When the active form of a protein is intrinsically disordered

Back in the day, biochemists talked about the shape of a protein, influenced by the spectacular pictures produced by Xray crystallography. Now, of course, we know that a protein has multiple conformations in the cell. I still find it miraculous that the proteins making us up have only relatively few. For details see — https://luysii.wordpress.com/2010/08/04/why-should-a-protein-have-just-one-shape-or-any-shape-for-that-matter/.

Presently, we also know that many proteins contain segments which are intrinsically disordered (e.g. no single shape).The pendulum has swung the other way — “estimations that contiguous regions longer than 50 amino acids ‘may be present” in ‘up to’ 50% of proteins coded in eukaryotic genomes [ Proc. Natl. Acad. Sci. vol. 102 pp. 17002 – 17007 ’05 ]

[ Science vol. 325 pp. 1635 – 1636 ’09 ] Compared to ordered regions, disordered regions of proteins have evolved rapidly, contain many short linear motifs that mediate protein/protein interactions, and have numerous phosphorylation sites compared to ordered regions. Disordered regions are enriched in serine and threonine residues, while ordered sequences are enriched in tyrosines — this highlights functional differences in the types of phosphorylation. Interestingly tyrosines have been lost during evolution.

What are unstructured protein segments good for? One theory is that the disordered segment can adopt different conformations to bind to different partners — this is the moonlighting effect. Then there is the fly casting mechanism — by being disordered (hence extended rather than compact) such proteins can flail about and find partners more easily.

Given what we know about enzyme function (and by inference protein function), it is logical to assume that the structured form of a protein which can be unstructured is the functional form.

Not so according to this recent example [ Nature vol. 519 pp. 106 – 109 ’15 ]. 4EBP2 is a protein involved in the control of protein synthesis. It binds to another protein also involved in synthesis (eIF4E) to suppress a form of translation of mRNA into protein (cap dependent translation if you must know). 4EBP2 is intrinsically disordered. When it binds to its target it undergoes a disorder to ordered transition. However eIF4E binding only occurs from the intrinsically disordered form.

Control of 4EBP2 activity is due, in part, to phosphorylation on multiple sites. This induces folding of amino acids #18 – #62 into a 4 stranded beta domain which sequesters the canonical YXXXLphi motif with which 4EBP2 binds eIF4E (Y stands for tyrosine, X for any amino acid, L for leucine and phi for any bulky hydrophobic amino acid). So here we have an inactive (e.g. nonbonding) form of a protein being the structured rather than the unstructured form. The unstructured form of 4EBP2 is therefore the physiologically active form of the protein.

Off to China

No posts until March. Off to meet our new Granddaughter. Will be Email and Internet free until then.

To fill up the empty hours until I’m back, drug chemists should study the physical chemistry of protein/protein interaction, since that’s where most cellular work is done (and where new drugs should be useful). The interctions are multiple, transient and nonequivalent (the WordPress processor substituted this for nonCovalent).

An interesting paper made all 160,000 possible variants of 4 amino acids at the interface between two bacterial proteins [ Science vol. 347 pp. 673 – 677 ’15 ]. For bacterial histidine kinases mutating just 3 or 4 interfacial amino acids to match those in another kinase is enough to reprogram their specificity. The key amino acids are Ala284, Val285, Ser288, Thr289. The results were rather surprising.


Scary stuff

While you were in your mother’s womb, endogenous viruses were moving around the genome in your developing developing brain according to [ Neuron vol. 85 pp. 49 – 59 ’15 ].

The evidence is pretty good. For a while half our genome was called ‘junk’ by those who thought they had molecular biology pretty well figured out. For instance 17% of our 3.2 gigaBase DNA genome is made of LINE1 elements. These are ‘up to’ 6 kiloBases long. Most are defective in the sense that they stay where they are in the genome. However some are able to be transcribed into RNA, the RNA translated into proteins, among which is a reverse transcriptase (just like the AIDS virus) and an integrase. The reverse transcriptase makes a DNA copy of the RNA, and the integrates puts it back into the genome in a different place.

Most LINE1 DNA transcribed into RNA has a ‘tail’ of polyAdenine (polyA) tacked onto the 3′ end. The numbers of A’s tacked on isn’t coded in the genome, so it’s variable. This allows the active LINE1’s (under 1/1,000 of the total) to be recognized when they move to a new place in the genome.

It’s unbelievable how far we’ve come since the Human Genome Project which took over a decade and over a billion dollars to sequence a single human genome (still being completed by the way filling in gaps etc. etc [ Nature vol. 517 pp. 608 – 611 ’15 ] using a haploid human tumor called a hydatidiform mole ). The Neuron paper sequenced the DNA of 16 single neurons. They found LINE1 movement in 4

Once a LINE1 element has moved (something very improbable) it stays put, but all cells derived from it have the LINE1 element in the new position.

They found multiple lineages and sublineages of cells marked by different LINE1 retrotransposition events and subsequent mutation of polyA microsatellites within L1. One clone contained thousands of cells limited to the left middle frontal gyrus, while a second clone contained millions of cells distributed over the whole left hemisphere (did they do whole genome on millions of cells).

There is one fly in the ointment. All 16 neurons were from the same ‘neurologically normal’ individual.

Mosaicism is a term used to mean that different cells in a given individual have different genomes. This is certainly true in everyone’s immune system, but we’re talking brain here.

Is there other evidence for mosaicism in the brain? Yes. Here it is

[ Science vol. 345 pp. 1438 – 1439 ’14 ] 8/158 kids with brain malformations with no genetic cause (as found by previous techniques) had disease causing mutations in only a fraction of their cells (hopefully not brain cells produced by biopsy). Some mosaicism is obvious — the cafe au lait spots of McCune Albright syndrome for example. DNA sequencing takes the average of multiple reads (of the DNA from multiple cells?). Mutations foudn in only a few reads are interpreted as part of the machine’s inherent error rate. The trick was to use sequencing of candidate gene regions to a depth of 300 (rather than the usual 50 – 60).

It is possible that some genetically ‘normal’ parents who have abnormal kids are mosaics for the genetic abnormality.

[ Science vol. 342 pp. 564 – 565, 632 -637 ’13 ] Our genomes aren’t perfect. Each human genome contains 120 protein gene inactivating variants, with 20/120 being inactivated in both copies.

The blood of ‘many’ individuals becomes increasingly clonal with age, and the expanded clones often contain large deletions and duplications, a risk factor for cancer.

Some cases of hemimegalencephaly are due to somatic mutations in AKT3.

30% of skin fibroblasts ‘may’ have somatic copy number variations in their genomes.

The genomes of 110 individual neurons from the frontal cortex of 3 people were sequenced. 45/110 of the neurons had copy number variations (CNVs) — ranging in size from 3 megaBases to a whole chromosome. 15% of the neurons accounted for 73% of of the CNVs. However, 59% of neurons showed no CNVs, while 25% showed only 1 or 2.

The chemical ingenuity of the lake Ontario midge

Well we’re freezing our butts off here in sunny New England, so it’s time to discourse upon the chemical ingenuity of antifreeze proteins. They’ve long been known, with most found in fish living in arctic waters. A very unusual structure is found in a 79 amino acid protein from an insect living near Lake Ontario. It contains 79 amino acids with a set of 10 amino acid tandem repeats making up most of the protein. Here is the the repeat.

X X Cys X Gly X Tyr Cys X Gly ; X = any amino acid.

Can you as a computational chemistry expert figure out what it forms?

The 10 amino acids form a complete circle with the peptide backbone looking nothing like an alpha helix, a beta sheet or anything else I’ve seen. It just sort of wanders around for 360 degrees. In cross section the ‘circle’ resembles the Greek letter theta with a disulfide bond between the two cysteines forming a crossbar inside the circle. This puts all 7 tyrosines from the 7 repeats in a row on one side of the circle, where they form the presumed ice binding site. The solenoid is reinforced by intrachain hydrogen bonds, and side chain salt bridges. You can read about it and see some pictures in Proc. Natl. Acad. Sci. vol. 112 pp. 737 – 742 ’15 ].

The chemical ingenuity of some of these proteins is remarkable. None of them (except one) appear to have been figured out before their structures were determined.

[ Proc. Natl. Acad. Sci. vol. 108 pp. 7281 – 7282 ’11 ] Even now, the structural differences between the surface of ice nuclei and liquid water are poorly characterized (we don’t even know how many hydrogen bonds are involved), yet antifreeze proteins somehow recognize it. Some 12 different structural motifs have been found in antifreeze proteins. 3 are given — one is a small globular protein (sea pout) another is an alpha helix (winter flounder), and the third is a stack of left handed PolyProtein-II helices (snow flea). The present work gives a fourth example — a right handed parallel beta helix from (Marinomonas primoyensis). It is a 34 kiloDalton domain — it is a calcium bound parallel beta helix, with an extensive array of icelike surface waters that are anchored via hydrogen bonds directly to the protein backbone and adjacent side chains. The bound waters make an excellent 3 dimensional match to the primary prism and basal planes of ice.

Probably the most counterintuitive antifreeze protein is the following. It stands a lot of what we thought we knew about protein structure on its head.

[ Science vol. 343 pp. 743 – 744, 795 – 798 ’14 ] Almost all globular proteins reported to date have a dry protein core (e.g. water free). An antifreeze protein called Maxi from the winter flounder (Pseudopleuronectes americanus) has been found with a water filled core. It is a 3 kiloDalton alanine rich 4 helix bundle 145 Angstroms long. The periodicity of the alpha helices is 11 amino acids. A single turn of an alpha helix is 5.4 Angstroms high and 11 Angstroms wide. So 11 amino acids fairly neatly comes out to 16 Angstroms in length (because each helical turn is 3.7 residues (vs. the normal 3.6 in the classic alpha helix). The ice binding residues are Threonine at position i, Alanine at position i+4 and Alanine at position i + 8 (putting them along one face of the helix). The protein is a dimer of monomers each containing two helices. The core is comprised of 400 (yes 400 !) highly organized water molecules. The water is interleaved as a roughly two molecule thick layer between both intra and intermonomer helix interfaces, extending to the ice binding surfaces. Maxi must bind ice nuclei and inhibit their growth. The water molecules inside the bundle form pentagons ! ! ! Amazingly, this was predicted 50 years ago by Scheraga . The 5 membered water rings form cages around individual amino acid side chains, illustrating their semi-clathrate structure — rather than ice. Most of the carbonyls are involved in hydrogen bonding interactions with water — helping to keep the protein soluble. The protein denatures at low temperatures (16 C)

Ordered water can be found in most high resolution Xray crystallograpy protein structures, but they are usually between the proteins. Maxi retains the very structure of water.

Removal of water has been proposed as a potential rate limiting step in protein folding. Maxi folds to the point where water not in direct contact with the protein chain is removed from its core. It then arrests further folding to retain a beautifully ordered core of water interleaved between the protein helices.

Amazing! No one would ever have predicted something like Maxi (except Sheraga).

The butterfly effect in cancer

Fans of Chaos know all about the butterfly, where a tiny change in air current produced by a butterfly’s wings in Brazil leads to a typhoon in Java. Could such a thing happen in cell biology? [ Proc. Natl. Acad. Sci. vol. 112 pp. 1131 – 1136 ’15 ] comes close.

The Cancer Genome Project has spent a ton of money looking at all the mutations of all our protein coding genes which occur in various types of cancers. It was criticized as we already knew that cancer is effectively a hypermutable state, and that it would just prove the obvious. Well it did, but it also showed us just what a formidable problem cancer actually is.

For instance [ Nature vol. 489 pp. 519 – 525 ’12 ] is report from the Cancer Genome Atlas of 178 cases of squamous cell cancer of the lung. There are a mean of 360 exonic mutations, 165 genomic rearrangements, and 323 copy number alterations per tumor. The technical details in the rest of the paragraph can be safely ignored but the point is that there no consistent pattern of mutation was found (except for p53 which is mutated in over 50% of all types of cancer, which we knew long before the Cancer Genome Atlas). Recurrent mutations were found in 11 genes. p53 was mutated in nearly all. Previously unreported loss of function mutations were seen in the class I major histocompatibility (HLA-A). Several pathways were altered relatively consistently (NFE2L2, KEAP1 in 34%, squamous differentiation genes in 44%, PI3K genes in 47% and CDKN2A and RB1 in 72%). EGFR and kRAS mutations are rare in squamous cell cancer of the lung (but quite common in adenocarcinoma). Alterations in FGFR are quite common in squamous cell carcinomas.

This sort of thing (which has been found in all the many types of tumors studied by the Cancer Genome Atlas) lead to a degree of hopelessness in looking for the holy grail of a single ‘driver mutation’ which leads to cancer with its attendant genomic instability.

All is not lost however.

MCF-10A is an immortalized epithelial cell line derived from human breast tissue. It is capable of continuous growth, but is far from normal: (1) an abnormal complement of chromosomes ) (2) threefold amplification of the MYC oncogene, and (3) deletion of a known tumor suppressor . It does lack some mutations found in breast cancer. For instance, the Epidermal Growth Factor Receptor 2 (ERRBB2) is not amplified. The cell line doesen’t express the estrogen and progesterone receptors — making it similar to triple negative breast cancer.

A single amino acid mutation (Arginine for Histidine at amino acid #1047 ) in the catalytic subunit of a very important protein kinase (p110alpha of the PIK3CA gene) was put into the MCF-10A cell line (which they call MCF-1A-H1047R). The mutation was chosen because it is one of the most frequently encountered cancer specific mutations known. Exome sequencing of the entire genome showed that this was the only change — but the control sequences outside the exons weren’t studied, a classic case of the protein centric style of molecular biology.

In the (admittedly not completely normal) cell line, the mutation produced a cellular reorganization that far exceeds the known signaling activities of PI3K. The proetins expressed were stimilar to the protein and RNA signatures of basal breast cancer. The changes far exceeded the known effects of PIK3CA signaling. The phosphoproteins of MCF-1A-H1047R are extremely different. Inhibitors of the kinase induce only a partial reversion to the normal phenotype.

They plan to study the epigenome. This is signifcant as breast cancers are said in the paper to have tons of mutations changing amino acids in proteins (4,000 per tumor). In my opinion they should do whole genome sequencing of MCF-A1-H1047R as well.

The mutant becomes fully transformed whan a second mutation (of KRAS, an oncogene) is put in. This allows them to form tumors in nude mice. Recall that nude mice (another rodent beloved of experimental biologists — see the previous post on the Naked Mole Rat) has a very limited immune system, allowing grafts of human cells to take root and proliferate.

How close the initial cell line is to normal is another matter. Work on a similar cell line the (3T3 fibroblast) has been criticized because that cell is so close to neoplastic. At least the mutant MCF-1A-H1047R cells aren’t truly neoplastic as they won’t produce tumors in nude mice. However, mutating just one more gene (KRAS) turns MCF-1A-H1047R malignant when transplanted.

The paper is also useful for showing how little we really understand about cause and effect in the cell. PI3K has been intensively studied for years because it is one of the major players telling cells to grow in size rather than divide. And yet “the mutation produced a cellular reorganization that far exceeds the known signaling activities of PI3K”

Time for drug chemists to hit the cell biology books

The (undeservedly) obscure Naked Mole Rat should be of interest to drug chemists for two reasons (1) it lives 8 times as long its fellow rodent the lab mouse (2) it never gets cancer (despite being under observation for the past 40 years). So untangling the mechanisms behind this should tell us about aging and cancer, particularly since cancer accounts for over 50% of the mortality in lab rodents. They age healthy. Until the last few years of their long lives, they show minimal morphological and physical changes of aging.

This post will concern a possible way Naked Mole Rats escape cancer. I’ve attempted to provide a molecular biologiocal background for chemists about DNA, RNA, gene transcription etc. See 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 is very little in these posts about cell physiology and biology. I suggest having a look at “Molecular Biology of The Cell” and “Cancer” by Robert Weinberg. Get the latest editions, as things are moving rapidly.

The following paper tried to find out why Naked Mole Rats don’t get cancer [ Proc. Natl. Acad. Sci. vol. 112 pp. 1053 – 1058 ’15 ]. In tissue culture, naked mole rat fibroblasts show hypersensitivity to contact inhibition (aka early contact inhibition aka ECI). E.g. they stop dividing or die when they get too close to each other. The signal triggering ECI comes from hyaluronan (which has a very high molecular weight) outside the cell. Removal of high MW hyaluronan abrogates ECI and makes naked mole rat cells susceptible to malignant transformation.

ECI is associated with an increase in expression of p16^INK4a, a tumor suppressor (here is where the cell biology comes in). Cells losing expression no longer show ECI. Deletion and/or silencing of INK4a/b is found in human cancers as well. The genomic locus containing p16^INK4a is small (under 50 kiloBases), but it it codes for 3 different tumor suppressors (p16^INK4a, p15^INK4b and p14^ARF). The 3 proteins coordinate a signaling network depending on the activities of the retinoblastoma protein (RB) and p53 (more cell molecular biology).

In the naked mole rat, the INK4a/b locus codes for an additional product which consists of p15^INK4b exon #1 joined to p16^INK4a exons #2 and #3, due to alternative splicing. They call this pALT^INK4a/b. It is present in cultured cells from naked mole rat tissues, but is absent in human and mouse cells. pALT^INK4a/b expression is induced during early contact inhibition and by a variety of stresses such as ultraviolet light, gamma radiation, loss of substrate attachment and expression of oncogenes. When over expressed in human cells, pALT^INK4a/b has more ability to induce cell cycle arrest than either p16^INK4a or p15^INK4b. So pALT^INK4a/b might explain the increased resistance to tumors.

There’s also a lot of work concerning why they live so long, but that’s for another post.

Big Brother is watching you and you’re telling him everything he needs to know (if you’re on Facebook)

Big Brother is watching you and you’re telling him everything he needs to know (if you’re on Facebook). Here’s why. A computer analysis of your ‘likes’ predicts the results of your completing a 100 item personality questionnaire, better than those whom you’ve friended on Facebook. [ Proc.Natl. Acad. Sci. vol. 112 pp. 1036 – 1040 ’15 ] Has the gory details.

We do know that people lie when completing such things and the MMPI (Minnesota Multiphase Personality Inventory) has a scale for lying. Apparently everyone steals from mommy’s purse at some point, and your lie score on the MMPI goes up if you say you never did.

The study used a mere 86,220 volunteers who completed the 100-item International Personality Item Pool (IPIP) Five-Factor Model of personality questionnaire, measuring traits of openness, conscientiousness, extroversion, agreeableness, and neuroticism. The sample used in this study was obtained from the myPersonality project. myPersonality was a popular Facebook application that offered to its users psychometric tests and feedback on their scores. The data was anonymized and is in the public domain. How normal such an individual can be I leave up to you.

Human personality judgments were obtained from the participants’ Facebook friends, who were asked to describe a given participant using 10 of the 100 items of the IPIP personality measure. E.g. the friends were filling out the 10 items as they thought the subject would (or as they saw the subject).

So it’s the same questionnaire. The paper pitted a computer algorithm based on your Likes to predict your IPIP responses against those of your so-called Facebook friends who presumably know much more about you than just your Facebook Likes. The algorithm won. It didn’t win by much. Computer-based judgments (r = 0.56) correlate more strongly with participants’ self-ratings than average human judgements did (r = 0.49). Surprisingly, neither did terribly well, but then we all know that our judgement of ourselves is usually rather different than others. It’s why city people often tell you what they’re ‘really like’, while Montanans don’t. They know that there are so few people around that they’ll see you again. Your long term behavior will tell them everything they need to know.

Update 31 Jan ’15 — I told the people I play piano trios with about the paper. The cellist (a retired Actuary) had an excellent explanation of why the algorithm was more accurate than the friends individually. See if you can think of the reason.

She notes that the 3 of us interact with each other individually, e.g. we act differently for each of our friends, exposing just the parts of our personalities we choose. They aren’t the same for everyone. Obvious, now that she’s thought of it (did you?)

As usual the Poets have said it better

And would some Power the small gift give us
To see ourselves as others see us!
It would from many a blunder free us,
And foolish notion:

Robert Burns (1786)

We know how to make a mouse dream when we want

Everybody knows abut Rapid Eye Movement sleep (REM sleep) now. It wasn’t always that way. I found out about it in med school when my wife pointed me to a fascinating article in the New Yorker, concerning the work of Dement and Kleitman. Briefly, if you wake someone up during REM, they’ll tell you they’re dreaming. As a budding Neurologist, I actually got an afternoon off from my internship to hear Dement talk. I’d been up most of the previous night, and after a nice lunch they turned the lights off as Dement began showing slides and I promptly feel asleep. After it was over and the lights came back on, the guy next to me asked what I’d been dreaming.

There’s been a huge amount of progress on sleep in the past year.

1. At long last, we may actually have a clue as to why we spend a third of our lives asleep. The short answer is that it is to flush out the brain. For details please see https://luysii.wordpress.com/2013/10/21/is-sleep-deprivation-like-alzheimers-and-why-we-need-sleep-in-the-first-place/

2. A recent paper found an area in the brain, which, when stimulated, takes a sleeping mouse into REM sleep. The technique is yet another use of optogenetics (which is almost sure to win Karl Diesseroth a Nobel). For details please see https://luysii.wordpress.com/2013/05/19/a-certain-nobel-prize/.

Optogenetics gives you the ability (after a lot of molecular biological work) to turn specific sets of neurons on (or off). It was known that a very old area of the brain was involved in consciousness, wake and sleep. Just which areas were crucial for REM was controversial. Prior to optogenetics, lesions were made in various place and the animals studied. Neurologic diagnosis of what part of the brain did what was essentially done this way using the various natural disasters which befall the brain. A stroke here cause language problems, a tumor there, caused visual disturbance etc. etc. It worked well, but always contained an essential ambiguity. If you turn of a switch, a light bulb stops shining. But the switch doesn’t really produce the light although it is necessary.

However, stimulating a given nucleus and shifting an animal from regular sleep to REM sleep is far less ambiguous.

The details are quite technical and probably not comprehensible to most of the readership, but here they are for the neurophysiologists in the audience.

[ Proc. Natl. Acad. Sci. vol. 112 pp. 584 – 589 ’15 ] Cholinergic neurons in the mesopontine tegmentum have been implicated in REM sleep, but lesions of the area have had varying effects on REM. This work shows that selective optogenetic activation of cholinergic neurons in the pedunculopotine tegmentum (PPT) or the laterodorsal tegmentum (LDT) increases the number of REM sleep episodes without changing REM sleep duration. Activating them in either nucleus during NREM induces REM. The work was done in transgenic mice which have extra copies of the vesicular AcCh transporter with increased cholinergic tone.

Monamines (particularly norepinephrine) are alerting, and it has been shown that neurons in LDT are inhibited by seronin in rat and guinea pig.

An interesting way to study the hydrophobic effect between protein surfaces

Protein interaction domains haven’t been studied to nearly the extent they need to be, and we know far less about them than we should. All the large molecular machines of the cell (ribosome, mediator, spliceosome, mitochondrial respiratory chain) involve large numbers of proteins interacting with each other not by the covalent bonds beloved by organic chemists, but by much weaker forces (van der Waals,charge attraction, hydrophobic entropic forces etc. etc.).

Designing drugs to interfere (or promote) such interactions will be tricky, yet they should have profound effects on cellular and organismal physiology. Off target effects are almost certain to occur (particularly since we know so little about the partners of a given motif). Showing how potentially useful such a drug can be, a small molecule inhibitor of the interaction of the AIDs virus capsid protein with two cellular proteins (CPSF6, TNPO3) the capsid protein must interact with to get into the nucleus has been developed. (Unfortunately I’ve lost the reference). For more about the host of new protein interaction domains (and potential durable targets) just discovered please see https://luysii.wordpress.com/2015/01/04/microexons-great-new-drugable-targets/

Hydrophobic ‘forces’ are certain to be important in protein protein interactions. A very interesting paper figured out a way to measure them using atomic force microscopy (AFM). [ Nature vol. 517 pp. 277 – 279, 347 – 350 ’15 ]. This is particularly interesting to me because entropy has nothing to do with the force as measured. I’ve always assumed that the the hydrophobic force was entropic, similar to the force exerted by rubber when you stretch it. It’s what pushes hydrophobic side chains into the interior of proteins (e.g water doesn’t have to decrease its entropy by organizing itself to solvate hydrophobic side chains). Not so in this case.

The authors prepared self-assembled monolayers using dodecyl thiol (CH3 (CH2) 10 CH2 SH) bound to gold. Every now and then an amino group or a guanido group was placed at the other end of the thiol. This allowed them to produce a mixture of hydrophobic groups (60%) and ionic species (NH4+ or guanidinium ions) within nanoMeters of the hydrophobic regions. The amine and the guanidino groups were the same distance as the hydrocarbon ends from the gold surface. A gold atomic force microscope (AFM) with a hydrophobic tip (the same C(12) moiety), was then used to measure the adhesive force between the tip and the surface in aqueous solution.

This is important because it is a measurement not a theoretical calculation (apologies Ashutosh). This is particularly useful since water is so complex that we don’t have a good understanding (potential function) for it.

Methanol was added (which eliminated most of the hydrophobic interactions). Sensitivity to methanol was taken as a signature of the hydrophobic component of the force. The pH could be manipulated, so the R – NH2 could be charged to R -NH3+, ditto for guanidinium to the uncharged species.

So guess what the effect of amino and guanidine groups were on the hydrophobic interaction. I was rather surprised.

The strength of hydrophobic interactions between the mixed monolayers and the tip doubled when neutral amino groups found within nanoMeters of hydrophobic regions are charged to form R -NH3+ ions by lowering the pH. A similarly placed guanidinium ion eliminates the hydrophobic interactions at all pHs. So the effect of the two side chains (NH2 for lysine, guanidinium for arginine) is opposite.

They note that the ammonium ion is well hydrated, but guanidinium is hydrated only at the edges of the plane (where the electrons are) but not above it. This allows guanidinium an amphipathic behavior, which is why it can be a denaturant (did you know this? I didn’t).

I’m sure that the effect of negative ions (e.g. carboxyl groups) and every other conceivable side chain will be studied in the future.

Thus hydrophobicity is not an intrinsic property of any given nonPolar domain. It can be changed by functional groups within 10 Angstroms.. So placing a charged group near a hydrophobic domain, should allow tuning of the hydrophobic driving force. I’d be amazed if this isn’t found to be the case evolutionarily.

They also studied some wierd looking stuff resembling proteins (beta peptides { e.g. the amino and carboxyl groups on adjacent carbons rather than the same one as with alpha amino acids) with weird side chains which are known to adopt an amphipathic helical conformation. THe nonpolar side chains were trans 2 aminocyclohexanecarboxylic acid (ACHC), and the cationic side chains were beta3 homolysine. Why didn’t they use something more natural. The peptide forms an ACHC rich nonPolar square domain 10 Angstroms on a side with a polar patch on the other side of the helix.

So it’s a fascinating piece of work with large implications for the design of drugs attacking protein protein interfaces.

What a difference a change of administration makes

This is not a scientific post. Having a son who majored in journalism educated me to the various and sundry ways news is slanted. Here in Massachusetts, the administration changed from 8 years of Democratic governance to Republican. Liberals shouldn’t fret as the legislature remains 90% Democratic.

For the past 8 years the local press has been carrying water for increased spending and taxes. We have been regaled with headlines decrying “Draconian cuts” and budget gaps. Such was the case with the outgoing administration, where stories began appearing last December about budget gaps on the order of 700 million. I wrote the reporter asking what this represented in terms of the total budget and never got anything back, ditto for the response from one of the few Republican senators still standing. Throughout the decade I could never get a straight answer as to the actual amount of the budget and the year to year changes in same.

Now we have the following http://www.masslive.com/politics/index.ssf/2015/01/gov_charlie_baker_massachusetts_765_million_budget_gap.html#incart_m-rpt-1, and from the same reporter who never responded last month. Here’s what the reporter was forced to report.

“tax revenues are coming in on target, with an approximately 4.5 percent increase over last year. However, state spending is on target to increase by 7.3 percent“. It will be amusing to see if ‘Draconian cut” stories appear as they have in the past. Mr. Micawber always had a budget gap and so do we.

Along the same lines here’s a heartwarming headline, to disguise an appeal for higher taxes. http://finance.yahoo.com/news/obama-channels-inner-robin-hood-as-rich-get-richer-154533477.html.

Derek Lowe always regrets posting anything remotely political on his blog “In the Pipeline”. Hopefully I won’t. If you must respond, please be civil.


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