Big Trouble in Little Synthetic Organic Chemistry?

Michael Rafferty who teaches in the Department of Medicinal Chemistry at the University of Kansas has a thought-provoking article in the Journal of Medicinal Chemistry in which he questions whether it's time to reinvent the model for training academic scientists in graduate programs to better equip them for the complexity and rigors of modern drug discovery. His target is the cadre of synthetic organic chemists who for decades have functioned as the indispensable backbone of the pharmaceutical industry. The title of the article - "No Denying It: Medicinal Chemistry Training Is In Big Trouble" - should be self-explanatory, in case anyone is wondering where exactly the author's sentiments lie on the topic.

Even today when you say that someone is a "medicinal chemist" it usually means someone who is trained as a synthetic organic chemist, who either goes into the lab and makes molecules himself or herself or who directs other people to do the same. Rafferty is asking whether the decades-old standard of recruitment into medicinal chemistry groups in the pharmaceutical industry - sound training in synthetic organic chemistry - might have to be revised.

Rafferty's basic point is that the kind of wisdom needed to find hits, advance them into lead compounds and finally into drug candidates does not really benefit from having a background in pure synthetic organic chemistry: it's much more about SAR analysis and understanding pharmacological properties. As he points out, the pharmaceutical industry has of course realized and maintained that all that wisdom can be learnt on the job. But Rafferty is not sure, and part of his skepticism comes from two revealing studies that basically showed two things: first, that even experienced medicinal chemists do not agree when picking good leads, and second, that most medicinal chemists even now don't really take optimum properties into account when designing compounds. The problem with lead picking is thus not synthesis, it's an ability to parse a complex landscape of multiple properties. Multiparameter optimization is still a beast whose footprints are rarely found among the thinking of medicinal chemists.

I think in general he's right. Advances in pharmacology, toxicology, computational chemistry and other fields over the past few decades have made it possible to both calculate as well as use property-based information in early stages of drug discovery. The article focuses on lipophilicity as one parameter which really should be considered on a regular basis but which isn't a lot of time. The problem is that a lot of synthesis has turned into a machine for cranking out molecules, so drug discovery scientists end up making molecules because they can be easily made. It's a theme that I and others have written about previously: making molecules is no longer the rate determining step in drug discovery: design is the important paradigm. One of the reasons is that CROs in China and India can now often make molecules as easily as in-house synthetic chemists. In one sense what the article is saying is because these CROs can now pick up the slack, chemists can use the time to more productively think about property-based optimization.

Now while I think it's cogent to include as much property information as possible in early drug discovery, it's worth noting that some of this information is dubious and some is valuable; the problem is that often it's hard to say which information would be dubious and which would be valuable. One of the reasons medicinal chemists disagree on compound selection is because gut instincts and experience can sometimes overrule what may seem like cogent limits on properties like lipophilicity. Nonetheless, having medicinal chemists who are tuned by default to thinking about properties would be a good idea. 

The second caveat I would apply to approaches like this is to not discount the value of a classical synthetic organic chemistry education. As has been amply demonstrated, making a complex molecule over a long period of time is more about handling setbacks, persisting with grit and developing the kind of character that can handle repeated failures than about making the molecule per se. And god knows we need all these qualities in drug discovery, a field which is literally a glutton for attrition and failure. In addition, even today there are molecules which often stump the best efforts of standard synthetic routes. Thus, it's always a good idea to have a core group of accomplished synthetic chemists in any program. In one sense the argument is really about degree, it's about what the size of this core should be, and the article argues that maybe it should be smaller than what has been traditionally thought.

Rafferty's main prescription is that graduate programs training chemists for drug discovery should now focus less on synthesis and more on multiparameter optimization and on other disciplines which can be used to think about properties upfront. The industry should do likewise in deemphasizing training of synthetic organic chemistry and emphasizing broader training in medicinal chemistry during recruitment. When I was in graduate school I was fortunate to study under a world-class medicinal chemist. Not only did his group teach students to think about properties at a relatively early stage, but more in line with what this article says, he also created a very good drug discovery course which gave students a solid flavor of the process and emphasized the contributions of other disciplines like pharmacology, formulation, metabolic studies and molecular modeling. Rafferty is encouraging more graduate programs to include such courses, and I definitely agree with him on this. The second prescription he has is to create more industry-academic partnerships in which industry contributes personnel, scholarships and funding to expose students to actual drug discovery and not just synthesis. A scheme like this has been in place in Europe for some time now.

Wikipedia seems to have caught up with the times when it defines medicinal chemistry as a discipline which 

"In its most common practice —focusing on small organic molecules—encompasses synthetic organic chemistry and aspects of natural products and computational chemistry in close combination with chemical biology, enzymology and structural biology, together aiming at the discovery and development of new therapeutic agents. Practically speaking, it involves chemical aspects of identification, and then systematic, thorough synthetic alteration of new chemical entities to make them suitable for therapeutic use. It includes synthetic and computational aspects of the study of existing drugs and agents in development in relation to their bioactivities (biological activities and properties), i.e., understanding their structure-activity relationships (SAR)."

Perhaps academia and industry can embrace this definition more fully.

Image: Amriglobal

On AlphaGo, chemical synthesis and the rise of the intuition machines

There is a very interesting article by quantum computing and collaborative science pioneer Michael Nielsen in Quanta Magazine on the recent victory of Google’s program AlphaGo over the world’s reigning Go champion, Lee Sedol. In the article Nielsen tries to explain what makes this victory so special. Some people seem to think that Go is just a more complex version of chess, with more branching possibilities and solutions. And since Deep Blue beat Kasparov in 1997 and we have acquired far more computing power since then, this would simply be one more summit on that journey.

In the article Nielsen explains why this belief is incorrect. Go is very different from chess for many reasons. Not only are the number of solutions and branch points exponentially greater, but the winning features of Go are more nebulous are far more prone to intuition. The difference between a win for black over white in chess is clear – it’s when white’s king is checkmated. But the difference between a win for black over white in Go can be very subtle; it’s when black’s pieces surround white’s pieces better, and the definition of “surround” can be marginal. Unlike chess where you display all your pieces, in Go many of your pieces are held in reserve, so your opponent has to consider those pieces too when he or she makes a move. Unlike chess where even an amateur can recognize a winning board, a winning board in Go may be only slightly different from a losing board. In his book “On China”, Henry Kissinger says that China’s strategy is like Go’s whereas the West’s has been like chess’s. That’s something to think about.

However, the important thing here is that it’s precisely these complex features of Go that make it much more prone to subtle intuition: for a human Go player, recognizing a winning board over a losing board is as much a matter of intuition and feeling as it is of mechanistic rational analysis. It’s these features that make it far harder for a machine to defeat a Go champion than a chess champion. And yet two weeks back it did.

What made this victory possible? According to Nielsen, it was the fact that AlphaGo’s algorithm was actually trained to recognize human intuition. Its creators did this by training the program’s neural nets on thousands of past winning boards. These winning boards were human products; they were products of the intuition employed by human players. But the program did not need to understand intuition; it simply needed to learn it by looking at thousands of cases where that intuition worked successfully. AlphaGo’s creators further made the neural net play against itself and tweak its parameters until it achieved a successful result. Ultimately when the program was deployed, not only could it calculate a mind boggling number of winning boards, but it could also use elements of human intuition to say which ones looked good.

Nielsen thinks that it’s this ability to capture important elements of human intuition that marks AlphaGo’s victory as a new era in artificial intelligence. Human beings think that intuition is perhaps the most important thing that distinguishes them from machines. And yet if we think about intuition as pattern recognition and extrapolation gathered from evaluating thousands of past examples, there is no reason why a machine cannot learn how to intuit its way through a tough problem. In our case those countless examples have been ingrained by millions of years of neural and biological evolution; in case of machines we will provide it with those examples ourselves.

I thought of AlphaGo’s victory as I read Derek’s post on automating synthesis by having a smart algorithm work through all the intermediates, starting materials and potential branch points of a complex molecule’s synthesis. Derek thinks that it’s not too far in the future when such automated synthesis starts contributing significantly to the production of complex molecules like drugs and and other materials, and I tend to agree with him. People have been working on applying AI to synthesis since E J Corey’s LHASA program and Carl Djerassi’s work on AI in chemistry from the late 70s, and it does seem that we are getting close to what would be at least a moderately interesting tipping point in the field.

One of the commenters on Derek’s blog brought up the subject of AlphaGo’s latest win, and when I pointed out Nielsen’s article, had the following to say:

"These are my thoughts exactly. When we don’t understand chemical intuition people tend to think “Well, if we can’t understand it ourselves, how can we code it into a computer?” But what if the question is turned back onto you, “If YOU don’t understand chemical intuition, how did YOU learn it?” You learned it by looking at lots of reactions and drawing imperceptible parallels between disparate data points. This is neural net computing and, as you say, this is what allows AlphaGo to have “intuition” without that feature being encoded into its logic. The way these computers are now learning is no different than how humans learn, I think we just need to provide them with informational infrastructure that allows them to efficiently and precisely navigate through the data we’ve generated so far. With Go that’s simple, since the moves are easily translated to 1’s and 0’s. With chemistry it’s tougher, but certainly nowhere near impossible."

“Tougher, but not impossible” is exactly what I think about applying AI to automated chemical synthesis and planning. The fact is that we have accumulated enough synthetic data and wisdom over fifty years of brilliant synthetic feats to serve as a very comprehensive database for any algorithm wanting to use the kind of strategy that AlphaGo did. What I think should be further done is for developers of these algorithms to also train their program’s neural nets on past successful syntheses by chemists who were not just renowned for their knowledge but were known for the aesthetic sense which they brought to their syntheses. Foremost among these of course was the ‘Pope’, R B Woodward, who when he won the Nobel Prize was anointed by the Nobel committee as being a “good second” to Nature when it came to implementing notions of art, beauty and elegance in organic synthesis. Woodward’s syntheses were widely considered to be beautiful and spare, and his use of stereochemistry especially was unprecedented.

Fortunately, we also have a good guidebook to the use of elegance and aesthetics in organic synthesis: K C Nicolaou’s “Classics in Total Synthesis" series. My proposal would be for the developers to train their algorithms on such classics. For every branch point in a synthesis campaign there are several – sometimes thousands - of directions that are possible. Clearly people like Woodward picked certain directions over others, sometimes using perfectly rational principles but at other times using their sense of aesthetics. Together these rational approaches and aesthetic sense comprise what we can call intuition in synthesis. It would not be that hard to train a synthesis AI’s neural nets on capturing this intuition by constantly asking it to learn what option among the many possible were actually chosen in any good synthesis. That in turn would allow us to tweak the weights of the ‘neurons’ in the program’s neural nets, just like the creators of AlphaGo did. If repeated enough number of times, we would get to a stage when the program’s decision to follow one route over another are dictated not just by brute force computation of number of steps, availability of reagents, stereochemical complexity etc. but also simply by what expert human beings did in the past.

At this stage the algorithm would start capturing what we call intuitive elements in the synthesis of complex molecules. Any such program that cuts down synthetic planning and execution time by even 20% would have a very distinct advantage over the (non-existent?) competition. There is little doubt that not only would it be quickly adopted by industry and academia, but that its key functions would also be rapidly outsourced, just like software, car manufacturing and chemical synthesis are currently. This in turn would lead to a huge impact on jobs, STEM careers as well as the economy. The political fallout could be transformational.

All this could potentially come about by the application of training algorithms similar to AlphaGo’s to the construction of synthesis AI software. It would be wise for chemists to anticipate these developments instead of denying their inevitable onward march. We are still a long way from when a computer comes up with a synthetic route rivaling those of a Bob Woodward, an E J Corey or a Phil Baran. But as far as actual impact is concerned, the computer does not need to win that contest; it simply needs to be good enough. And that future seems closer than we think.

  

Darwin's "endless forms most beautiful" quote...applied to chemistry

“Thus, from the ashes of alchemy, from war and peace, the most exalted object which we are capable of conceiving, namely, the production of new molecules that never existed before, directly follows. 

There is grandeur in this view of matter, with its several properties, having been originally breathed into a few elements or into one; and that, whilst this planet has gone cycling on according to the fixed laws of thermodynamics, from so simple a beginning endless forms most beautiful and most wonderful have been, and are being, synthesized.”

Original quote.

Molecules, software and function: Why synthesis is no longer chemistry's outstanding problem.

R B Woodward and his followers have solved the general
problem of organic synthesis. We need to solve the general
problem of design and function.

Yesterday's post by Derek titled 'The End of Synthesis'  (follow up here) ruffled quite a few feathers. But I suspect one of the reasons it did so is because it actually hits too close to home for those who are steeped in the art and science of organic synthesis. The paper which the post talks about, by chemist Martin Burke in Science may or may not be the end of synthesis but it may well be the beginning of the end, at least symbolically. As much as it might be unpalatable to some, the truth is that synthesis is no longer chemistry’s outstanding general problem.

Synthesis was the great philosophical question of the twentieth century, not the twenty-first. As Derek pointed out, in the 50s it was actually not clear at all that a molecule like strychnine with its complex shape and stereochemistry could even be made. But now there is little doubt that given enough manpower (read graduate students and postdocs) and money, basically anything that you can sketch on paper can be made. Now I am certainly not claiming that synthesizing a complex natural product with fifty rotatable bonds and twenty chiral centers is even today a trivial task. There is a still a lot of challenge and beauty in the details. I am also not saying that synthesis will cease to be a fruitful source of solutions for humanity’s most pressing problems, such as disease or energy; as a tool the importance of synthesis will remain undiminished. What I am saying is that the general problem of synthesis has now been solved in an intellectual sense (as an aside, this would be consistent with the generally pessimistic outlook regarding total synthesis seen on many blogs, including Derek's.). And since the general problem has been solved it's not too audacious to think that it might lend itself to automation. Once you have a set of formulas for making a molecule, it is not too hard to imagine that machines might be able to bring about specific instantiations of those formulas, even if you will undoubtedly have to work out the glitches along the way.

I always think of software when I think about the current state of synthesis. When software was being developed in the 40s and 50s it took the ingenuity of a John von Neumann or a Grace Hopper to figure out how to encode a set of instructions in the form of a protocol that a machine could understand and implement. But what it took von Neumann to do in the 50s, it takes a moderately intelligent coder from India or China to do in 2014. Just as the massive outsourcing of software was a good example of software's ability to be commoditized and automated, so is the outsourcing of large swathes of organic synthesis a telling sign of its future in automation. Unlike software synthesis is not quite there yet, but given the kind of complexity that it can create on demand, it will soon be.

To see how we have gotten here it's worth taking a look at the history, and this history contains more than a nugget of comparison between synthesis and computer science. In the 1930s the general problem was unsolved. It was also unsolved in the 50s. Then Robert Burns Woodward came along. Woodward was a wizard who made molecules whose construction had previously defied belief. He had predecessors, of course, but it was Woodward who solved the general problem by proving that one could apply well-known principles of physical organic chemistry, conformational analysis and stereochemical control to essentially synthesize any molecule. He provided the definitive proof of principle. All that was needed after that was enough time, effort and manpower. Woodward was followed by others like Corey, Evans, Stork and now Phil Baran, and all of them demonstrated the facile nature of the general problem.

If chemistry were computer science, then Woodward could be said to have created a version of the Turing Machine, a general formula that could allow you to synthesize the structure of any complex molecule, as long as you had enough NIH funding and cheap postdocs to fill in the specific gaps. Every synthetic chemist who came after Woodward has really developed his or her own special versions of Woodward’s recipe. They might have built new models of cars, but their Ferraris, Porches and Bentleys – as elegant and impressive as they are – are a logical extension of Woodward and his predecessor’s invention of the internal combustion engine and the assembly line. And it is this Turing Machine-like nature of synthetic schemes that lend them first to commoditization, and then to automation. The human component is still important and will always be but the proportion of that creative human contribution is definitely changing.

A measure of how the general problem of synthesis has been solved is readily apparent to me in my own small biotech company which specializes in cyclic peptides, macrocycles and other complex bioactive molecules. The company has a vibrant internship program for undergraduates in the area. To me the most remarkable thing is to see how quickly the interns can bring themselves up to speed on the synthetic protocols. Within a month or so of starting at the bench they start churning out these compounds with the same expertise and efficiency as chemists with PhDs. The point is, synthesizing a 16-membered ring with five stereocenters has not only become a routine, high-throughput task but it’s something that can be picked up by a beginner in a month. This kind of synthesis might have easily fazed a graduate student in Woodward's group twenty years ago and taken up a good part of his or her PhD project. The bottom line is that we chemists have to now face an uncomfortable fact: there are still a lot of unexpected gems to be found in synthesis, but the general problem is now solved and the incarnation of chemical synthesis as a tool for other disciplines is now essentially complete.

Functional design and energetics are now chemistry’s outstanding general problems

So if synthesis is no longer the general problem, what is? George Whitesides has held forth on this question in quite a few insightful articles, and my own field of medicinal chemistry and molecular modeling provides a good example. It may be easy to synthesize a highly complex drug molecule using routine techniques, but it is impossible, even now, to calculate the free energy of binding of an arbitrary simple small molecule with an arbitrary protein. There is simply no general formula, no Turing Machine, that can do this. There are of course specific cases where the problem can be solved, but the general solution seems light years away. And not only is the problem unsolved in practice but it is also unsolved in principle. It's not a question of manpower and resources, it's a question of basic understanding. Sure, we modelers have been saying for over twenty years that we have not been able to calculate entropy or not been able to account for tightly bound water molecules. But these are mostly convenient questions which when enunciated make us feel more emotionally satisfied. There have certainly been some impressive strides in addressing each of these and other problems, but the fact is that when it comes to calculating the free energy of binding, we are still today where we were in 1983. So yes, the calculation of free energies – for any system – is certainly a general problem that chemists should focus on.

But here’s the even bigger challenge that I really want to talk about: We chemists have been phenomenal in being able to design structure, but we have done a pretty poor job in designing function. We have of course determined the function of thousands of industrial and biological compounds, but we are still groping in the dark when it comes to designing function. An example from software would be designing an emergency system for a hospital: there the real problem is not writing the code but interfacing the code with the several human, economic and social factors that make the system successful. 

Here are a few examples from chemistry: Through combinatorial techniques we can now synthesize antibodies that we want to bind to a specific virus or molecule, but the very fact that we have to adopt a combinatorial, brute force approach means that we still can’t start from scratch and design a single antibody with the required function (incidentally this problem subsumes the problem of calculating the free energy of antigen-antibody binding). Or consider solar cells. Solid-state and inorganic chemists have developed an impressive array of methods to synthesize and characterize various materials that could serve as more efficient solar materials. But it’s still very hard to lay out the design principles – in general terms – for a solar material with specified properties. In fact I would say that the ability to rapidly make molecules has even hampered the ability to think through general design principles. Who wants to go to the trouble of designing a specific case when you can simply try out all combinations by brute force?

I am not taking anything away from the ingenuity of chemists – nor am I refuting the belief that you do whatever it takes to solve the problem – but I do think that in their zeal to perfect the art of synthesis chemists have neglected the art of de novo design. Yet another example is self-assembly, a phenomenon which operates in everything from detergent action to the origin of life. Today we can study the self-assembly of diverse organic and inorganic materials under a variety of conditions, but we still haven’t figured out the rules – either computational or experimental – that would allow us to specific the forces between multiple interacting partners so that these partners assembly in the desired geometry when brought together in a test tube. Ideally what we want is the ability to come up with a list of parts and the precise relationships between them that would allow us to predict the end product in terms of function. This would be akin to what an architect does when he puts together a list of parts that allows him to not only predict the structure of a building but also the interplay of air and sunlight in it.

I don’t know what we can do to solve this general problem of design but there are certainly a few promising avenues. A better understanding of theory is certainly one of them. The fact is that when it comes to estimating intermolecular interactions, the theories of statistical thermodynamics and quantum mechanics do provide – in principle – a complete framework. Unfortunately these theories are usually too computationally expensive to apply to the vast majority of situations, but we can still make progress if we understand what approximations work for what kind of systems. Psychologically I do think that there has to be a general push away from synthesis and toward understanding function in a broad sense. Synthesis still rules chemical science and for good reason; it's what makes chemistry unique among the sciences. But that also often makes synthetic chemists immune to the (well deserved) charms of conformation, supramolecular interactions and biology. It’s only when synthetic chemists seamlessly integrate themselves into the end stages of their day job that they will learn better to appreciate synthesis as an opportunity to distill general design principles. Part of this solution will also be cultural: organic synthesis has long enjoyed a cultish status which still endures. 

However the anguish should not obscure the opportunity here. The solution of the general problem of synthesis and its possible automation should not leave chemists chagrined since it's really a tribute to the amazing success that organic synthesis has engendered in the last thirty years. Instead of reinventing ourselves as synthetic chemists let's retool. Let the synthetic chemist interact with the physical biochemist, the structural engineer, the photonics expert; let him or her see synthesis through the requirement of function rather than structure. The synthesis is there, the other features are not. Whitesides was right when he said that chemists need to broaden out, but another way to interpret his statement would be to ask other scientists to channel their thoughts into synthesis in a feedback process. As chemists we have nailed structure, but nailing design will bring us untold dividends and will enormously enhance the contribution of chemistry to our world. 

Adapted from a previous post on Scientific American Blogs.

Chemical and Engineering News celebrates 90 years: How chemistry has come a long way

Chemistry is - in the true sense - the central science, reaching inside every aspect of our lives (Image: Marquette University)

Chemical and Engineering News (C&EN) is celebrating 90 years of its existence this year, and I can only imagine how perplexed and awestruck its editors from 1923 would have been had they witnessed the state of pure and applied chemistry in 2013. I still remember devouring the articles published in the magazine during its 75th anniversary, and this anniversary also offers some tasty perspectives on a diverse smattering of topics; catalysis, structural biology and computational chemistry to name a few. 

There's an article in the magazine documenting how the single-most important concept in chemistry - that of the chemical bond - has undergone a transformation; from fuzzy, to rigorously defined, to fuzzy again (although in a very different sense).

Nobel Laureate Roald Hoffmann had something characteristically insightful to say about The Bond:

"My advice is this: Push the concept to its limits. Be aware of the different experimental and theoretical measures out there. Accept that at the limits a bond will be a bond by some criteria, maybe not others. Respect chemical tradition, relax, and instead of wringing your hands about how terrible it is that this concept cannot be unambiguously defined, have fun with the fuzzy richness of the idea.”

In a bigger sense the change in chemistry during these 90 years has been no less than astounding. In 1923 the chemical industry already made up the foundations of a great deal of daily life, but there was little understanding of how to use the concepts and products of chemical science in a rational manner. Since 1923 our knowledge of both the most important aspect of pure chemistry (the chemical bond) and of applied chemistry (synthesis) has grown beyond the wildest dreams of chemistry's founders.

If we had to pinpoint two developments in chemistry during these 90 years that would truly be described as "paradigm shifts", they would be the theoretical understanding of bonding and the revolution in instrumental analysis. As I and others have argued before, chemistry unlike physics is more "Galisonian" than "Kuhnian", relying as much on new instrumental techniques as on conceptual leaps for its signal achievements.

The two most important experimental advances in chemistry - x-ray diffraction and nuclear magnetic resonance - both came from physics, but it was chemists who honed these concepts into a routine laboratory tool for the structure determination of a staggeringly diverse array of substances, from table salt to theribosome. The impact of these two developments on chemistry, biology, medicine and materials science cannot be underestimated; they cut down the painstaking task of molecular structure determination from months to hours, they allowed us to find out the nature of novel drugs, plastics and textiles and they are now used by every graduate student every single day to probe the structure of matter and synthesize new forms of it. Other developments like infrared spectroscopy, electron diffraction, atomic force microscopy and single molecule spectroscopy are taking chemistry in novel directions.

The most important theoretical development in chemistry also derived from physics, but its progress against demonstrates chemists' central role in acting as mediators between concept and application. It also serves to make a key point about reductionism and the drawbacks of trying to reduce chemistry to physics. The chemical bond is an abstract concept going back to "affinities" between atoms (which when illustrated were replete with hooks and eyes). But it was in 1923 that the great American chemist G. N. Lewis propounded the idea in terms of atoms sharing electrons. This was a revolutionary brainwave and illuminated the way for Linus Pauling, John Slater, Robert Mulliken, John Pople and others to use the newly developed machinery of quantum mechanics to fashion the qualitative principle into an accurate, quantitative tool which  - with the development of modern computing - now allows chemists to routinely calculate and predict important properties for any number of chemical substances.

Yet the ramifications of the chemical bond tempt and beguile physicists and constantly escape from their grasp when they try to define them too accurately. The above quote by Roald Hoffmann puts the problem in perspective; quintessentially chemical ideas like aromaticity, the hydrophobic effect, steric effects and polarity "fray at the edges" (in Hoffmann's words) when you try to push them to their limits and try to define them in terms of subatomic physics. Chemistry is a great example of an emergent discipline. It is derived from physics and yet independent of it, relying on fundamental definitions at its own level when progressing.

The chemical bond and other theoretical aspects of chemistry have enabled the rise of the one activity pursued by chemists of which society is an unsurpassed beneficiary - the science, art and commerce of synthesis. Every single molecule that bathes, clothes, feeds, warms, transports and heals us has been either derived from nature using chemical techniques or has been synthetically made in a chemical laboratory. The social impact of these substances is hard to underestimate; even a sampling of a few such as the contraceptive pill, antibiotics or nylon attests to the awesome power of chemistry to completely transform our lives.

In 1923 synthesis was a haphazard process and there was virtually no understanding of how we could do it rationally. All of this changed in the 1950s and 60s when a group of pioneering scientists led by the legendary organic chemist Robert Burns Woodward revolutionized the process and honed synthesis into a precisely rational science which took advantage of the course of chemical reactions, the alignment of orbitals, the development of new chemical reagents and the three-dimensional shape of molecules. Many Nobel Prizes were handed out for these groundbreaking discoveries, but none surpassed the sheer impact that synthesis will continue to have on our way of life.

As is inevitably the case for our embrace of science and technology, with progress also come problems, and chemists have had to deal with their share of issues like environmental pollution, drug side effects and the public perception of chemistry. Suffice it to say that most chemists are well aware of these and are working hard to address them. They recognize that with knowledge comes responsibility, and the responsibility they bear to mitigate the ills of the wrongful application of their science transcends their narrow professional interests and encompasses their duties as citizens.

In the new century chemistry continues to build upon its past and chemists continue to push its boundaries. Another change which the editors of C&EN would not have foreseen in 1923 is the complete integration of chemistry into other disciplines like biology, medicine and engineering and its coming into its own as the true "central science". Today chemistry deeply reaches into every single aspect of our lives. The cardinal problems facing civilization - clean and abundant food and water, healthcare, national security, overpopulation, poverty, climate change and energy - cannot be solved without a knowledge of chemistry. Simply put, a world without chemistry would be a world which we cannot imagine, and we should all welcome and integrate the growth of chemical science into our material and moral worldview.

First published on the Scientific American Blog Network.

On synthesis, design and chemistry's outstanding philosophical problems

Chemists need to move from designing structure - exemplified by this synthetic receptor - to designing function (Image: Max Planck Institute).

Yesterday I wrote a post about a perspective by multifaceted chemist George Whitesides in which he urged chemists to broaden the boundaries of their discipline and think of big picture problems. But the article spurred me to think a bit more about a question which I (and I am sure other chemists) have often thought about; what’s the next big challenge for chemistry?

And when I ask this question I am not necessarily thinking of specific fields like energy or biotechnology or food production. Rather, I am thinking of the next outstanding philosophical question confronting chemistry. By philosophical question I don’t mean an abstract goal which only armchair thinkers worry about. The philosophical questions in a field are those which define the field’s big problems in the most general sense of the term. For physicists it might be understanding the origin of the universe, for biologists the origin of life. These problems can also be narrowly defined questions that nonetheless expand the understanding and scope of a field; for instance in the early twentieth century physicists were struggling to make sense of atomic spectra, which turned out to be important for the development of quantum theory. It’s also important to note that the philosophical problems of a field change over time, and this is one reason why chemists should be aware of them; you want to move with the times. If you were a “chemist” in the sixteenth century the big question was transmutation. In the nineteenth century when chemistry finally was cast in the language of elements and molecules the big question became theconstitution of molecules in the form of atomic arrangements.

Synthesis is no longer chemistry’s outstanding general problem

When I think about the next philosophical question confronting chemistry I also feel a sense of despondency. That’s because I increasingly feel that the great philosophical question that chemists are going to face in the near future is emphatically not one whose answer they will locate in the all-pervasive activity that always made chemistry unique: synthesis. What always set chemistry apart was its ability to make new molecules that never existed before. Through this activity chemistry has played a central role in improving our quality of life.

The point is, synthesis was the great philosophical question of the twentieth century, not the twenty-first. Now I am certainly not claiming that synthesizing a complex natural product with fifty rotatable bonds and twenty chiral centers is even today a trivial task. I am also not saying that synthesis will cease to be a fruitful source of solutions for humanity’s most pressing problems, such as disease or energy; as a tool the importance of synthesis will remain undiminished. What I am saying is that the general problem of synthesis has now been solved in an intellectual sense (as an aside, this would be consistent with the generally pessimistic outlook regarding total synthesis seen on many blogs.)

The general problem of synthesis was unsolved in the 30s. It was also unsolved in the 50s. Then Robert Burns Woodward came along. Woodward was a wizard who made molecules whose construction had defied belief. He had predecessors, of course, but it was Woodward who solved the general problem by proving that one could apply well-known principles of physical organic chemistry, conformational analysis and spectroscopy to essentially synthesize any molecule. He provided the definitive proof of principle. All that was needed after that was enough time, effort and manpower. If chemistry were computer science, then Woodward could be said to have created a version of the Turing Machine, a general formula that could allow you to synthesize the structure of any complex molecule, as long as you had enough NIH funding and cheap postdocs to fill in the specific gaps. Every synthetic chemist who came after Woodward has really developed his or her own special versions of Woodward’s recipe. They might have built new models of cars, but their Ferraris, Porches and Bentleys – as elegant and impressive as they are – are a logical extension of Woodward and his predecessor’s invention of the internal combustion engine and the assembly line.

A measure of how the general problem of synthesis has been solved is readily apparent to me in my own small biotech company which specializes in cyclic peptides, macrocycles and other complex bioactive molecules. The company has a vibrant internship program for undergraduates in the area. To me the most remarkable thing is to see how quickly the interns can bring themselves up to speed on the synthetic protocols. Within a month or so of starting at the bench they start churning out these compounds with the same expertise and efficiency as chemists with PhDs. The point is, synthesizing a 16-membered ring with five stereocenters has not only become a routine, high-throughput task but it’s something that can be picked up by a beginner in a month. This kind of synthesis might have easily fazed a graduate student twenty years ago and taken up a good part of his or her PhD project. The bottom line is that we chemists have to now face an uncomfortable fact: there are still a lot of unexpected gems to be found in synthesis, but the general problem is now solved and the incarnation of chemical synthesis as a tool for other disciplines is now essentially complete.

Functional design and energetics are now chemistry’s outstanding general problems

So if synthesis is no longer the general problem, what is? My own field of medicinal chemistry and molecular modeling provides a good example. It may be easy to synthesize a highly complex drug molecule using routine techniques, but it is impossible, even now, to calculate the free energy of binding of an arbitrary simple small molecule with an arbitrary protein. There is simply no general formula, no Turing Machine that can do this. There are of course specific cases where the problem can be solved, but the general solution seems light years away. And not only is the problem unsolved in practice but it is also unsolved in principle. Sure, we modelers have been saying for over twenty years that we have not been able to calculate entropy or not been able to account for tightly bound water molecules. But these are mostly convenient questions which when enunciated make us feel more emotionally satisfied. There have certainly been some impressive strides in addressing each of these and other problems, but the fact is that when it comes to calculating the free energy of binding, we are still today where we were in 1983. So yes, the calculation of free energies – for any system – is certainly a general problem that chemists should focus on.

But here’s the even bigger challenge that I really want to talk about: We chemists have been phenomenal in being able to design structure, but we have done a pretty poor job in designing function. We have of course determined the function of thousands of industrial and biological compounds, but we are still groping in the dark when it comes to designing function. Here are a few examples: Through combinatorial techniques we can now synthesize antibodies that we want to bind to a specific virus or molecule, but the very fact that we have to adopt a combinatorial, brute force approach means that we still can’t start from scratch and design a single antibody with the required function (incidentally this problem subsumes the problem of calculating the free energy of antigen-antibody binding). Or consider solar cells. Solid-state and inorganic chemists have developed an impressive array of methods to synthesize and characterize various materials that could serve as more efficient solar materials. But it’s still very hard to lay out the design principles – in general terms – for a solar material with specified properties. In fact I would say that the ability to rapidly make molecules has even hampered the ability to think through general design principles. Who wants to go to the trouble of designing a specific case when you can simply try out all combinations by brute force?

I am not taking anything away from the ingenuity of chemists – nor am I refuting the belief that you do whatever it takes to solve the problem – but I do think that in their zeal to perfect the art of synthesis chemists have neglected the art of de novo design. Yet another example is self-assembly, a phenomenon which operates in everything from detergent action to the origin of life. Today we can study the self-assembly of diverse organic and inorganic materials under a variety of conditions, but we still haven’t figured out the rules – either computational or experimental – that would allow us to specific the forces between multiple interacting partners so that these partners assembly in the desired geometry when brought together in a test tube. Ideally what we want is the ability to come up with a list of parts and the precise relationships between them that would allow us to predict the end product in terms of function. This would be akin to what an architect does when he puts together a list of parts that allows him to not only predict the structure of a building but also the interplay of air and sunlight in it.

I don’t know what we can do to solve this general problem of design but there are certainly a few promising avenues. A better understanding of theory is certainly one of them. The fact is that when it comes to estimating intermolecular interactions, the theories of statistical thermodynamics and quantum mechanics do provide – in principle – a complete framework. Unfortunately these theories are usually too computationally expensive to apply to the vast majority of situations, but we can still make progress if we understand what approximations work for what kind of systems. Psychologically I do think that there has to be a general push away from synthesis and toward understanding function in a broad sense. Synthesis still rules chemical science and for good reason; it's what makes chemistry unique among the sciences. But that also often makes synthetic chemists immune to the (well deserved) charms of conformation, supramolecular interactions and biology. It’s only when synthetic chemists seamlessly integrate themselves into the end stages of their day job that they will learn better to appreciate synthesis as an opportunity to distill general design principles. Let the synthetic chemist interact with the physical biochemist, the structural engineer, the photonics expert; let him or her see synthesis through the requirement of function rather than structure. Whitesides was right when he said that chemists need to broaden out, but another way to interpret his statement would be to ask other scientists to channel their thoughts into synthesis in a feedback process. As chemists we have nailed structure, but nailing design will bring us untold dividends and will help make the world a better place.

First published on the Scientific American Blog Network.