Enzymes and Food

I spent the afternoon teaching a class on cheesemaking for the Douglas County Master Food Preservers.  It went quite well; they are a group that knows about food, fermentation, some biology and food chemistry, and yet for most of them dairy products were terra incognita.  This made them ideal students, engaged, intelligent, and naive.

An essential part of making most cheeeses involves rennet.  One can use animal rennet, which is a crude extract of the stomach lining of a young ruminant.  One can use (as I do) a microbial rennet, which is a single enzyme extracted from the fungus Mucor miehi.  One can use an extract from the flower of the cardoon thistle, which doesn't work as well as normal rennet and is only used in a handful of unusual cheeses.  Or, these days, one can use recombinant rennet, which is an enzyme extracted from bacteria that have been given the genes that are expressed in the stomach lining of a young ruminant.  In all cases, the active ingredient in rennet is a specific protease.  This enzyme cuts proteins between two specific amino acids, and in a specific amino acid context (to make an analogy to language, it would be like a text editor that only cuts between the letters "x" and "t" but only if they occur at the end of a word--not very common).  Almost all the protein in milk is casein, which happens to have the target for rennet; and when rennet cuts casein at that spot, the casein sticks together so that cheese can be made.  No rennet, no fromage. All praise to rennet!

This set me to thinking.  Are there other examples where a specific enzyme, with a specific target, is absolutely essential for making a food?  Here's all the others that I can think of, after mulling on and off for a day.  

1.  Candy with syrupy centers.  How do they put liquid in a chocolate shell?  They don't.  They put a solid disaccharide sugar and an enzyme, invertase.  Invertase cuts the disaccharide into two monosaccharides and a molecule of water; the sugars dissolve into the water, and there you are.  The ingredients on the package will say "invert sugar."  

2.  Chicha. This is a maize-based beer like product from the Inca empire.  Beer requires some sugar to ferment, but corn, which the Inca grew, only has starch.  Fortunately, starch can be hydrolyzed to glucose by the very specific enzyme amylase.  Where would an Inca find amylase?  In spit.  There were people whose job it was to chew corn; the amylase in their saliva would act upon the starch in the corn, and they would spit the pulp into a jar.  The pulp of chewed-up corn, spit, and glucose liberated from the starch by saliva amylase would then ferment into a beer, which the Inca would drink.  Yum!  (You can do the same trick; put a little bit of raw potato in your mouth, and eventually it will start to taste sweet.)

3.  Not essential, but interesting--papain and bromelain for a tender steak.  There's a couple of enzymes, derived from papayas and bromeliads (pineapples), that like rennet, are proteases.  However, their specificity differs from that of rennet, and it turns out that they are really good at breaking some of the tougher fibers in muscle proteins.   It's not essential for preparing meat, but if you buy meat tenderizer, most likely you'll be getting one of these two plant enzymes.

I would love to hear of other examples of specific enzymes, independent of an organism, being essential for the production of a particular food.  There's zillions of examples of specific species being required for a food, but a single cell brings hundreds of enzymes to bear.  A single, purifyable enzyme?  That's much rarer.  

A simple lesson in enzyme kinetics

(Ever since a college class on physical chemistry, I retreat to the verities of thermodynamics when confronted with the incomprehensibility of human behavior.  There’s no understanding what happened in Connecticut a few days ago--just trying to arrive at a mechanism that will allow you to get through your day without hiding in a bunker to avoid every other human being.)

Look, here’s a test tube of solvent with two solutes in it. 

One is a substrate—a chemical that can undergo a reaction, but doesn’t readily do so.  The other is an enzyme—a chemical that, when it bumps into the substrate, makes it undergo the reaction. 

Enzymes are proteins, noodle-like strings of amino acids that must fold up into a specific shape to do their job.  This process can, and does, go awry at a certain rate; a defined proportion of a population of this enzyme will be misfolded.  If there are only a few molecules of the enzyme, then it’s unlikely that you’ll find a single misfolded enzyme.  If there are thousands of molecules of the enzyme, then you’ll find a couple misfolded enzymes.  If there are millions of molecules of the enzymes, then it’s a certainty that you’ll find a good number of misfolded enzymes.

Now, the misfolded enzyme is evil.  When it bumps into a molecule of substrate, it makes it undergo the wrong reaction, one that produces a lethal product.

Very simple.  Since the proportion of misfolded enzyme is constant, if you increase the amount of enzyme in the jar, you will increase the amount of evil enzyme.  There’s no way around that fact. 

Let’s say that you keep the amount of enzyme in the jar constant, but you increase the amount of substrate.  You will increase the likelihood that a molecule of evil enzyme will bump into a molecule of substrate, and make something lethal.  This is physical chemistry, this is the way the world works, and arguing against it is like arguing against gravity.

(In the picture, I’m just looking at the "evil" reaction; the “good” reaction still happens, but I’m more interested in the “evil” reaction catalyzed by the evil enzyme.)

If you’ve had college biology, you may have encountered enzyme kinetics.  That’s what we’re seeing here.  You can make a graph showing the relationship between substrate concentration and the rate at which the reaction happens.  Eventually, you saturate the system, and the reaction goes as fast as possible. 

There’s two ways you can avoid producing the lethal product.  Make the concentration of enzyme really, really low—it will be less likely that you’ll have any of the evil enzyme.  Or, you can make the concentration of substrate really, really low—it will be less likely that a molecule of substrate will encounter a molecule of evil enzyme.

 

...........................

In any population of humans, there’s going to be a small percentage that just ain’t right in the head.  If there’s only a thousand people in your population, and there’s a good social support network, then there may not be any such troubled individuals.  But, in a country of 300 million, there’s going to be people who do evil.  Unless we reduce our country’s population to a thousand people, there will be psychopaths, just like in a collection of millions of molecules of enzyme, there will be evil misfolded enzyme.

For a normal human being—for most of my neighbors here in a pretty “red” part of the country—an encounter with the substrate in this argument, a gun, is part of a recreational experience.  People hunt, or practice marksmanship, or just go plinking tin cans.  Many of my neighbors have the kind of semi-automatic weapons used in Clackamas and Connecticut and Aurora and Milwaukee, and nothing bad happens.   

But if you put the substrate of a semi-automatic weapon into the hands of a psychopath, you get that lethal reaction that we saw in Clackamas a week ago and in Connecticut a couple of days ago. 

If you increase the concentration of substrate—of guns, especially those guns that are useless for hunting—you will increase the rate of the reaction.  This is reality, this is how thermodynamics says the universe works, despite the idiot fantasies of Dennis Richardson, the Oregon State Representative from Central Point, just down the interstate from here:

“If I had been a teacher or the principal at the Sandy Hook Elementary School and if the school district did not preclude me from having access to a firearm, either by concealed carry or locked in my desk, most of the murdered children would still be alive, and the gunman would still be dead, and not by suicide…we need to ensure that our children are safe, and we can’t do that by disarming those who are on the scene.”  

I don’t know if Representative Richardson ever studied any physical sciences in school; if he were taking introductory bio from he, he’d have just failed.  This is really simple stuff. 

As I’ve said, many or most of my neighbors have guns, mostly for hunting.  More than a few have handguns (We once got our car towed by a guy who had his on the dashboard, and who reminded me a little too much of the character John Goodman played in “Barton Fink”*).  Some have semiautomatics.  They tend to feel more strongly about their weapons than I do about my most prized possession.  They will all aver that they are of sound mind and practice all the rules of gun safety.  Most will point to a highly ambiguous clause in the Constitution.  A few of the fringier ones will maintain that their ability to outgun government representatives is the bulwark that prevents tyranny, which I’d find laughable if it didn’t reflect a cocktail of psychosis and lethal force. 

Reading and talking with gun enthusiasts, I’m struck by the degree to which these weapons are signifiers of something transcendent and essential to their self-regard.  They try for words to explain it to me, and give up—it ends up being like explaining religion or love.  Having not had their—I’m at a loss for what to call it…epiphany? Love affair? revalation?...I’ll admit that I utterly fail to understand their point of view.  I’m fine with hunting rifles.  But no one needs an automatic or semiautomatic weapon, any more than they need a howitzer or Sherman tank. 

Reading Representative Richardson’s remarks, two things are clear: he wants lots of guns, and he ardently wants dead children (just not as many).  Other gun enthusiasts have basically said that there’s no eliminating psychopaths, but the right to hyper-lethal weaponry is sacrosanct—so, we just have to accept a certain baseline of slaughter.  In their view, we’d be best off if we were in the saturated region of the enzyme kinetics graph. 

If we, as a society, want evil such as happened this week to stop, the only way we can do it is to reduce the concentration of substrate—of weapons whose designed purpose is to kill lots of humans—to zero.  If we, as a society, don’t have the will to do this, then we, as a society, are affirming that we want this to happen again, and again, and again. 

This is not politics; this is really basic, simple physical science.  How we get there is politics. 

*I’ve heard it argued that a well-armed society is a polite society.  This is both true and utter horse$#!+.  I was very polite and most agreeable with the tow-truck driver.  I did not feel especially freedom-y, and I don’t think I would have felt any more freedom-y if I were also armed. 

FRETting about folding

Nature is the consummate magician. There are things that human intelligence and its servant computers fail to do despite the mightiest struggles; nature does them with an insouciant shrug. For a biologist, the most maddening example of this is the folding of proteins.

A protein is a linear molecule, hundreds or thousands of atoms long. Every third atom in this chain has a chemical decoration; there are twenty different types of decorations, some acidic, some basic, some neutral, some positively charged, or negatively, or relatively large or small. Depending on the linear arrangement of these decorations, the protein can coil up like an old-fashioned telephone cord, or fold itself in pleats, or sort of randomly squiggle about, in any combination of different patterns in three-dimensional space. Here’s an example, the botox protein I wrote about earlier.

If this protein were to fold up in the wrong shape, it wouldn’t work at all. So how does a protein always fold up into the right shape?

Now, we know that the decision about how to bits of the protein line up next to each other is in some way dependent upon the order of decorations on the atoms in the protein chain. Some decorations like to be next to each other, while others shun each other’s company. In a really simplified image, you can imagine a protein as being like a whip with decorated with a plus and a minus static charge, a north and a south pole magnet, a bit of fuzz and a bit of claw Velcro, a “male” and a “female” Lego block, a similar pair of Duplo blocks, and an electrical plug and a socket. If you were to randomly shake that whip around, you could predict that you would always end up at the same end state: plus with minus, north with south, and so on. This arrangement is the most stable state—the lowest energy state.

Proteins (in theory) behave similarly, only the “whip” is shaken by the random jiggling of thermal motion—and, usually, a specific protein with a specific arrangement of decorations will always end up in the same three-dimensional shape. And, as a testament to human ingenuity and the power of computers, we can actually predict the most stable, lowest-energy state of short proteins with relatively simple arrangements of decorations.

We run into problems, though, when we try to predict the three-dimensional structure of more everyday proteins—which have hundreds of decorations. The most sophisticated computers get bogged down with all the possible permutations, and we have a mixed record at best for understanding how these things fold up. And while we crack our skulls about the problem, nature casually takes proteins and effortlessly folds them into the right shape, over and over again. It keeps a biologist humble.

We don’t even really understand the kinetics of the process—some proteins fold up into their finished shape in milliseconds, while others that are not much longer take thousands of times longer to fold up. What takes longer? Do the slower proteins have more possibilities to try out before they settle on the best shape? Are they just not as flexible? A neat technical tour-de-force gives us at least a little clue towards this last problem. A group of researchers at the National Institutes of Health (I approve of this use of my taxes) found an interesting similarity between the behavior of “fast-folding” and “slow-folding” proteins.

So, consider these two proteins.

This one, nicknamed WW, folds into this shape rapidly.

This one, named GB1, folds into shape 10,000 times more slowly.

What does that mean, what I just wrote? Those numbers are based on taking a huge number of unfolded protein molecules of WW or GB1, putting them in solution, and measuring how long it takes for half of them to assume their folded shape. So, in this case, “how fast something folds” is descripting of a large population, but doesn’t tell us much about how an individual molecule behaves. How long does it take a single individual protein to transition from unfolded to properly-folded?

A morbid analogy would be the half life of a human population: if you looked at all the people born in 1903, you could calculate a half-life, or how long it takes for half of that group of people to die. This tells you a lot about how long an average person lives, which is many years. It tells you nothing about how long it takes to transition from alive to not-alive, which is usually a rapid transition.

What the NIH researchers did was to modify these proteins so that they could examine them, and distinguish more precisely how long it took an individual to change from unfolded to properly folded. To do this, they attached specific dye molecules to either end of the unfolded protein. These dye molecules have a really cool property: if you zap one with the right amount of energy in the form of purple light, it will actually dump that energy onto the other dye molecule, which will fluoresce, shining with red light. They will only do this, though, if the dye molecules are really close together, and in this setting, they are only close together if the protein is properly folded. This process is called Förster Resonance Energy Transfer, or FRET. To go back to the image of a decorated whip, this is like attaching dye markers to either end of the whip. If the whip is unfolded, when you shone purple light on it, it wouldn't fluoresce. Energy couldn't get from one end of the whip to the other:

If it were partially folded, it would fluoresce weakly, because it would be hard for energy to get from one dye molecule to the other.

If it were fully folded, and you shone purple light on it, it would be easy for energy to get from one dye molecule to the other, so it would fluoresce brightly.

So, you could measure how fast it takes the whip to get folded by measuring how rapidly red fluorescence increases. So, measuring how long it takes an individual protein to change from unfolded to properly folded was a matter of measuring how rapidly FRET efficiency increased.

The data from these experiments are not all that fun to look at, involving a fair amount of

But the bottom line was that for both fast- and slow-folding proteins, the transition from no structure at all to completely folded structure was about the same, in the range of a hundredth of a millisecond. The "slow-folding" proteins seem to dawdle and delay and do everything they can to put off folding, but once they decide to fold, they fold just as rapidly as the "fast-folding" ones. It's kind of like the situation mentioned earlier with the population of humans born in 1903; some may live a long time, others die in infancy, but the transition between alive and dead always takes the same, brief amount of time.

So, we know a little more about the process of protein folding now. If we are trying to understand why two proteins fold up at rates that differ ten thousand-fold, we at least know where not to look for answers. However, we still don’t really know what the answer is--what the slow protein is doing when it's not folding up. Nature, like a good magician, is still reminding that we are in the dark.

Hoi Sung Chung, Kevin McHale, John M. Louis, and William A. Eaton (2012). Single-Molecule Fluorescence Experiments Determine Protein Folding Transition Path Times. Science 335: 981- 984.

The Wikipedia web page on FRET is not bad. The above is obviously a gross simplification.

Proteins, Puzzles, and Perjury

There was a bit of news last week that generated headlines such as “Gamers Solve Problem that Stumped Scientists.” As always with science by press release, the reality is cool but not that cool.

The “Protein Folding Problem” is one of the most damnable problems facing biology. It would really be nice to reliably predict protein structures. Knowing the structure of a protein allows us to understand how the protein works, so we can do useful things like design effective drugs. However, precisely determining the 3-D structure of a protein is extremely time-consuming, fiddly work that has a low probability of success. So, there’s a lot of interest in using computers to predict the 3-D structure of a protein.

The problem is this: genes encode proteins, and we can easily “read” a gene to predict the linear sequence of amino acids in a protein. However, a linear sequence of amino acids is useless: it must fold on itself in an often-incredibly complicated structure to make a functional protein. Starting with a linear sequence—basically a string—there’s a nearly infinite number of three-dimensional structures that are possible. Some possible shapes can be eliminated, since certain amino acids in the string don’t want to be near each other or near water. Some other possible shapes are more likely, since certain amino acids in the string want to be near each other, or near water.

In principle, those simple rules should make it possible to predict how a linear sequence of amino acids will fold to make a protein. However, a typical protein is made of several hundred amino acids. So, while computers are OK at predicting structures of very short fragments of proteins, predicting the structure of a protein requires more power. Lots of power—the number of possible ways a typical protein can fold far exceeds the number of possible moves in a game of chess (about 10⁴⁶), so IBM built a successor to the chess-playing “Deep Blue” supercomputer and called it “Blue Gene,” intending it to work on this problem. Blue Gene has been among the most powerful supercomputers for several years, but it still is far from efficient at predicting protein structures

A somewhat more effective approach to “the protein problem” has been to use distributed computing—borrowing time on hundreds or thousands of networked PCs when their owners are not using them. SETI@home, which screens huge amounts of radio telescope data for potential signals of extraterrestrial life, is a famous example of this. Biochemists have Rosetta@home, which uses the same approach to predict protein structure. This venture has actually produced some predictions which jibed pretty well with the actual structures. But Rosetta is still limited; being a computer program, it relies on brute force and wastes resources looking at possibilities that are “stupid.”

One way to get around this problem is to borrow from humans something that computers lack: intuition. This has been the approach of the creators of “Foldit,” a program that turns the protein folding problem into a game. Players are given a snippet of a protein, and (not needing to understand anything about Van der Waals forces or acid-base interactions), jiggle it around until it reaches a very stable conformation—which corresponds to a high score. As the authors of the paper that made the headlines say, this program uses the power of games…

“to channel human intuition and three-dimensional pattern-matching skills to solve challenging scientific problems. Although much attention has recently been given to the potential of crowdsourcing and game playing, this is the first instance that we are aware of in which online gamers solved a longstanding scientific problem. These results indicate the potential for integrating video games into the real-world scientific process: the ingenuity of game players is a formidable force that, if properly directed, can be used to solve a wide range of scientific problems.”

So what did the gamers actually do? They started with a bunch of predicted structures for one protein, generated by Rosetta@home, and tweaked them. Once the actual protein structures were experimentally determined (again, a terribly painful and difficult task), the gamers’ predictions were noticeably better than Rosetta’s. Here’s a picture comparing their results with the actual structure—the linear string of amino acids is sometimes presented as a flat ribbon, sometimes as a noodle; it can curl up like a telephone cord, or lie flat in a sheet, but this picture shows one string.

The red ribbons represent the predictions of Rosetta; the yellow represent the predictions of the gamers; and the blue is the real structure of the protein. All three are superimposed. In almost all parts of the protein, the yellow, gamers’ structure is closer to the real, blue structure than the red, Rosetta structure. Bravo gamers! However, it is worth noting that the gamers started from structural predictions by Rosetta, and there are still places where neither Rosetta nor the gamers predicted reality very well.

This result leaves the protein structure problem in an interesting place. On the one hand, progress could be made by using more of that intangible, unquantifiable whatzit, human intuition. However, this is not intellectually satisfying; it would be nice to say that we really understood the rules of protein folding—and if we could understand them, we could teach these rules to a sufficiently powerful computer. After all, a computer has no intuition, but then again, nor does a string of amino acids, which just follows the rules of physical law. So, clearly, we need bigger more powerful computers which can more closely simulate reality.

This seemed like an insurmountable challenge—only so many people will join with a distributed network such as Rosetta@home, and machines much bigger than Blue Gene are prohibitively expensive. However, Felix Balatro and his coworkers at Miskatonic University and in the Ukraine arrived at a devious solution to the problem. In a series of stunning papers starting in the December 2011 issue of the (admittedly rather obscure) Ukrainskii Zhurnal Tsilkovita Durnitsya , Balatro predicted the structure of a half-dozen difficult proteins with unprecedented accuracy.

These results were not widely reported in the popular news, but they raised a lot of questions in academia. After all, Miskatonic was not known as a computer science powerhouse, and the Ukrainian group seemed suspiciously difficult to contact for discussion about methods. Nonetheless, the results kept coming in the early part of 2012, and the predictions only gained in sophistication. In fact, one of the predictions was actually used to develop an anti-retroviral drug.

The curtain was finally lifted on the mystery by the German weekly der Zwiebel. The elusive Ukrainians were a front group for an organized crime syndicate that rented out time on the botnet of more than seven million computers infected with the “Conficker” worm. Balatro realized that this botnet was by far the world’s largest distributed computing network, and that its masters—although very punctilious about their payment schedule—were essentially in the business of renting computing power. Granted, nearly all of their other customers were criminals, and the power was typically used for card-hacking and DDOS attacks, but the rates were very cheap and the programmers very clever. Balatro arrived at the conclusion that this was the best way he could use his insubstantial research funding.

This disclosure left the scientific community, and society as a whole, in a quandary. Some demanded that Balatro’s papers should be retracted—but they couldn’t say exactly why, since the results were valid and there were no obvious conflicts of interest. Some prosecutors wanted to bring suit—but there really weren’t any injured parties, and no US laws were broken. An intriguing new avenue for drug design had been suggested by some of his results—but would such a drug be ethically tainted?

Although the scientific worth of Balatro’s results remains unchallenged, the ethical clouds surrounding the results continue to gather. An anonymous whistleblower recently revealed to der Zwiebel that DARPA actually considered and partially developed a worm that would allow it to run simulations of atomic weapon tests at low cost. Balatro himself provides the most recent puzzle; he was unexpectedly absent for the first day of his own class in the summer 2012 session at Miskatonic University, and the university administration has not been able to get in contact with him for over a month. There is concern that the Ukrainians did not appreciate the attention he drew to them, or worse—that he failed to make a payment.

Allen, F., et al (2001). Blue Gene: A vision for protein science using a petaflop supercomputer. IBM Systems Journal 40: 310-327.

Firas Khatib, Frank DiMaio, Foldit Contenders Group, Foldit Void Crushers Group,

Seth Cooper, Maciej Kazmierczyk, Miroslaw Gilski, Szymon Krzywda, Helena Zabranska, Iva Pichova, James Thompson, Zoran Popović, Mariusz Jaskolski, David Baker (2011). Crystal structure of a monomeric retroviral protease solved by protein folding game players. Nature Structural and Molecular Biology. Published online 18 September 2011; doi:10.1038/nsmb.2119.

Balatro, Felix, and Українська асоціація обманщики (2012). You shouldn’t believe everything you read. український журнал цілковита дурниця 22: 18-41.

Balatro, Felix, and Українська асоціація обманщики (2012). It’s probably a good idea to run these author names through Google translate. український журнал цілковита дурниця 22: 138-141.

Balatro, Felix, and Українська асоціація обманщики (2012). Miskatonic University may ring a bell for sci-fi fans. український журнал цілковита дурниця 23: 77-91.