Never a simple staple

Stapled peptide. Image: Nature

Carmen Drahl of C&EN has a pretty nice overview of what's happening in the world of stapled peptides. Those who have followed this development are aware of both the promise and the caveats in the area. Interest in constrained peptides was sparked by the observation that helices are involved in a lot of important protein-protein interactions and therapeutics areas. Cancer seems to be an especially prominent target.

The simple thinking is that if you constrain a helix to its helical shape using various chemical strategies, you could minimize the entropic cost of helix formation. In addition, by modulating the properties of whatever chemical group you are using to constrain the structure, you could possibly get better affinity, cell penetration and stability. The strategies used have been varied, from olefin linkers to hydrocarbon linkers, and they have a long history. But stapled peptides have been especially noteworthy; the staple in this case is a short hydrocarbon linker connecting one residue to another a few angstroms away. Based on this idea, groups from Harvard launched a biotech startup named Aileron. Stapled peptides, it seemed were on a promising upward trajectory.

Except that nothing in biology is as simple as it seems. A recent report from groups in Australia and Genentech demonstrated that a previously promising stapled helix which inhibits the antiapoptotic protein Bim is not as potent as it seemed. The problems seem to lie with the fundamental helical structure of the molecule; the paper found that in adding the hydrocarbon staple, you are perturbing some productive intramolecular hydrogen bonding interactions between the residues, and this results in an unfavorable enthalpy of binding.

It's worth reading Carmen's piece not just for the science but for the potential conflict of personalities; science is a human game after all. In this case the conflict arises not only from the Australia/Genentech group's doubts about the original Harvard peptide but the Harvard group's contention that the Australia/Genentech team was in fact looking at the wrong peptide.

Hopefully the misunderstanding will be cleared soon but one thing is clear; this debate seems to be good for science. Constraining helices and other peptides is a completely legitimate way of thinking about improving drug potency and properties, but the devil is in the details. Whenever you put on a constraint you are going to subtly perturb the structure of the molecule, and what seems important here is to investigate how these subtleties will affect the desired functions and properties.

Ultimately stapled peptides are no different from a dozen other drug design strategies. There are cases where they will work and cases where they won't, and any efforts to tease these differences apart will advance the science. Neither stapled peptides nor any other kind of specific drug modification is going to give us the silver bullet. But we already knew this, didn't we?

#Arseniclife reviews: Missing the forest for the trees

In this year's ScienceOnline conference I co-moderated a productive session on peer review in which I pointed out how overly conservative or agenda-driven peer reviews can prevent the publication of legitimate science. Now here's a case where the opposite seems to have occurred; highly questionable science making it through the filter of peer review as easily as particles of dust would make it through a sieve with penny-sized holes.

Thanks to the Freedom of Information Act, USA Today and a couple of other scientists got their hands on the reviews of the infamous #arseniclife paper. There were three reviewers of the study, and all of them approved the paper for publication.

What's interesting is how effortlessly the reviewers miss the forest for the trees. We of course have the benefit of hindsight here, but it's still striking how all three reviews simply swallow the flawed paper's basic and potentially textbook-changing paradigm - the substitution of arsenic for phosphorus - right off the bat. Once they accept this basic premise, all their other objections can simply be seen as nitpicking and window dressing. Only one reviewer asks questions that come close to questioning the absence of phosphorus in the medium, but even he or she quickly veers off course. Another calls the paper a "rare pleasure" to read, seemingly unaware that the pleasure which the paper has provided comes from an extraordinarily ambitious claim that needs to be vetted as closely as possible.

In fact the reviewers ask good questions about vacuoles seen in the bacterium, about better standards for some of the experiments, about better methods to quantify arsenic in its various forms. They even ask a few very chemical questions regarding bond distances. But all these questions are somewhat beside the point since they flow from a fundamentally flawed belief.

When I was in graduate school, the most important thing that my advisor taught me was to always question the assumptions behind a study. If you don't do this, it's easy to be seduced by the technical details of the experiment and to let these details convince you that the basic premise is validated. That's what seems to me to have happened here. All the reviewers seem to have been sucked into legitimate and interesting questions about minutiae. But all the time they forget that what really needs to be questioned is the giant assumption from which all the minutiae have been derived, an assumption that we now know does not stand up to scrutiny. There's an important lesson here.

Andrew Grant

Andrew Grant's name may not be known to everyone, but he was a well-known computational chemist who made some very original contributions to the field. For most of his career he worked at AstraZeneca. 

A few days ago he tragically passed away from a massive heart attack while still in excellent health and in his 40s. Makes you appreciate how fortunate you are to be alive and how fragile your time on this planet is. Although I never met him, I remember him giving a talk at OpenEye a few years ago on electrostatics. I remember an unassuming, cheerful man who was clearly passionate about his science.

Grant's longtime friend and colleague Anthony Nicholls of OpenEye has a moving and informative tribute on his webpage. As Anthony notes, wholly original contributions in the field of molecular modeling have been very rare.

"More than just encouragement, he gave ideas. Before he had settled in Macclesfield he had spent a year in the Wilmington branch, working with Brian Masek. Brian had been playing around with the superposition of molecules represented as fused spheres. The code he had written was slow and prone to getting stuck in local minima, but when it worked it gave strikingly good overlays. While Andy was with Harold Scheraga, he had been given the task of seeing how one might use Gaussians to calculate a robust and rapid estimate of molecular area- a problem he had not solved. However, he had worked with Professor Barry Pickup at Sheffield University, his PhD advisor, on the concept of representing molecular volumes with Gaussians. In fact, although it is little appreciated, I think that work with Barry and Maria Gallardo, who became his long-time partner, was one of the best ever in the modeling of molecules. It is highly unintuitive that one can use Gaussians to not just represent the volume of an atom, many had been drawn to that concept before, but to use the convolution formula for Gaussians to represent spherical overlaps- to any order! Pure genius. And the result- that you could model the fused sphere volume to within 0.1%- I do believe is the most remarkable result I have ever seen in our field."

Virtual shock

The Raspberry Pi computer sat innocently in the glove box. This particular glove box was military-grade, enclosed on all sides except one by an inch of reinforced steel, with a narrow porthole made from Pyrex for viewing and manipulation. A robotic arm allowed you to punch the keys. We gratifyingly thought of the $35 units that we had purchased for this project; there’s only so many octa-core Dell Precision Towers that you can blow up every day.

I winced as Alex gingerly started adding yet another nitrogen atom to the ring. It was conventional wisdom, known for ages and duplicated in laboratories around the world. Most explosives including TNT and RDX contained a generous dose of nitrogen atoms; add enough nitrogens to a molecule – preferably a ring – in certain strategic positions and you would almost certainly make a big bang.  The bang came from a fundamental property of nitrogen, its tendency to cling to its own kind and eschew others with a fanatical tenacity. It was just basic chemistry, except that it had been put to good use in the service of war and killing for decades.

But nobody had pushed the principle to its limits. Not like this.

The idea came from a recent publication from Prof. Klapötke’s group in Munich. They had synthesized azidoazide azide. That tongue twister gave away the identity of the beast; “azide” was chemical lingo for a group of three nitrogens strung together in a line. Azides are notoriously explosive; lead azide for instance consists of a single lead atom decorated with six nitrogens (two azides), waiting to blow anyone who approaches them to kingdom come. Azidoazide azide sported no less than eight nitrogens tightly knit around a ring. The resulting molecular entity was so unstable that it literally disintegrated the moment it was born. As veteran chemist and blogger Derek Lowe described it,

“The compound exploded in solution, it exploded on any attempts to touch or move the solid, and (most interestingly) it exploded when they were trying to get an infrared spectrum of it. The papers mention several detonations inside the Raman spectrometer as soon as the laser source was turned on”.

Basically the thing exploded no matter what you did or didn’t do to it. The infrared spectrum was a harmless thing, a common experimental technique only supposed to aid in deciphering the structure of a molecule based on the vibrations of bonds between specific atoms. But the mercurial fiend was so remarkably unstable that it was a miracle it could yield itself to being described in a respectable journal, let alone be subjected to the indignities of infrared radiation.

It was after reading the paper that Alex had a brainwave. Azidoazide azide clearly blew up as soon as it was made. What if we designed an explosive that actually blew up before it was made? Preferably the moment it was drawn on a computer and optimized into a realistic structure with normal bond lengths and angles. We could call it a pre-explosive. You could always run the risk that such a compound blew up when it was doodled on a paper napkin by that workaholic chemist even as his kids were playing scrabble in the living room, but everyone knew that decades of graduate school training had done nothing to obliterate chemists’ bad molecular drawings with nonsensical bond lengths and angles. No risk there.

It would be the perfect weapon. Ideally we would want tantalizing features of the molecule – perhaps an infrared spectrum, maybe a melting point, even a few steps of the enabling reaction  – to somehow fall into the hands of the enemy. This could be accomplished using a double agent or a spy who willingly allowed herself to be captured with key documents. Once the enemy located the details of the characterization, they would no doubt think that they now possessed the recipe for a key weapon of strategic importance; perhaps a new chemical or debilitating agent, a revolutionary material for armor or a life-saving battlefield drug. All resources would be focused on figuring out the molecular structure of this potential bonanza by working backwards from its properties.

Now all that we would have to do is wait for them to try to reverse-engineer the molecule. Of course, everything’s that’s reverse-engineered these days has to first pass through a computer model. There is no better way to unearth a plausible structural gem from the dross of incomplete data than by using one of those new neural network-enhanced quantum genetic algorithms. The number of possible structures corresponding to such sparse data is astronomical and only a computer can cycle through these endless wannabes. But thanks to D-Wave’s pioneering work, computing power has progressed to such an extent now that commercial software can search roughly ten trillion molecular possibilities in a matter of hours. Once the enemy lets its computing power loose on our data, their computer transforms itself into a literal time bomb even as it cycles through the list of possible structures. Since the algorithm is random, the correct structure may come up within a few seconds or it may be the last one on the list. But what’s certain is that at some point it will appear, and the rest will literally be history. History scattered around in the form of discrete particulate matter.

We waited with bated breath the first time we did it, allowing the molecular structure to relax and optimize its energy. We don’t know exactly what happened as the convergence cycles came to a standstill and the initially deformed bonds started to look normally formed. They found both of us stretched out on the floor. Fortunately this first attempt had only resulted in a design with a modest PEDI (Pre-Explosive Detonation Impact) factor of 5.2, hardly sufficient to cause maiming or death; theory predicts that we would need a PEDI of at least 40 to cause damage equivalent to that caused by the most powerful non-nuclear explosive. But after the mishap the computers were duly installed in a robot-controlled glove box with reinforced walls. The plan was to ramp up the PEDI in a respectable, controlled manner.

It’s a particularly nice day outside as Alex is about to fire up a calculation on a potential molecular candidate. “Remind me what you are doing, again. I have to admit I was too groggy when you excitedly called me in the middle of the night yesterday”. “Well, it was one of those obscure new open-access journals they keep emailing us about. Usually I delete the emails the moment I see them, but this one had something in the title about azides so I took a look. There was a paper from some group in Latvia, from a university I have never heard of. Conforming to the shoddy standards in these journals, there was apparently a lot of characterization but few specific structures except for two general scaffolds, both similar to the work done at Toulouse on low-yield azides in the 80s; I guess Raman spectrometers are cheap and they were obsessed with patent filings. Thought I would reverse-engineer one of them just to see what it looks like.”

The computer displays elegant ball-and-stick structures in front of us as I absent-mindedly listen to Alex and tap my fingers on the side of the glove box. Alex’s quip about open-access journals makes me think of that article in Nature published a few months back which talked about the nuisance created by the proliferation of spurious open-access journals. Many of these use fake fronts, email addresses and entire made-up office locations to convince readers of their authenticity. Most ask you to foot the publishing fees and then disappear. I bet you would find no trace of their whereabouts if you actually decided to look for them. Of course you probably deserved it if you were credulous enough to fall for an unknown publication from a made-up source.

Suddenly something snaps inside me. I get up, startled, and look at Alex, even as he watches the computer flash a structure with a particularly beautiful geometric arrangement of atoms. Oxygens are flaming red, nitrogens are a tranquil blue.

Six thousand miles away in Kiev, a man sits sipping coffee in a café near the old town square. His cell phone rings and a gruff voice communicates the message. The man hangs up and mutters to himself, “45”. His face breaks into a faint, satisfied smile. He goes back to sipping his coffee.

This post was inspired by a spoof article by Isaac Asimov. In the 1940s Asimov was working on a rather thankless Ph.D. at Columbia University. Part of his work involved investigating the properties of compounds which were highly soluble in water. Some of these chemicals were so highly soluble that they seemed to dissolve almost instantly. This behavior encouraged Asimov to pen a spoof article titled “The Endochronic Properties of Resublimated Thiotimoline” about a compound that actually dissolves before it hits the water. Recent articles on new explosives that seem to literally detonate as soon as they are formed lead me to similar thinking…

First published on Scientific American Blogs.

The GPCR Network: A model for open scientific collaboration

This post was first published on the Scientific American Blog Network

The complexity of GPCRs is illustrated by this mechanical view of their workings (Image: Scripps Research Institute)

G Protein-Coupled Receptors (GPCRs) are the messengers of the human body, key proteins whose ubiquitous importance was validated by the 2012 Nobel Prize in chemistry. As I mentioned in a post written after the announcement of the prize, GPCRs are involved in virtually every physiological process you can think of, from sensing colors, flavors and smells to the action of neurotransmitters and hormones. In addition they are of enormous commercial importance, with something like 30% of marketed drugs binding to these proteins and regulating their function. These drugs include everything from antidepressants to blood-pressure lowering medications.

But GPCRs are also notoriously hard to study. They are hard to isolate from their protective lipid cell membrane, hard to crystallize and hard to coax into giving up their molecular secrets. One reason the Nobel Prize was awarded was because the two researchers – Robert Lefkowitz and Brian Kobilka – perfected techniques to isolate, stabilize, crystallize and study these complex proteins. But there’s still a long way to go. There are almost 800 GPCRs, out of which ‘only’ 16 have been crystallized during the past decade or so. In addition all the studied GPCRs are from the so-called Class A family. There’s still five classes left to decipher, and these contain many important receptors including the ones involved in smell. Clearly it’s going to be a long time before we can get a handle on the majority of these important proteins.

Fortunately there’s something important that GPCR researchers have realized; it’s the fact that many of these GPCRs have amino acid sequences that are similar. If you know what experimental conditions work for one protein, perhaps you can use the same conditions for another similar GPCR. Even for dissimilar proteins one can bootstrap based on existing knowledge. Based on the similarity you could also build computer models for related proteins. Finally, you can use a small organic molecule like a drug to essentially serve as a clamp that helps stabilize and crystallize the GPCR.

But all this knowledge represents a distributed body of work, spread over the labs of researchers worldwide and expected to be sequestered by them for their own benefits. These individual researchers working in isolation would not only face an uphill battle in figuring out the right conditions for studying their proteins but would also run the risk of reinventing the wheel and duplicating conditions from other laboratories. The central question asked by all these researchers is, how does the binding of a small molecule like a drug on the outside of a GPCR lead to the transmission of a signal to the inside?

Enter the GPCR Network, a model of collaborative science which promises to serve as a fine blueprint for other similar efforts. The network was created through a funding opportunity from the National Institute of General Medical Sciences in 2010 and has set itself the goal of structurally characterizing 15-25 GPCRs in the next five years. The effort is based at the Scripps Research Institute in La Holla and involves at least a dozen academic and industrial labs.

So how does this network work? The idea for the network came from the recognition that there are hundreds of GPCR researchers spread across the world. Each one is an expert on a particular GPCR but each one has largely worked separately. What the network does is to leverage the expertise from one researcher’s lab and apply it a similar GPCR in another lab (there are technical criteria for defining ‘similarity’ in this case). There are a variety of very useful protocols, ideas and equipment that can be shared between labs. This sharing cuts down on redundant protocols, saves money and accelerates the resolution of new GPCR puzzles much faster than what could be achieved individually.

For instance, a favorite strategy for stabilizing a GPCR involves tagging it with an antibody that essentially holds the protein together. An antibody that worked for one GPCR can be lent to a researcher who is investigating another GPCR with a similar amino acid sequence. Or perhaps there is a chemist who has discovered a new molecule that binds very tightly to a particular receptor. The network would put him in touch with a crystallographer who could use that molecule to fish out that GPCR from a soup of other proteins and crystallize it. Once the crystallographer solves the structure of the protein using this molecule, he or she could then send the structure to a computer modeler who can use it to build a structure for another particularly stubborn GPCR which could not be crystallized. The computer model might explain some unexpected observations from a fellow network researcher who was using a novel instrumental technique. This novel technique would then be shared with everyone else for further studies.

Thus, what has happened here is that the individual pockets of knowledge from a biochemist, organic chemist, crystallographer and computer modeler – none of whom would have proceeded very far by themselves – are merged together to provide an integrated picture of a few important GPCRs. The entire pipeline of protocols including protein isolation, purification, structure determination and modeling also serves as a feedback loop, with insights from one step constantly informing and enriching others. This represents a fine example of how collaborative and open research can accelerate important research and save time and money. It's to the credit of these scientists that they haven't held their valuable reagents and techniques close to their chest but are sharing them for everyone's benefit.

In the three years since it has been up and running, the GPCR Network has leveraged the expertise of many experts in generating insights into the structure and function of important receptors. Its collaborative efforts have resulted in eight protein structures in just two years. These include the adenosine receptor which mediates the effect of caffeine, the opioid receptor which is the target for morphine and the dopamine receptor which binds to dopamine. Every one of these collaborations involved a dozen or so researchers across at least three or four labs, with each lab employing its particular area of expertise. Gratifyingly, there’s also a few industrial labs involved in the efforts and we can hope that this number will increase even as the pharmaceutical industry becomes more collaborative.

It’s also worth noting that the network was funded by the NIGMS, an institution which has been subject to the whims of budget and personnel cuts. This institution is now responsible for an effort that’s not only accelerating research in a fundamental biological area but is also contributing to a better understanding of existing and future drugs. Scientists, politicians and members of the public who are seeking a validation of basic, curiosity-driven scientific research and reasons to fund it shouldn’t have to look for.

Review on N-methylation

Veteran peptide chemist Horst Kessler (TU Munich) has a good review on the effects of N-methylation of peptides and proteins in a recent issue of Angewandte Chemie. N-methylation has been an interesting and frequently productive strategy for a long time, but the main problem was that the chemistry needed to implement it wasn't there yet. But thanks to new developments chemists have caught up and selective N-methylation of amides no longer needs to be the rate-limiting step that it was.

N-methylation has a variety of interesting and potentially very useful effects on small molecule and peptide conformation and function. For one thing, N-methylated amide bonds have a different distribution of cis and trans forms which is somewhat more evenly distributed than that in non N-methylated amide bonds which dominantly prefer the trans conformation. This can significantly tweak the distribution of conformations in solution.

From a biological standpoint things get even more interesting. N-methylation makes the molecule more lipophilic and therefore more membrane-permeable, improving cell penetration. It gets rid of one hydrogen bonding N-H bond. This can sometimes have an unfavorable effect on permeability if that N-H forms an intramolecular hydrogen bond, but often it can help. Intramolecular hydrogen bonds are another valuable tactic for hiding polar surface area and improving permeability. The ideal situation is a combination of both N-methylation and intramolecular hydrogen bonding, exemplified by the archetypal "large", complex, biologically active drug, cyclosporine. Recent studies by the Jacobson (UCSF) and Lokey (groups) have described strategies for both specific N-methylation chemistry and for predicting permeability using computational calculations.

Finally, N-methylation can prevent recognition and cleavage by peptidases which recognize "normal" amide bonds, especially when the N-methylated amides are part of a cyclic peptide. All these factors can significantly improve bioavailability. Kessler talks about all of them and illustrates these principles with a few striking examples, including somatostatin, amanitin and melanocortin. Many of these sport similar motifs, leading to ideas for possible design of standardized building blocks for improving permeability and bioavailability. The piece is worth a look if you are into developing peptides and peptidomimetics as drugs or even more generally if you are interested in peptide and small molecule conformations.

The value of long-term vision

Friend and fellow blogger David Kroll has a great profile of Bob Lefkowitz, last year's chemistry Nobel Laureate from Duke. The most striking thing for me was to read about how Duke bent over backwards and went to unbelievable lengths to get Lefkowitz on their faculty in the 70s. Says something about the value of long-term vision and investment in basic research, something that sadly seems to be exceedingly lacking these days.

"Lefkowitz almost didn't make it to Duke. He had already committed to practicing medicine at the Massachusetts General Hospital of Harvard University after his service commitment. After six months there, "I really missed the lab," Lefkowitz recalls, adding he was "like a junkie who needed a fix."

Meanwhile, 600 miles south in Durham, the medical school at Duke University was flourishing. Dr. Andy Wallace, chief of cardiology, had seen the young Lefkowitz present his receptor studies at an American Heart Association meeting. He and Dr. Jim Wyngaarden, chairman of medicine, they tried to lure Lefkowitz to Duke. However, Harvard had already promised Lefkowitz a faculty position after his cardiology fellowship.

Lefkowitz admits he had no intention of coming to Duke and politely rejected Duke's offer. But Wallace and Wyngaarden rejected Lefkowitz's rejection. Their counteroffer included a $32,000 annual salary—the equivalent of $165,000 today (the initial offer was $24,000)—and an open-ended request for his other needs.

Still thinking Duke wasn't in his future, he responded with "outrageous demands" Lefkowitz says. One of those was that he start as an associate professor with academic tenure, a position that requires rigorous review at seven to 11 years of faculty service. He was just 30, straight out of his fellowship.

"That was the most outrageous demand and that was the one put in there to scotch the whole deal because I didn't want to come," Lefkowitz says. "The whole purpose of my request was to give me a graceful way out because I knew in my head that what I was asking was impossible."

Wyngaarden and Wallace met every demand.

Lefkowitz was dumbfounded. "Duke was a young institution [in 1973]. But it was a decent institution, and the offer was just so non-comparable with what Harvard was offering that I said, 'This is it. I gotta go for it.'"

"But a lot of people said, 'How can you go to Duke?' Even my in-laws at the time." He reproduces the Yiddish accent: "'Whaddaya, crazy? You're at Hawvaad.' But something said, 'Go for this.'"

Who knew VCs had a sense of humor

So it's the annual J P Morgan Healthcare Conference in California and I see, of all things...#jpmpickuplines on Twitter. I don't know how much these can mitigate the still-dour VC landscape, but hey, at least nobody can blame them for trying to present evidence that they are human.

Chemistry and Biology: Kuhnian or Galisonian?

Peter Galison who has emphasized the dominance of experimental techniques in engineering scientific revolutions (Image: BNL).

First published on the Scientific American Blog Network.

Freeman Dyson has a perspective in this week's Science magazine in which he provides a summary of a theme he has explored in his book "The Sun, the Genome and the Internet". Dyson's central thesis is that scientific revolutions are driven as much or even more by tools than by ideas. This view runs somewhat contrary to the generally accepted belief regarding the dominance of Kuhnian revolutions - described famously by Thomas Kuhn in his seminal book "The Structure of Scientific Revolutions" - which are engineered by ideas and shifting paradigms. In contrast, in reference to Harvard university historian of science Peter Galison and his book "Image and Logic", Dyson emphasizes the importance of Galisonian revolutions which are driven mainly by experimental tools.

As a chemist I find myself in almost complete agreement with the idea of tool-driven Galisonian revolutions. Chemistry as a discipline rose from the ashes of alchemy, a thoroughly experimental activity. Since then there have been four revolutions in chemistry that can be called Kuhnian. One was the attempt by Lavoisier, Priestley and others at the turn of the 17th century to systematize elements, compounds and mixtures to separate chemistry from the shackles of alchemical mystique. The second was the synthesis of urea by Friedrich Wohler in 1828; this was a paradigm shift in the true sense of the term since it placed substances from living organisms into the same realm as those from non-living organisms. The third revolution was the conception of the periodic table by Mendeleev, although this was more of a classification akin to the classification of elementary particles by Murray Gell-Mann and others during the 1960s. A minor revolution accompanying Mendeleev's invention that was paramount for organic chemistry was the development of the structural theory by von Leibig, Kekule and others which led the way to structure determination of molecules. The fourth revolution was the application of quantum mechanics to chemistry and the elucidation of the chemical bond by Pauling, Slater, Mulliken and others. All these advances blazed new trails, but none were as instrumental or overarching as the corresponding revolutions in physics by Newton (mechanics), Carnot, Clausius and others (thermodynamics), Maxwell and Faraday (electromagnetism), Einstein (relativity) and Einstein, Planck and others (quantum mechanics).

Why does chemistry seem more Galisonian and physics seem more Kuhnian? One point that Dyson does not allude to but which I think is cogent concerns the complexity of the science. Physics can be very hard, but chemistry is more complex in that it deals with multilayered, emergent systems that cannot yield themselves to reductionist, first principles approaches. This kind of complexity is also apparent in the branches of physics typically subsumed under the title of "many-body interactions". Many-body interactions range from the behavior of particles in a superconductor to the behavior of stars condensing into galaxies under the influence of their mutual gravitational interaction. There are of course highly developed theoretical frameworks to describe both kinds of interactions, but they involve several approximations and simplifications, resulting in models rather than theories. My contention is that the explanation of more complex systems, being less amenable to theorizing, are driven by Galisonian revolutions rather than Kuhnian.

Chemistry is a good case in point. Linus Pauling's chemical theory arose from the quantum mechanical treatment of molecules, and more specifically the theory of the simplest molecule, the hydrogen molecular ion which consists of one electron interacting with two nuclei. The parent atom, hydrogen, is the starting point for the discipline of quantum chemistry. Open any quantum chemistry textbook and what follows from this simple system is a series of approximations that allow one to apply quantum mechanics to complex molecules. Today quantum chemistry and more generally theoretical chemistry are highly refined techniques that allow one to explain and often predict the behavior of molecules with hundreds of atoms.

And yet if you look at the insights gained into molecular structure and bonding over the past century, they have come from a handful of key experimental approaches. Foremost among these are x-ray diffraction, which Dyson also mentions, and Nuclear Magnetic Resonance (NMR) spectroscopy, also the basis of MRI. It is hard to overstate the impact that these techniques have had on the determination of the structure of literally millions of molecules ranging across an astonishing range of diversity, from table salt to the ribosome. X-ray diffraction and NMR have provided us not only with the locations of the atoms in a molecule, but also with invaluable insights into the bonding and energetic features of the arrangements. Along with other key spectroscopic methods like infrared spectroscopy, neutron diffraction and fluorescence spectroscopy, x-rays and magnetic resonance have not just revolutionized the practice of chemical science but have also led to the most complete understanding we have yet of chemical bonding. Contrast this wealth of data with similar attempts using purely theoretical techniques which can also be used in principle to predict the structures, properties and functions of molecules. Progress in this area has been remarkable and promising, but it's still orders of magnitude harder to predict, say, the most stable configuration of a simple molecule in a crystal than to actually crystallize the chemical even by trial and error. From materials for solar cells to those for organ transplants, experimental structure determination in chemistry has fast outpaced theoretical prediction.

What about biology? The Galisonian approach in the form of x-ray diffraction and NMR has been spectacularly successful in the application of chemistry to biological systems that culminated in the advent of molecular biology in the twentieth century. Starting with Watson and Crick's solution of the structure of DNA, x-ray diffraction basically helped formulate the theory of nucleic acid and protein structure. Particularly noteworthy is the Sanger method of gene sequencing - an essentially chemical technique - which has had a profound and truly revolutionary impact on genetics and medicine that we are only beginning to appreciate. Yet we are still far from a theory of protein structure in the form of protein folding; that Kuhnian revolution is yet to come. The dominance of Galisonian approaches to biochemistry raise the question about the validity of Kuhnian thinking in the biological sciences. This is an especially relevant question because the last Kuhnian revolution in biology - a synthesis of known facts leading to a general explanatory theory that could encapsulate all of biology - was engineered by Charles Darwin more than 150 years ago. Since then nothing comparable has happened in biological science; as indicated earlier, the theoretical understanding of the genetic code and the central dogma came from experiment rather than the very general synthesis in terms of replicators, variation and fitness that Darwin put together for living organisms. Interestingly, in his later years (and only a year before the discovery of the structure of DNA) the great mathematician John von Neumann put forward a Darwin-like, general theoretical framework that explained how replication and metabolism could be coupled to each other, but this was largely neglected and certainly did not come to the attention of practicing chemists and biologists.

Dyson's essay and the history of science does not necessarily assert that the view of science in terms of Kuhnian revolutions is misguided and that in terms of Galisonian revolutions is justified. It's rather that complex systems are often more prone to Galisonian advances because the theoretical explanations are simply too complicated. Another viewpoint driven home by Dyson is that Kuhnian and Galisonian approaches alternate and build on each other. It is very likely that after a few Galisonian spells a field becomes ripe for a Kuhnian consolidation.

Biology is going to be especially interesting in this regard. 

The most exciting areas in current biology are considered to be neuroscience, systems biology and genomics. These fields have been built up from an enormous number of experimentally determined facts but they are in search of general theories. However, it is very likely that a general theoretical understanding of the cell or the brain will come from very different approaches from the reductionist approaches that were so astonishingly successful in the last two hundred years. A Kuhnian revolution to understand biology could likely borrow from its most illustrious practitioner - Charles Darwin. One of the signature features of Darwin's theory is that it seeks to provide a unified understanding that transcends multiple levels of biological organization, from individual to society. Our twenty-first view of biology adds two pieces, genes and culture, to opposite ends of the ladder. It is time to integrate these pieces - obtained by hard, creative Galisonian science - into the Kuhnian edifice of biology.

Nobel Week Dialogue

There hasn't been much blogging over the last two weeks, mainly because I have been blogging for a special event preceding the official Nobel Prize ceremony in Stockholm. 

"Nobel Week Dialogue" was a day-long symposium organized by the Nobel committee and other sponsors on December 9. The topic was "The Genomic Revolution and its Impact on Society" and it featured many science and policy leaders including Eric Lander, Steven Chu, James Watson and Craig Mello. 

I was invited to write for this event and I have four posts, mainly historical and philosophical, contemplating aspects of the genomic revolution.

1. Physicists in Biology; And Other Quirks of the Genomic Age.

2. An interview with Watson and Crick by Horace Freeland Judson.

3. How they did it.

4. The Third Age of Molecular Biology.