigosertib will be useful in 20 – 40% of all cancer. Can you say blockbuster drug?

Do you have a speculative bent? Buy the company testing the drug and owning the patent — Onconova Therapeutics. It’s quite cheap — trading at $.40 (yes 40 cents !). It once traded as high as $30.00 — symbol ONTX. I don’t own any (yet), but for the price of a movie with a beer and some wings afterwards you could be the proud owner of 100 shares. If Rigosertib works, the stock will certainly increase more than a hundredfold.

Enough kidding around. This is serious business. In what follows you will find some hardcore molecular biology and cellular physiology showing just what we’re up against. Some of the following is quite old, and probably out of date (like yours truly), but it does give you the broad outlines of what is involved.

The pathway from Ras to the nucleus

The components of the pathway had been found in isolation (primarily because mutations in them were associated with malignancy). Ras was discovered as an oncogene in various sarcoma viruses. Mutations in ras found in tumors left it in a ‘turned on’ state, but just how ras (and everything else) fit into the chain of binding of a growth factor (such as platelet derived growth factor, epidermal growth factor, insulin, etc. etc.) to its receptor on the cell surface to alterations in gene expression wasn’t clear. It is certain to become more complicated, because anything as important as cellular proliferation is very likely to have a wide variety of control mechanisms superimposed on it. Although all sorts of protein kinases are involved in the pathway it is important to remember that ras is NOT a protein kinase.

l. The first step is binding of a growth factor to its receptor on the cell surface. The receptor is usually a tyrosine kinase. Binding of the factor to the receptor causes ‘activation’ of the receptor. Activation usually means increasing the enzymatic activity of the receptor in the tyrosine kinase reaction (most growth factor receptors are tyrosine kinases). The increase in activity is usually brought about by dimerization of the receptor (so it phosphorylates itself on tyrosine).

2. Most activated growth factor receptors phosphorylate themselves (as well as other proteins) on tyrosine. A variety of other proteins have domains known as SH2 (for src homology 2) which bind to phosphorylated tyrosine.

3. A protein called grb2 binds via its SH2 domain to a phosphorylated tyrosine on the receptor. Grb2 binds to the polyproline domain of another protein called sos1 via its SH3 domain. At this point, the unintiated must find the proceedings pretty hokey, but the pathway is so general (and fundamental) that proteins from yeast may be substituted into the human pathway and still have it work.

4. At last we get to ras. This protein is ‘active’ when it binds GTP, and inactive when it binds GDP. Ras is a GTPase (it can hydrolyze GTP to GDP). Most mutations which make ras an oncogene decrease the GTPase activity of RAS leaving it in a permanently ‘turned on’ state. It is important for the neurologist to know that the defective gene in type I neurofibromatosis activates the GTPase activity of ras, turning ras off. Deficiencies (in ras inactivation) lead to a variety of unusual tumors familiar to neurologists.

Once RAS has hydrolyzed GTP to GDP, the GDP remains bound to RAS inactivating it. This is the function of sos1. It catalyzes the exchange of GDP for GTP on ras, thus activating ras.

5. What does activated ras do? It activates Raf-1 silly. Raf-1 is another oncogene. How does activated ras activate Raf-1 ? Ras appears to activate raf by causing raf to bind to the cell membrane (this doesn’t happen in vitro as there is no membrane). Once ras has done its job of localizing raf to the plasma membrane, it is no longer required. How membrane localization activates raf is less than crystal clear. [ Proc. Natl. Acad. Sci. vol. 93 pp. 6924 – 6928 ’96 ] There is increasing evidence that Ras may mediate its actions by stimulating multiple downstream targets of which Raf-1 is only one.

6. Raf-1 is a protein kinase. Protein kinases work by adding phosphate groups to serine, threonine or tyrosine. In general protein kinases fall into two classes those phosphorylating on serine or threonine and those phosphorylating on tyrosine. Biochemistry has a well documented series of examples of enzymes being activated (or inhibited) by phosphorylation. The best worked out is the pathway from the binding of epinephrine to its cell surface receptor to glycogen breakdown. There is a whole sequence of one enzyme phosphorylating another which then phosphorylates a third. Something similar goes on between Raf-1 and a collection of protein kinases called MAPKs (mitogen activated protein kinases). These were discovered as kinases activated when mitogens bound to their extracellular receptors.There may be a kinase lurking about which activates Raf (it isn’t Ras which has no kinase activity). Removal of phosphate from Raf (by phosphatases) inactivates it.

7. Raf-1 activates members of the MAPK family by phosphorylating them. There may be several kinases in a row phosphorylating each other. [ Science vol. 262 pp. 1065 – 1067 ’93 ] There are at least three kinase reactions at present at this point. It isn’t known if some can be sidestepped. Raf-1 activates mitogen activated protein kinase kinase (MAPK-K) by phosphorylation (it is called MEK in the ras pathway). MAPK-K activates mitogen activation protein kinase (MAPK) by phosphorylation. Thus Raf-1 is actually mitogen activated protein kinase kinase kinase (sort of like the character in Catch-22 named Junior Junior Junior). (1/06 — I think that Raf-1 is now called BRAF)

8. The final step in the pathway is activation of transcription factors (which turn genes off or on) by MAP kinases by (what else) phosphorylation. Thus the pathway from cell surface is complete.

Mind the gap (junction that is)

Gap junctions don’t get much play in pharmacology, or even in neurology, where they are widespread in the central nervous system, linking neurons to neurons, astrocytes to astrocytes. They may get quite a bit more if blocking them is a way of treating metastatic disease (see later).

A bit of background if you’re unfamiliar with them. This is from my notes Molecular Biology of the Cell 4th Edition p. 1074

The gap junction is a cylindrical oligomer composed of 6 identical rod shaped subunits (called connexins). They have 4 transmembrane segments and two extracellular loops which contain a beta-strand structure (and which are an essential structural basis for the docking of the two connexons). Multiple connexons in a membrane tend to form hexagonal arrays.

The gap junction spans the lipid bilayer creating a channel along the central axis. The pore is made of two such protein hexamers one from each cell (called a hemichannel or a connexon) arranged end to end. Different tissues have different specific gap junction proteins (connexins). Man has 14 distinct connexins each encoded by a separate gene (20 homologous proteins in man PNAS 103 pp. 5213 – 5218 ’06). Most cell types express more than one. Connexins are capable of assembling into a heteromeric connexon Adjacent cells expressing different connexins can form intercellular channels in which the two aligned dihalf-channels are different. Each gap junction can contain a cluster of a few to MANY THOUSANDS of CONNEXONs.

Neuroscientists should be interested in them as they form a functional ‘synapse’ between cells, e.g. a way of transferring information between them. For the afficienado there will be much more at the end. To flog a nearly dead horse, this is yet another way a wiring diagram of the brain won’t help you understand it — gap junctions don’t show up when you’re looking at classic synapses. For details see https://luysii.wordpress.com/2011/04/10/would-a-wiring-diagram-of-the-brain-help-you-understand-it/

A recent paper in Nature implied that cancer cells can form gap junctions with astrocytes (a glial cell of the brain). Usually we think of gap junctions being of the same cell type, but not here apparently.

Then they describe a mechanism for the cancer cell tweak the astrocyte so it produces something enabling the cancer cell to survive. Here’s whqt they claim

[ Nature vol. 533 pp. 493 – 498 ’16 ] Human and mouse breast and lung cancer cells express protocadherin7 (PCDH7) whicboth promotes (how?) the assembly of carcinoma – astrocyte gap junctions made of connexin43. PCDH7 normally is only expressed in brain. It joints the stialyl transferase ST6GALNAC5 and neuroserpin as brain restricted proteins which metastastic cells from breast and lung cancer use to colonize the brain.

Metastastic cells then uswe the channels to transfer cGAMP to astrocytes activating the STING pathway, which results in InterferonAlpha (IFNalpha) and Tumor Necrosis Factor (TNF), paracrine signals. These activate STAT1 and NFkappaB in the metastatic cells, supporting tumor growth and chemoresistance.

Meclofenamate and tonabersat are ‘modulators’ of gap junctions, breaking the loop between metastatic cancer cell and the astrocyte. Adding them to the tissue culture studied in the paper, inhibited tumor growth. So here might be a way treat metastatic cancer — particularly since meclofenamate is an FDA approved generic drug available without a prescription.

I think the mechanism described above is incomplete — why should a tumor cell transfer something to another cell to have it secrete something which makes the original cell use something it already had.

Now for a few of the things gap junctions are doing in the brain.
****

[ Neuron vol. 90 pp. 810 – 823 ’16 ] ManhyGABAeric interneurons (are there other kinds?) IN VITRO are coupled by gap junctions. This work used dual patch clamp recordings of interneurons IN VIVO. They studied coupled cerebellar Golgi cells, and showed that, in the presence of spontaneous background synaptic activity, electrically coupled cerebellar Golgi cells showed robust milliSecond precision correlated activity. This was further enhanced by sensory stimulation.

The electrical coupling equlized membrane potential fluctuations, so that coupled neurons approach action potential threshold together. They say that something called spike triggered spikelets transmitted through gap junctions conditionally triggered postJunctional spikes, if both neurons were close to threshold.

Spikelets are brief low amplitude potentials which look like action potentials but which are much smaller. A spike cannot be generated without a much larger potential change than provided by a spikelet, because the spikelet voltage is too small to activate the ion channels of electrically excitable membranes.

So gap junctions controls the temporal precision and degree of both spontaneous and sensory evoked correlated activity betwen interneurons, by the cooperative effects of shared synaptic depolarization and spikelet transmission.

[ Neuron vol. 90 pp. 912 – 913, 1043 – 1056 ’16 ] It has been found that the strength of electrical coupling between neurons in a network is highly variable (even in the same neuron, so it could be coupled at different strengths with each of its partners). Site specific modulation of electrical coupling quickly reconfigures networks of electrically coupled neurons in the retina. Phosphorylation of connexin36 alters its conductivity.

The number of gap junctions determines the strength of ele tical coupling between cerebellar Golgi cells. Ultrastructural analysis shows that gap junctions vary widely in size, which also influences coupling strength (according to a computer simulation). These are dendro-dendritic electrical synapses (widespread in the brain between inhibitory interneurons).

Only 18% or so of the channels present at the gap junctions account for the boserved strength of electrical transmission between cerebellar golgi cells.

Somato-somatic junctions occur in the mammalian trigeminal mesencephalic nucleus. Could the excess junctions be acting as adhesion molecules.

In one system, the turnover of gap junction channel proteins is rapid and comparable with that of glutamic acid receptors.

Gap junctions are ‘low pass filters’ (they pass slow fluctuations of membrane potential better than they pass rapid fluctuations). This is why the electrical synapses are inhibitory — each action potential from a Golgi cell consists of a rapid (but brief) depolarizing spike followed by a relatively deep and protracted afterhyperpolarization — which is 200 times longer than the spike — and transmitted much more effectively.

Inhibition by sparse excitatory input breaks up Golgi network synchronization, because the coupling to adjacent cells is different for each one, causing dispersion of the spikes.

In quietly attentive animals cerebellar Golgi cells generate rhythmic synchronous activity at 8 Hertz. The same behavior is seen in cerebellar slices. The hyperpolarizing electrical post-synaptic potentials (PSPs) are the only synchronizing force. This is the default state, but it can be disrupted by a variety of sensory stimuli (or by movements) which reduce spiking frequency and rhythmicity.

Golgi cells can inhibit thousands of granule cells, and every granule cell gets inhibitory input from 4 – 8 Golgi cells. The transient nature of network desynchronization ‘could’ allow the cerebellar input layer to act as a timing device over the 10 milliSecond to 1 second timescale.

In a gambling mood?

If a pair of posters to be presented Monday 6 June at the 2016 American Society of Clinical Oncology Annual Meeting in Chicago, Illinois, contains the results of a phase III clinical trial of rigosertib, and if the results are as good as a paper discussed below the stock Onconova Therapeutics (ONTX) will jump by a factor of 10 to 100.

Full disclosure: I own some. The posters may just describe the clinical trial rather than report the results in which case all bets are off. In that case, I’ll just hold the stock until the results are in. This isn’t the ‘pump and dump’ beloved of boiler room operators everywhere. The rationale for the drug and my take on the original paper (3 May ’16) are reproduced below.

Has the great white whale of oncology finally been harpooned?

The ras oncogene is the great white whale of oncology. Mutations in 20 – 40% of cancer turn its activity on so that nothing can turn it off, resulting in cellular proliferation. People have been trying to turn mutated ras off for years with no success.

A current paper [ Cell vol. 165 pp. 643 – 655 ’16 ] describes a new and different way to attack it. Once ras is turned on (either naturally or by mutation) many other proteins must bind to it, to produce their effects — they are called RAS effectors, among which are the uneuphoniously named RAF, RalGDS and PI3K. They bind to activated ras by the cleverly named Ras Binding Domain (RBD) which has 78 amino acids.

The paper describes rigosertib, a not that complicated molecule to the chemist, which inhibits the binding (by resembling the site on ras that the RBD binds to). It is a styryl benzyl sulfone and you can see the structure here — https://en.wikipedia.org/wiki/Rigosertib.

What’s good about it? Well it is in phase III trials for a fairly uncommon form of cancer (myelodysplastic syndrome). That means it isn’t horribly toxic or it wouldn’t have made it out of phase I.

Given the mechanism described, it is possible that Rigosertib will be useful in 20 – 40% of all cancer. Can you say blockbuster drug?

Do you have a speculative bent? Buy the company testing the drug and owning the patent — Onconova Therapeutics. It’s quite cheap — trading at $.40 (yes 40 cents !). It once traded as high as $30.00 — symbol ONTX. I don’t own any (yet), but for the price of a movie with a beer and some wings afterwards you could be the proud owner of 100 shares. If Rigosertib works, the stock will certainly increase more than a hundredfold.

Enough kidding around. This is serious business. In what follows you will find some hardcore molecular biology and cellular physiology showing just what we’re up against. Some of the following is quite old, and probably out of date (like yours truly), but it does give you the broad outlines of what is involved.

The pathway from Ras to the nucleus

The components of the pathway had been found in isolation (primarily because mutations in them were associated with malignancy). Ras was discovered as an oncogene in various sarcoma viruses. Mutations in ras found in tumors left it in a ‘turned on’ state, but just how ras (and everything else) fit into the chain of binding of a growth factor (such as platelet derived growth factor, epidermal growth factor, insulin, etc. etc.) to its receptor on the cell surface to alterations in gene expression wasn’t clear. It is certain to become more complicated, because anything as important as cellular proliferation is very likely to have a wide variety of control mechanisms superimposed on it. Although all sorts of protein kinases are involved in the pathway it is important to remember that ras is NOT a protein kinase.

l. The first step is binding of a growth factor to its receptor on the cell surface. The receptor is usually a tyrosine kinase. Binding of the factor to the receptor causes ‘activation’ of the receptor. Activation usually means increasing the enzymatic activity of the receptor in the tyrosine kinase reaction (most growth factor receptors are tyrosine kinases). The increase in activity is usually brought about by dimerization of the receptor (so it phosphorylates itself on tyrosine).

2. Most activated growth factor receptors phosphorylate themselves (as well as other proteins) on tyrosine. A variety of other proteins have domains known as SH2 (for src homology 2) which bind to phosphorylated tyrosine.

3. A protein called grb2 binds via its SH2 domain to a phosphorylated tyrosine on the receptor. Grb2 binds to the polyproline domain of another protein called sos1 via its SH3 domain. At this point, the unintiated must find the proceedings pretty hokey, but the pathway is so general (and fundamental) that proteins from yeast may be substituted into the human pathway and still have it work.

4. At last we get to ras. This protein is ‘active’ when it binds GTP, and inactive when it binds GDP. Ras is a GTPase (it can hydrolyze GTP to GDP). Most mutations which make ras an oncogene decrease the GTPase activity of RAS leaving it in a permanently ‘turned on’ state. It is important for the neurologist to know that the defective gene in type I neurofibromatosis activates the GTPase activity of ras, turning ras off. Deficiencies (in ras inactivation) lead to a variety of unusual tumors familiar to neurologists.

Once RAS has hydrolyzed GTP to GDP, the GDP remains bound to RAS inactivating it. This is the function of sos1. It catalyzes the exchange of GDP for GTP on ras, thus activating ras.

5. What does activated ras do? It activates Raf-1 silly. Raf-1 is another oncogene. How does activated ras activate Raf-1 ? Ras appears to activate raf by causing raf to bind to the cell membrane (this doesn’t happen in vitro as there is no membrane). Once ras has done its job of localizing raf to the plasma membrane, it is no longer required. How membrane localization activates raf is less than crystal clear. [ Proc. Natl. Acad. Sci. vol. 93 pp. 6924 – 6928 ’96 ] There is increasing evidence that Ras may mediate its actions by stimulating multiple downstream targets of which Raf-1 is only one.

6. Raf-1 is a protein kinase. Protein kinases work by adding phosphate groups to serine, threonine or tyrosine. In general protein kinases fall into two classes those phosphorylating on serine or threonine and those phosphorylating on tyrosine. Biochemistry has a well documented series of examples of enzymes being activated (or inhibited) by phosphorylation. The best worked out is the pathway from the binding of epinephrine to its cell surface receptor to glycogen breakdown. There is a whole sequence of one enzyme phosphorylating another which then phosphorylates a third. Something similar goes on between Raf-1 and a collection of protein kinases called MAPKs (mitogen activated protein kinases). These were discovered as kinases activated when mitogens bound to their extracellular receptors.There may be a kinase lurking about which activates Raf (it isn’t Ras which has no kinase activity). Removal of phosphate from Raf (by phosphatases) inactivates it.

7. Raf-1 activates members of the MAPK family by phosphorylating them. There may be several kinases in a row phosphorylating each other. [ Science vol. 262 pp. 1065 – 1067 ’93 ] There are at least three kinase reactions at present at this point. It isn’t known if some can be sidestepped. Raf-1 activates mitogen activated protein kinase kinase (MAPK-K) by phosphorylation (it is called MEK in the ras pathway). MAPK-K activates mitogen activation protein kinase (MAPK) by phosphorylation. Thus Raf-1 is actually mitogen activated protein kinase kinase kinase (sort of like the character in Catch-22 named Junior Junior Junior). (1/06 — I think that Raf-1 is now called BRAF)

8. The final step in the pathway is activation of transcription factors (which turn genes off or on) by MAP kinases by (what else) phosphorylation. Thus the pathway from cell surface is complete.

Internal Energy, Enthalpy, Helmholtz free energy and Gibbs free energy are all Legebdre transformations of each other

Sometimes it pays to be persistent in thinking about things you don’t understand (if you have the time as I do). The chemical potential is of enormous interest to chemists, and yet is defined thermodynamically in 5 distinct ways. This made me wonder if the definitions were actually describing essentially the same thing (not to worry they are).

First, a few thousand definitions

Chemical potential of species i — mu(i)
Internal energy — U
Entropy — S
Enthalpy — H
Helmholtz free energy — F or A (but, maddeningly, never H)
Gibbs free energy — G
Ni — number of elements of chemical species i
Pressure — p
Volume — V
Temperature — T

Just 5 more
mu(i) == ∂H/∂Ni constant S, p
mu(i) == ∂S/∂Ni constant U, V
mu(i) == ∂U/∂Ni constant S, V
mu(i) == ∂F/∂Ni constant T, V
mu(i) == ∂G/∂Ni constant T, p

Clearly, at a given constellation of S, U, F, G the mu(i)’s won’t all be the same number, but they’re essentially the same thing. Here’s why.

Start with a simple mathematical problem. Assume you have a simple function (f) of two variables (x,y), and that f is continuous in x and y and that its partial derivatives u = ∂f/∂x and w = ∂f/∂y are continuous as well so you have

df = u dx + w dy

u and dx are conjugate variables, as are w and dy

Suppose you want to change df = u dx + w dy to

another function g such that

dg = u dx – y dw

which is basically flipping a pair of conjugate variables around

Patience, the reason for wanting to do this will become apparent in a moment.

The answer is to use what is called the Legendre transform of f which is simply

g = f – y w

dg = df – y dw – w dy

plug in df

dg = u dx + w dw – y dw – w dy == df – y dw – w dy Done.

Where does the thermodynamics come in?

Well, you have to start somewhere, so why not with the fundamental thermodynamic equation for internal energy U

dU = ∂U/∂S dS + ∂U/∂V dV + ∑ ∂U/∂Ni dNi

We already know that ∂U/Ni = mu(i)

Because of the partial derivative notation (∂) it is assumed that all the other variables say in the expression for dU e.g. V and Ni are held constant in ∂U/∂S. This will reduce the clutter in notation which is already cluttered enough.

We already know that ∂U/∂Ni is mu(i). One definition of temperature T, is as ∂U/∂S, and another for p is -∂U/∂V (which makes sense if you think about it — decreasing volume relative to U should increase pressure).

Suddenly dU looks like what we were talking about with the Legendre transformation.

dU = T dS – p dV + ∑ mu(i) dNi

Apply the Legendre transformation to U to switch conjugate variables p and V

H = U + pV ; looks suspiciously like enthalpy (H) because it is

dH = dU + p dV + V dp + ∑ mu(i) dNi

= T dS – p dV + ∑ mu(i) dNi + p dV + V dp

= T dS + V dp + ∑ mu(i) dNi

Notice how mu(i) here comes out to ∂H/dNi at constant S and P

Start with the fundamental thermodynamic equation for internal energy

dU = T dS – p dV + ∑ mu(i) dNi

Now apply the Legendre transformation to T and S and you get
F = U – TS ; looks like the Helmholtz free energy (sometimes written A, but never as H) because it is.

You get

dF = – S dT – p dV + ∑ mu(i) dNi

Who cares? Chemists do because, although it is difficult to hold U constant or S constant (and it is impossible to measure them directly) it is very easy to keep temperature and volume constant in a reaction, meaning that changes in Helmholtz free energy under those conditions is just
∑ mu(i) dNi. So here mu(i) = ∂F/∂Ni at constant T and p

If you start with enthalpy

dH = T dS + V dp + ∑ mu(i) dNi

and do the Legendre transform you get the Gibbs free energy G = H – TS

I won’t bore you with it but this gives you the chemical potential mu(i) at constant T and p, conditions chemists easily arrange all the time.

To summarize

Enthalpy (H) is one Legendre transform of internal energy (U)
Helmholtz free energy (F) is another Legendre transform of U
Gibbs free energy (G) is the Legendre transform of Enthalpy (H)

It should be clear that Legendre transforms are all reversible

For example if H = U + PV then U = H – PV

If you think a bit about the 5 definitions of chemical potential, you’ll see that it can depend on 5 things (U, S, p, V and T). Ultimately all thermodynamic variables (U, S, H, G, F, p, V, T, mu(i) ) often have relations to each other.

Examples include H = U + pV, F = U – TS, G = H -TS

Helping keep things clear are equations of state from the things you can easily measure (p,V, T). The most famous is the ideal gas law p V = nRT.

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