Why should chemists study the origin of life?

In the past we have alluded to the fact that the origin of life (OOL) is a quintessentially chemical problem. But from a professional standpoint, what's in it for chemists and why should they care? Some thoughts:

1. OOL is the ultimate interdisciplinary playing field: No matter what kind of chemist you are, OOL provides an opportunity for you to flex your intellectual muscles. Organic chemists can of course contribute directly to OOL research by speculating on and studying the kinds of reactions that would have been important in molecular origins. Some reactions such as the Strecker reaction (for amino acid synthesis) and the formose reaction (for carbohydrate synthesis) have already been proposed as the frontrunners for the genesis of life's molecules. Both reactions have been around for decades, but it was only recently that the concrete connection to OOL was made. What other reactions in the organic chemist's bag of tricks are applicable to OOL? The question should tickle organic chemists' brain cells like no other.

Other kinds of chemists also have a lot of potential contributions to make. The connection to biochemistry is obvious; for instance, how did the crucial watershed event of membrane formation come about and how did the earliest enzymes form? Inorganic chemists have made new inroads into OOL research, especially through pioneering research implicating metal sulfides in deep sea hydrothermal vents as precursors to organic life and inorganic surfaces (such as clays) as templates for primitive evolution and polymerization. Analytical chemists can bring their impressive phalanx of instrumentation like mass spectrometry and chromatography to bear on the problem. And theoretical and computational chemists can contribute to OOL by performing calculations on the forces operating in the processes of self-assembly that must have been key during the early moments of molecular organization. Of course, none of these areas is insular and every problem stated above demands the attention of every conceivable kind of chemist. Thus, there is a slice of pie in OOL for every chemist who dares to dream and the field guarantees an unlimited number of interdisciplinary collaborations.

2. OOL is a proving ground for basic chemical concepts: Just like organic synthesis is supposed to provide the ultimate training laboratory for fundamentals like spectroscopy, mechanism, and physical organic chemistry, OOL provides an opportunity to review and probe every basic chemical concept we can imagine in every chemical field. For instance, why are the pKa values of amino acids what they are? What would happen if they are different? Or the famous question; why did nature choose phosphates, a question which leads us to basic discussions of nucleophilicity, pKa, steric effects, thermodynamics, kinetics, atomic sizes and myriad other fundamental concepts. Other questions may include: Why alpha amino acids? Why ribose? Why these twenty amino acids and not others? We will never know the ultimate answers to these questions (since there was a fair element of chance involved), but simply asking them forces us to re-evaluate fundamental concepts of chemistry, an exercise that can be enormously rewarding and informative. OOL has involved fundamental research on chirality, self-assembly (more on this in the next point) and free energy calculation. This leads us from not knowing anything to fine-tuning our understanding and knowing something. As a side-benefit, then when there are some fanciful-sounding announcements, we can count on this knowledge to provide answers and level informed criticism.

3. OOL forces us to understand self-assembly: From a practical standpoint this may be the greatest benefit of OOL research. Self-assembly is undoubtedly the single-most important process in life's beginnings, and it also turns out to be of paramount importance in understanding everything else, from how Alzheimer's disease proteins fold to how surfactants sequester dirt to how we can construct supramolecular architectures for solar energy research. The workhorse in self-assembly is our cherished friend the hydrogen bond. Understanding the hydrogen bond thus opens the door to understanding self-assembly. In the past few years we have gained extremely valuable insights into hydrogen bonding, partly obtained through OOL research. For instance, studies of hydrogen bonding in DNA base pairing has revealed the subtle interplay between thermodynamics and electrostatics that stabilizes nucleic acids. Similar effects naturally operate in protein folding. The knowledge gained from such studies can help in the design of everything from novel proteins to supramolecular arrays. The same kind of self-assembly leads to insights into OOL questions addressing fundamental issues such as the formation of the first cell. The practical applications of self-assembly and OOL are thus two ends of a cycle which feed into each other, contributing and utilizing important insights that would fuel both basic and applied research. Understand self-assembly and you will not only inch closer to understanding origins but will also be able to harvest knowledge from the field toward practical ends.

4. OOL is the ultimate open-ended problem: Technically most problems in science are open-ended, but OOL is literally a problem without end. There is no conceivable way in which we will hit on the single, unique solution that jump-started life at a molecular level. We can inch tantalizingly closer to the plausible, but there is still a gigantic leap between the plausible and the certain. Should we despair? Absolutely not. If science can be defined as the "endless frontier", then OOL is the poster child for this definition. OOL will promise us an unending string of questions and plausible explanations until the end of the human species. This will bring us a proliferation of riches in basic chemical understanding. As scientists in general and chemists in particular, we should be ecstatic that OOL has given us a perpetual question machine to do research, discuss, debate and do more research. OOL like few other questions in science promises an infinitude of moments for reveling in the pleasure of finding things out.

And ultimately of course, OOL will help us take one more modest step in answering the question which human beings have asked since eternity- "Where do we come from?"

What more could we want?

Probing amyloid, one oligomer at a time

One of the more important paradigm shifts in our understanding of the Alzheimer’s disease-causing amyloid protein in the last few years has been the recognition of differences between the well known polymer aggregates of amyloid and their smaller, soluble oligomer counterparts. For a long time it was believed that the fully formed 40-42 amino acid protein aggregate found in autopsies was the causative agent in AD, or at least the most toxic one. This understanding has radically changed in the last few years, partly through elegant work done in identifying oligomers and partly through the unfortunate results of clinical trials targeting amyloid. The new understanding is that it’s not the fully formed aggregates but the smaller oligomers that are the real toxic species.

Identifying these different monomers, dimers, trimers and tetramers is a valuable goal. But until now their recognition has mainly depended on raising specific antibodies against them, a tedious and expensive process. Small molecule probes that specifically identify each oligomer have been missing. In a recent JACS communication, a team from the University of Michigan uses a simple but clever technique to develop such probes and makes a promising step in this direction.

The probes are based on the idea that the best antidote against a poison is another poison. In this case the poison is the specific sequence of amino acids that makes up amyloid. In particular, a sequence of five amino acids- KLVFF- has been found to be sufficient for aggregation and toxicity. The aggregates form by the stacking of beta sheets principally driven by hydrophobic interaction between the FF residues; each pair thus serves as a growth site for addition of further such residues. The insight then is that if one could construct a mimic of the sequence, this mimic would basically act as a competitive inhibitor and bind to the normal sequence, inhibiting further growth. In this case the strategy was to use KLVFF segments themselves which would sort of wrap around newly formed oligomers of different constitution and sequester them from further self-assembly. So the team essentially constructed two KLVFF segments joined by a linker. The linker would also serve the purpose of providing an entropic advantage to the two segments so that they would not be at an energetic disadvantage during binding. The important question was how long the linker should be.

To decide on the length of the linker the team made some clever use of molecular dynamics simulations. Since you can estimate the approximate thickness of every oligomer, you can estimate the linker length that would be required to keep two KLVFF segments at the same distance as the thickness of the oligomer. For instance, the distances between the segments needed to wrap around the oligomers were 14-15 A for the dimer, 19-20 A for the trimer and 24-25 A for the tetramer.



But the linker should also keep the segments stable at that distance. To probe this the team used MD simulations. The MD simulations revealed the length of the linker required to keep the two segments separated at the specific distances by indicating how much time the assembly spent at those distances.

To test these results, the team then generated mixtures of different kinds of KLVFF oligomers and then added each probe to the solution. A streptavidin moiety was attached to every probe. Silver staining revealed that each probe was specifically binding to an oligomer of a certain type dictated by the compatibility of the intraprobe distance and oligomer thickness. Trimers and tetramers could be clearly identified but there was more ambiguity in case of dimers, presumably because of their less ordered structure.

Most interestingly, the team then added the probes to cerebrospinal fluid (CSF). Since amyloid is part of normal physiology, it is present in CSF. Gratifyingly they found that the probes could very clearly label trimers and tetramers against a background of several other proteins and intermediates in CSF. This experiment notably demonstrates that the method can selectively detect amyloid oligomers in complex mixtures.

I think that this work is valuable and paves the way toward the development of similar small-molecule based probes for identifying the key intermediates in amyloid formation. It could also be very useful in exploring amyloid formation in normal physiology and in exploring the stages of protein self-assembly in diverse amyloid-based diseases.

Reinke, A., Ung, P., Quintero, J., Carlson, H., & Gestwicki, J. (2010). Chemical Probes That Selectively Recognize the Earliest Aβ Oligomers in Complex Mixtures Journal of the American Chemical Society DOI: 10.1021/ja106291e

Curbing the combinatorial catch

The 'combinatorial explosion' problem generally refers to the difficulty of locating a unique solution to a given problem when the potential space of solutions to be searched is astronomically large. It is found in many areas of science but most notably in protein folding where it takes the name of "Levinthal's Paradox". Biochemist Cyrus Levinthal pointed out in the 60s that if a given sequence of amino acids were to explore every possible conformation for each of its amino acids, even a small protein of 100 amino acid residues or so would take a time longer than the age of the universe to find the correct folded structure.

The paradox is clearly not a paradox since nature has solved the problem of protein folding countless number of times since life began on this planet (this is the protein-centric version of the anthropic principle). Thus, the combinatorial 'problem' is not a problem so far as we know that a robust and tried-and-tested solution exists and in fact has been used by nature to stunning effect. The problem is really to figure out the devilish details of this solution. In the past 30 years or so scientists have employed a battery of experimental and theoretical techniques to tackle the issue. Many important insights have revealed that understanding the factors that dictate the self-assembly of proteins can lead to great insights into the problem. Probably the foremost among these factors is the hydrophobic effect, which productively buries greasy chemical functionalities in the interior of proteins utilizing the multiple driving engines of favorable desolvation, entropic expulsion of water and weak packing-induced interactions. Other important factors ubiquitously used by nature include hydrogen bonds and salt bridges.

The key insight in tackling the problem has been to realize that protein folding or protein-protein interactions or indeed, all the myriad biomolecular interactions that occur in the cellular milieu, do not arise 'by chance'. Once we get past this stumbling block, things make a lot of sense. Chance events undoubtedly keep on happening, but nature preferentially preserves the consequences of certain events. Thus, similar motifs which have been successfully used for certain proteins are used for others. Nature does not need to keep on searching all of conformational space again and again for generating new structures. The analogy would be in designing a new house based on existing structures like bricks, arches and beams rather than designing it from scratch. A Victorian Englishman coined a word for this process of preservation of favorable elements leading to new biological entities a hundred and fifty years ago- natural selection. Thus, the protein folding problem can be immediately demystified when one realizes that natural selection keeps on using recurring motifs to build new structures. Far from being a chance event, the complexity of life can be explained by the re-use of pre-existing structures to build complexity. It may seem highly improbable and miraculous, but Darwin's genius was to provide a mechanism for precisely explaining this illusion of 'design', both on macro and molecular scales. It no longer seems improbable, but instead offers us a tool of incomparable power to peek into the heart of complex biological phenomena.

From a chemist's point of view, natural selection at the molecular level takes the form of the preservation of low-energy conformations of biomolecules that may possess other qualities such as stability, catalytic proficiency and rapid replication. Such chemical entities (think 'DNA') will persist and proliferate and they will be used in multiple designs. Consider coiled-coil structures with their typical seven-residue amino acid motifs or the catalytic triad that cleaves peptide bonds in proteases. Or think of something that's bleedingly simple- the phosphate group which, by virtue of its remarkable qualities of 'transient stability' to hydrolysis, proves to be the perfect connection for life's lego pieces. Once nature hit upon such designs, they could be easily employed in many different structures, dramatically reducing the amount of functional space to be searched. From a chemical perspective, the key property of these favored motifs is self-assembly which is driven by many well-understood physicochemical factors such as the aforementioned hydrophobic effect. Self-assembly, surely one of the greatest inventions of the laws of physics and chemistry, took the problem of the origin of life from miraculous impossibility to tantalizing possibility.

If nature can use pre-existing functionalities to solve the protein folding problem, why can't we do the same? Indeed, many theoretical approaches to protein folding have adopted this kind of approach. Probably the foremost algorithm for predicting protein folding today is a suite of programs called Rosetta which was originally developed by David Baker's group at the University of Washington. In a competition to predict protein structures in 2001, the program did so well that it was compared by a very famous computational chemist named Peter Kollman to Babe Ruth's world record, when even the second-best competitor was woefully lagging behind.

In the next post we will take a look at this program and why it works so successfully.