(Ir)rational drug design and the history of 20th century science

Here is an excellent overview of the hopes and foibles of "rational" drug design by Brooke Magnanti (Hat tip: Pete Kenny) which touches on several themes and names that would be familiar to those in the field: Ant Nicholls and OpenEye, Dave Weininger and Daylight fingerprints, Barry Werth's "The Billion Dollar Molecule" and Vertex, the inflated hopes of structure-based design, cheminformatics and screening etc. 

Those who are heroic survivors of that period would probably start with looking back with dewey eyes, followed by groans of disappointment. The bottom line in that article and several similar ones is that rational drug design and all that it entails (crystallography and molecular modeling in particular) has clearly not lived up to the hype. It's also clear that the swashbuckling scientists portrayed by Werth in his book for instance were more brilliant than successful. It's a tape of hope and woe that has played before, over and over again in fact.

It's clear that much of the faith in rational drug design until now has had a healthy component of irrational exuberance to it. Looking back at the inflated expectations of the 1980s and early 90s for designing drugs atom by atom, followed by the disappointing failures and massive attrition which rapidly succeeded these expectations, makes me wonder what it was exactly that got everyone into trouble. There was a constellation of factors of course, but the historian of science in me thinks that a major part of at least the psychological (and by extension, organizational) aspects of the issue have to deal with the stupendous successes of twentieth century science in generating a mountain of optimism which skeptics are still trying to chip away at.

It's quite clear that as far as scientific progress goes, the 20th century was the mother of all centuries. Very significant scientific advances (Newton, Maxwell, Darwin, Mendel) had undoubtedly occurred in earlier times, but the sheer rate at which science advanced in the last one hundred years far outstripped scientific progress in all previous centuries. Just consider the roster of both idea-based and tool-based scientific revolutions that we witnessed in the past century: x-rays, the atomic nucleus, relativity, quantum mechanics, nuclear fission, the laws of heredity, the structure of biomolecules, particle physics, lasers, computers, organic synthesis, gene editing...and we are just getting warmed up here.

By the 1980s this amazing collection of scientific gems had reached a crescendo, especially in the biomedical sciences. The rise of recombinant DNA technology, protein structure determination, and improved hardware, software and visualization virtually ensured that scientists started feeling very good indeed about designing drugs to block particular proteins at the molecular level. Philosophically too they were highly primed by the astounding reductionist successes of the past one hundred years. After all reductionism had uncovered the cosmic microwave background radiation from the Big Bang, given us the structure of elemental life proteins like hemoglobin and the photosynthetic complex, split the atom, doubled the number of transistors on a chip in eighteen months and taught us how to copy and paste genes. Designing drugs would be a natural extension, if not a job for graduate students, after all this success.

But what happened instead was that both scientifically and philosophically we ran into a wall. What we found out scientifically was that we still understand only a fraction of the complexity of biological systems that we need to for perturbing them with the fine scalpels of small organic molecules. Philosophically we found out that biological systems are emergent and contingent, so all the reductionist success of the past century is still not enough to understand them. In fact beyond a certain point reductionism would fundamentally put us on the wrong track. The past hundred years made us believers in Moore's Law, but what we got instead was Eroom's Law. Moore's Law is what reduces my running time from 12 mins/mile to 8:30 mins/mile in a year. Eroom's Law is what keeps it from reducing much further. Exponential technological success is not axiomatic and self-fulfilling.

I thus see a very strong influence of the success of twentieth century science in steering the wildly optimistic hopes of drug discovery scientists beginning in the 1980s. Hopefully we are wiser now, but institutional forces and biases still keep us from improving on our failures. As Pete Kenny says in his post for instance, obsession with specific technologies rather than a combined application of several technologies still biases scientists and managers in biotech and pharmaceutical organizations. The rise and ebb (did you just say "rise"?) of economic forces makes the job environment unstable and discourages scientists from pushing bold ideas that promise to break free from reductionist approaches. And much of our science is still based on sloppy theorizing without proper recourse to statistics and controls, not to mention an unbiased look at what the experiments truly are and are not telling us. 

Santayana told us that we are condemned to relive history if we forget it. But when it comes to the promises of rational drug design, what we should do perhaps is to purge our minds of the successes of the 20th century and remember Francis Bacon's exhortation from the 16th century instead: "All depends upon keeping the eye steadily fixed on the facts of nature. For God forbid that we should give out a dream of our own for a pattern of the world."

Image: "Cognition enhancer" (Source: Brooke Magnanti, Garrett Vreeland)

Crystallography and chemistry: The culture issue

Image: Charles Reynolds and ACS Med Chem Letters

As the old saying goes, beware of crystallographers bearing ligands. Charles Reynolds who is a well-known structure-based drug design expert has an editorial in ACS Medicinal Chemistry Letters touching on an issue that lies at the confluence of crystallography, medicinal chemistry and modeling: flaws in protein ligand co-crystal structures. It's a problem with major ramifications for drug design, especially since it sits at the apex of the process and has the power to influence all subsequent steps. It's also an issue that has come up many times before, but like many deep-seated issues this is one that has not quite disappeared from the palette of the structure-based design scientist.

In 2003 Davis, Teague and Gerard Kleywegt (who is incidentally also one of the wittiest conference speakers I have come across) wrote an article pointing out one simple observation: in several PDB structures of proteins co-crystallized with small molecule druglike ligands, the protein seems to be well-resolved and assigned, but the small molecule is often strained, with unrealistic bond lengths, planar aromatic ring atoms, non-planar amide bonds, rings in boat or pseudo chair conformations and clashes between protein and ligand atoms. Now the protein can also be misassigned, and so can water molecules, but it turns out that the problem looms much larger for ligands.

Reynolds's editorial takes another, 2014 look at this 2003 problem. And it seems that while some people have actually become more cognizant of issues in crystal structures, things aren't exactly rosy at this point in time. He points out a 2009 study that located 75% of the structures in the data set whose geometries could be improved by using better restraints.

The first and foremost pitfall that non-specialists fall into when taking a crystal structure at face value is is to assume that whatever they see on that fancy computer screen is...real. The fact though is that, barring any structure solved to better than 1 Å (when was the last time you saw that?) every crystal structure is a model (and while we are on the topic, Morpheus's definition of "real" may also be somewhat relevant here). The raw data is those dots that you see in the x-ray diffraction; everything after that, including the pretty picture that you visualize in Pymol, comes from a series of steps undertaken by the crystallographer that involve intuition, parameter fitting, expert judgement and the divining of complete information from incomplete data. That's potentially a lot of guesswork and approximation, and so it shouldn't be surprising that it often leads to flaws in the results.

So is this problem primarily a technology issue? Not really. Reynolds points out several programs that can now fit ligands to the electron density better and get rid of strain and artifacts; Schrodinger's PrimeX and OpenEye's AFITT are only two prominent examples. Nor is it complicated to find out in the first place whether a ligand might be strained; any scientist who has access to a good molecular mechanics energy minimization program can take the ligand structure out of the protein, minimize it to the nearest local minimum, look at the energy difference (usually > 5kcal/mol for a strained ligand), visualize steric clashes between atoms and reach a reasonable conclusion regarding the feasibility of that particular ligand conformation.

The abundance of methods for both figuring out strained ligand conformations and refining them seems to point to something other than technology as the operative factor in the misinterpretation of crystal structures. I believe the problem, in significant part, is culture. Reynolds alludes to this when he says that "Crystallographers are not chemists". When you are a crystallographer and are in hot pursuit of a protein structure, you are rightly going to experience a moment of ecstasy when that huge hulking hunk of sheets and strands finally appears on your screen. But most crystallographers don't care about that little blimp in the binding site - a small molecule that's often crystallized with the purpose of stabilizing the protein as much as for aiding drug discovery - as they do about their beloved protein. In addition, many crystallographers don't have the knee-jerk, intuitive reaction to, say, rings in boat conformations that a good medicinal chemist or a medicinal chemistry-aware modeler would have.

The unfortunate consequence of all this is that the ligand often just comes along for the ride and the protein's gory structural details are exquisitely teased apart at the expense of the ligand's. Protein love often inevitably translates into ligand hate. For an organic chemist a cyclohexane boat may be a textbook violation of conformational preferences, but for a crystallographer it's a big, hydrophobic group filling up a big, fuzzy halo of electron density. Crystallographers are not chemists.

However, an honest assessment of the problem would not unfairly pin the blame for bad ligand structures on crystallographers alone. The fact is that structure-based drug design is an intimate covenant between crystallographers, medicinal chemists and modelers and true appreciation and progress can only come from each side speaking or at least understanding the other's language. To this end, chemists and modelers need to be aware of crystallographic parameters and need to ask the right questions to the crystallographer, beginning with a simple question about the resolution (even this question is rarer than you may think). A medicinal chemist or modeler who simply plucks the provided structure out of the PDB file and starts using it to design drugs is as guilty as a chemistry-challenged crystallographer.

A typical set of questions a modeler or medicinal chemist might ask the crystallographer is: 

- What's the resolution?
- What are the R-factors and the B-factors? 
- Do you have equal confidence in all parts of the structure? Which parts are more uncertain?
- Are the amides non-planar? 
- Where are the water molecules located? How much confidence do you have in their placement?
- Are atoms supposed to be planar non-planar? 
- Are there any gauche or eclipsed interactions? 
- Are there boats in rings? 
- Have you looked at the strain energy of the ligand?
- How did you refine the ligand?

These questions are not meant to be posed to the crystallographer by men in dark suits in a dimly lit room with bars on the windows, but rather are supposed to provide a reality check on the fidelity of the structure and its potential utility in drug design for all three arms of the SBDD process. The questions are part of a process that allows all three departments to confer and reach an agreement; anyone can and should ask them. They are meant to bring hands together, not to point fingers.

One of the cultural problems in drug discovery is still the reluctance of one group of scientists to adopt at least parts of the cultural behavior of other groups. Organic chemists are quick to look at stereochemistry or unstable functional groups, modelers are not. Modelers are much more prone to look at conformation, organic chemists are not. Crystallographers are far more likely to bear multiple conformations of loops and flexible protein side chains in their minds, the other two parties are not.

The best way to fill these gaps is for each group to speak the language of the other, but until then the optimal solution is to have all of them look at the evidence and emphasize what they think is the most important part. But for that to happen each party has to make as many details of its own domain accessible to the others, and that is partly what is being said here.

Update: As usual, the Yoda of chemistry blogging got there first.

Why the same can be different: The case of the two enantiomers

The R enantiomer (green) allows Tyr337 to adopt
two different orientations. The S (yellow) does not.

Since we were discussing thermodynamics in biological systems the other day, here's a neat example from Angewandte Chemie of a system where thermodynamics reveals something surprising. The authors from Umeå University in Sweden were looking at two enantiomers of a ligand binding acetylcholinesterase. It's a robust, well-studied system and you don't really expect anything unexpected.

Except that it does do something unexpected. The first surprise was that both enantiomers bound with the same binding affinity. This is an observation that violates a central general tenet of biochemistry, namely that ligands and receptors are both chiral and therefore enantiomeric ligands will bind differently. The second surprise was that when they dissected the similar free energy of binding into entropic and enthalpic components, they found that the S enantiomer had a much more unfavorable entropy (1.5 e.u) than the R (8.5 e.u). Since the free energies were the same, this meant that there was enthalpy-entropy compensation, which meant in turn that the S enantiomer must have the more favorable enthalpy.

To investigate the origins of these differences, the two enantiomers were crystallized with the protein. Observation of the binding site indicated something interesting; the R enantiomer bound in a way that allowed a critical tyrosine residue (Tyr337) to adopt two different orientations. However, the S enantiomer shoved an ethyl group next to the tyrosine, essentially precluding this movement. Greater conformational flexibility for the tyrosine translated to greater disorder, hence the more favorable entropy for the R. What about enthalpy? Here it turns out that the S enantiomer, while sacrificing entropic freedom for the tyrosine, compensates by making stronger interactions with it. This was analyzed by quantum chemical calculations on a "reduced" version of the protein. Interestingly, the interactions are not "normal", respectable hydrogen bonds but "unnatural" C-H---O hydrogen bonds. For the R enantiomer, even these relatively weak interactions were enough to confer an enthalpic advantage that offset the entropic disadvantage.

This is why chemistry in general and biochemistry in particular are endlessly interesting; conventional wisdom is always being challenged even in well-studied systems, weak can be important, every example is unique and best of all, surprises lurk around almost every corner. As Arthur Kornberg put it, "I never met a dull enzyme".

Crystallography, chemistry and Nobel Prizes: Nothing to complain about

Roger Kornberg, chemist

One reason I have been puzzled and disappointed by the negative response to "biologists winning the chemistry Nobel Prize" is that the biologists who are the target of criticism have almost always been protein crystallographers. It's not like they are handing out chemistry prizes to entomologists or animal behaviorists. 

The response is especially puzzling because there's always been a proud tradition of crystallographers winning the chemistry Nobel Prize. In my reading of Nobel history I haven't really come across someone criticizing this trend; in fact I have seen the complaints emerge roughly in 2006 or so, when Roger Kornberg was recognized for his work on the machinery of transcription. Ironically, Kornberg himself in his Nobel interview praised chemistry as the "queen of the sciences" and even went to the length of saying that if an intelligent person could familiarize himself with just one science, it should be chemistry. Not surprisingly, Kornberg emphatically described himself as a chemist and chemists should proudly count him as one of their own.

And yet the gripes keep coming which is unfortunate. Let's be clear about one thing that Kornberg alluded to. Traditionally, the determination of molecular structure has always been a profoundly important concept in chemical science. Synthesis and function come next, but first one has to know the structure of the substance under investigation. A large part of the history of chemistry thus consists of organic chemists determining the structure of natural products, first through chemical degradation and then through increasingly sophisticated spectroscopic techniques including x-ray diffraction. The ribosome, GPCRs, ion channels and nuclear receptors are giant molecular assemblies, and the meticulous determination of their atomic-level structure is in principle no different from the structure determination of penicillin, aspirin or sodium chloride for that matter.

Largely for my own private elucidation but also to make this point clear, it's worth pointing out the list of crystallographers who have been awarded chemistry Nobel Prizes and their achievements. Most of these prizes have been awarded for specific structures but some have been awarded for methods, thus putting these prizes in the same category as those for NMR and mass spectrometry.

1954: Linus Pauling - Although Pauling is best known as a theoretical chemist, much of his most important work was in crystallography. At the beginning he used electron diffraction to resolve the structures of simple minerals and developed rules to describe their packing. Later he used crystallography to deduce the famous alpha helical and beta pleated sheet secondary structures of proteins.

1962: Max Perutz and John Kendrew - the fathers of modern protein crystallography, awarded the prize for their structure determination of two key proteins, hemoglobin and myoglobin. Perutz labored over the structure for fifteen years before cracking it and set the trend for every persistent crystallographer who was to follow.

1964: Dorothy Hodgkin - for her determination of the structures of important biochemical substances such as vitamin B12 and penicillin. Most chemists even today would place this work in the realm of chemistry.

1982: Aaron Klug - Klug developed crystallographic electron microscopy techniques to study many key biochemical assemblies like the tobacco-mosaic virus and chromatin.

1985: Herbert Hauptman and Jerome Karle - Hauptman and Karle formulated mathematical techniques for the direct interpretation of x-ray diffraction patterns which addressed the notorious "phase problem". This work was very much in the spirit of physics, and was the first prize awarded for diffraction methods. It's again worth noting that similar prizes were awarded for NMR and mass spectrometry methods and there was not a sound from chemists.

1988: Johann Deisenhofer, Robert Huber, Hartmut Michel - This prize was awarded for cracking open the structure of one of the most important proteins on the planet - the photosynthetic reaction center which captures light and performs the initial reactions in photosynthesis. This was also the first integral membrane protein to be crystallized, a huge technical achievement.

1997: Paul Boyer, John Walker and Jens Skou - Again, a prize awarded to an important and truly fascinating protein and the first molecular motor, the Na+ K+ ATPase. This discovery also shed light on the crucial process of ATP synthesis.

2003: Peter Agre and Roderick McKinnon - Another key protein, they just keep on coming. This time it was the potassium ion channel, the nerve center (pun) of ionic conduction, muscle action and neurotransmission among other processes.

2006: Roger Kornberg - Kornberg dissected the fundamental process of DNA to RNA transcription in meticulous detail over two decades. The work involved pinning down the positions of dozens of proteins assembled in a precisely orchestrated circus.

2009: Venki Ramakrishnan, Tom Steitz and Ada Yonath - Another molecular machine of profound importance - the ribosome. Not only did the fearsome structure of this gargantuan assembly of proteins and RNA yield to crystallography but it also validated one of the most startling and significant observations in the history of biochemistry - the ribosome is a ribozyme.

2011: Dan Shechtman - Caused a paradigm shift, albeit not in protein crystallography. Interestingly chemists were lukewarm even about this prize, relegating it to metallurgy or even physics rather than chemistry.

2012: Robert Lefkowitz and Brian Kobilka.

A few observations. There have been a total of 11 Nobel Prizes awarded since 1954 to x-ray crystallographers. That's not a lot and certainly nothing to complain about. There's of course more awarded to biochemists in general, but even there the count is 24 prizes since 1950. The crystallography prizes seem to become more frequent as we approach the 90s and the twenty-first century, and the reason is probably that the technology and methodology made it finally possibly to tackle the structures of fundamental entities like the ribosome and ion channels which couldn't be addressed before. It's also important to emphasize that each one of the protein structures provided insight into an important physiological process which involved a lot of actual, bond-breaking and bond-making, chemistry. It's natural for a chemist to lament his favorite field, reaction or molecule not winning a prize but the truth is that this reflect a provincialism that ignores chemistry's immense reach.

What's the future going to look like? Nobody can say for sure, but the increasing number of prizes awarded to biochemists and crystallographers since the 80s seem to indicate that this trend will continue, with prizes awarded even more frequently to protein crystallographers and molecular biologists. And this shouldn't be surprising. We are finally at a stage when we can use the full set of physical and chemical tools at our disposal to tackle the big biological and medical questions of our time. Chemistry through its use of structure determination techniques and small molecules will allow us to interrogate the function and find out the structure of increasingly complicated biological assemblies. 

But the take-home message is that any future chemistry Nobel Prizes awarded to "biologists" will only showcase the growing power of chemistry and spectroscopy to uncover life's deepest secrets. Synthetic and systems biologists for instance are just getting started in engineering cells and organisms and even that is chemistry. The location of the essence of biological existence in life's constituent molecules was one of the most revolutionary discoveries of all time. It seems fitting that this paradigm will shine in all its glory in the twenty-first century. Rather than resign themselves to what they see as an inevitable fate, chemists should celebrate this development as the ultimate manifestation of the power of chemistry in illuminating structure and function.

Protein-ligand crystal structures: WYSI(N)WYG

Crystal structures of proteins bound to small molecules have become ubiquitous in drug discovery. These structures are routinely used for docking, homology modeling and lead optimization. Yet as several authors have shown over the years, many of these structures can hide flaws that don't become apparent until they are actually revealed through analysis. Worse still, there may be flaws that never become apparent because nobody takes the trouble to look at the original data.

A recent paper from the group at OpenEye has a pretty useful analysis of flaws in crystal structures. They carry on a tradition most prominently exemplified by Gerard Kleywegt at Uppsala. The authors describe common metrics used for picking crystal structures from the PDB and demonstrate their limitations. They propose new metrics to remedy the problems with these parameters. And they use these metrics to analyze about 700 crystal structures used in structure-based drug design and software validation and find out that only about 120 structures or so pass the rigorous criteria used for distinguishing good structures from bad ones.

The most important general message in the article is about the difference between accuracy and completeness of data, and the caveat that any structure on a computer screen is a model and not reality. Even very accurate looking data may be incomplete and this flaw is often neglected by modelers and medicinal chemists when picking crystal structures. For instance, the resolution of a protein structure is often used as a criterion for selecting one among many structures of the same protein from the PDB. Yet the resolution only tells you how far apart atoms can be distinguished from each other. It does not tell you if the data is complete to begin with. So for instance, a crystallographer can acquire only 80% of the theoretically maximum possible data and present it with a resolution of 1.5 A, in which case the structure is clearly incomplete and possibly flawed for use in structure-based drug design. Another important metric is the R-free factor which is obtained by omitting certain parts of the data and refitting the rest to the model. A difference between R-free and the R-factor (a factor denoting the original difference between the full set of data and the model) of more than 0.45 for a structure with resolution 3.5 A or more is a red flag.

The OpenEye authors instead talk about a variety of measures that provide much better information about the fidelity of the data than resolution. The true measure of the data is of course the actual electron density. Any structure that is seen on the computer screen results from the fitting of a model to this electron density. While proteins are often fit fairly well to the density, the placement of ligands is often more ambiguous, partly because protein crystallographers are not always interested in the small molecules. The paper documents several examples of electron density that was either not fit or incorrectly fit by ligand atoms. In some cases sparse or even non-existent density was fit by guesswork, as in the illustration above. All these badly fit atoms show up in the final structure but only an expert would know this. The only way to overcome these problems is to take a look at the original electron density, which is unfortunately a task that most medicinal chemists and modelers are ill equipped for.

The worst problem with these crystal structures is that because they look so accurate and nice on a computer screen, they may fall into Donald Rumsfeld's category of "unknown unknowns". But even with "known unknowns" the picture is a disturbing one. When the authors apply all their filters and metrics to a set of 728 protein-ligand structures frequently used in benchmarking docking programs and in actual structure-based drug design projects, they find that only 17% or so (121) of the structures make it through. They collect these structures together and call the resulting database Iridium which can be downloaded from their website. But the failure of the 580 or so common structures used by leading software vendors and pharmaceutical companies to pass important filters leaves you wondering how many resources we may have wasted by using them and how much uncertainty is out there. 

Something to think about, especially when considering the 50,000 or so protein structures in the PDB. What you see may not be what you get.

Strain Energies in Ligand Binding: Round Two- Fight!

Or why to be wary of ligands in the PDB, force field energies, and anybody who tells you not to be wary of these two



One of the longstanding questions in protein-ligand binding has been; what is the energy penalty that a protein has to pay in order to bind a ligand? Another question is; what is the strain energy that a protein pays in order to bind the ligand? Contrary to what one might initially think, the two questions are not the same. Strain energy is the price paid to twist the conformation of the ligand into the binding conformation. Free energy of binding is the energy that the protein has to pay in addition to the strain energy in order to bind the ligand.

A few years ago, this question shot into the limelight because of a publication in J. Med. Chem. by Perola et al. from Vertex. The authors did a meticulous study of hundreds of ligands in their protein-bound complexes, some from the PDB and others proprietary. They used force fields to estimate the difference between the energy of the bound conformation of the ligands and the nearest local energy minimum conformation- the strain energy penalty. For most ligands, they obtained strain energies ranging from 2-5 kcal/mol. But what raised eyebrows was that for a rather significant minority of ligands, the strain energies seemed to be more than 10 kcal/mol, and for some they seemed to be up to 20 kcal/mol.

These are extremely high numbers. To understand why this is so, consider a fact that I have frequently emphasized on this blog; the concentration of a particular conformation in solution is virtually negligible if the free energy difference between it and a stable conformation is about only 3 kcal/mol. For a conformation to pay that much of an energy penalty in order to transform itself into the bound conformation would already be a stretch, considering its low concentration. For a conformation to pay an energy penalty of 20 kcal/mol does not make sense at all in this light, since such a conformation should be non-existent. Plus, think about the fact that hydrogen bonds usually contribute about 5 kcal/mol and that energy at room temperature is itself about 20 kcal/mol- significantly greater than the rotational barriers in most molecules- and this number for the strain energy penalty starts looking humungous. Where exactly would it come from?

Perola's paper generated a lot of buzz- a good thing. It was discussed by speakers at a conference in March last year that I attended. Now, a paper in J. Comp. Chem. seems to clear up the air a little. In a nutshell, the authors conclude that the strain energies they have measured seldom, if ever, surpass 2 kcal/mol. Needless to say, this is a huge difference compared to the earlier studies.

Why such a startling difference? It seems that as always, the answer strongly depends on the method and the data.

First of all, the PDB is not as flawless as people assume it is. Most people who are crystallizing protein-ligand complexes are first and foremost interested in the structure of the protein. They often do a poor job of fitting ligands to the electron density; Gerard Kleywegt of the University of Uppsala has done some marvelous work on detecting errors in PDB ligands, and his review on this should be a must-read for all scientists even marginally connected with crystallography. Because of poor fits, conformations of ligands in the electron densities in the PDB can be completely unrealistic and at the very least, brutally strained. Amides can be cis or non-planar, and more rarely planar aromatic rings can be deformed. There can be severe steric clashes which are not easily apparent. Quite naturally, such conformations when refined would lead to huge drops in energy. Therein lies the first source of the unrealistically large strain energy differences.

The second factor has to do with the vagaries and inadequacies of force fields, often unknown to crystallographers but known to experienced computational chemists. Force fields are quite poor at determining energies and their results are especially skewed by an overemphasis on electrostatic interactions which the force fields are ill-equipped to damp. Now consider what happens when a ligand in a PDB that has a positively and negatively charged group in it is optimized. If you relax it to the nearest local energy minimum, these two groups would instantly snap together and form a very strong ionic bond. This would lead to a huge overstabilization of the conformation, thus again giving the illusion of a large strain energy difference between the PDB conformation and the local minimum.

Finally, the devil is in the details. In doing the initial refinement of the conformation, the earlier study used a constraint called the flat-bottom potential in optimizing the PDB ligands in their bound state. However the flat-bottom potential, which extracts no penalties for atomic movement within a certain short distance and suddenly ramps up the penalty, is not physically realistic. A better method might be to use a harmonic potential which continuously and smoothy extracts a penalty proportional to atomic displacement.

The present study takes all these factors into account and also substitutes the force field results with some well-established quantum chemical energy determinations at the B3LYP/6-31G* level. They use this method to calculate the energies of bound and local energy minimum conformations. Secondly, they use a well-established continuum solvation model (PCM) as incorporated in the latest version of the Gaussian program to incorporate damping effects due to solvation. Thirdly as indicated above, they use the harmonic potential for optimization. Fourthly and most importantly, for the cases where the strain energy seems unusually high (and even there they set the bar quite high- anything greater than 2 kcal/mol), the authors closely investigate the relevant PDB entries and find that indeed, the ligands were not fit well into the electron density and had unrealistically strained conformations.

Once they tackled these problems, the strain energies all fell down to between 0.5 and 2 kcal/mol, which seems to be a realistic penalty that a conformation with a respectable concentration in solution could pay. There is now a second question; what is the maximum strain energy penalty that a ligand can pay to be transformed into the bound conformation? The authors are working on this question, and we will await their answer.

But this study reiterates two important lessons that should be remembered by anyone dealing with structure at all times:
1. Don't trust the PDB
2. Don't trust force field energies

Better still, as old Fox Mulder said, trust no one and nothing.

References:
1. Keith T. Butler, F. Javier Luque, Xavier Barril (2009). Toward accurate relative energy predictions of the bioactive conformation of drugs Journal of Computational Chemistry, 30 (4), 601-610 DOI: 10.1002/jcc.21087

2. Emanuele Perola, Paul S. Charifson (2004). Conformational Analysis of Drug-Like Molecules Bound to Proteins: An Extensive Study of Ligand Reorganization upon Binding Journal of Medicinal Chemistry, 47 (10), 2499-2510 DOI: 10.1021/jm030563w

3. A Davis, S Stgallay, G Kleywegt (2008). Limitations and lessons in the use of X-ray structural information in drug design Drug Discovery Today, 13 (19-20), 831-841 DOI: 10.1016/j.drudis.2008.06.006

Questions for the kinase biologists

I am working on a kinase inhibitor design project and I realised that there are some key questions that we need to get answered from the biologists before we can rationalize the selectivity of various kinase inhibitors for a given binding site. I also realised that these questions need to be answered for many other kinds of protein-inhibitor interactions.

1. Whenever we get different IC50 data for two inhibitors, we immediately try to look at binding interactions that may be different for the two moelcules to rationalize this observation. But as I have alluded before, it's not the IC50 but the Ki that's really to do with different binding interactions. The Ki and IC50 are related by an equation that includes both the Km value of ATP and the concentration of ATP in the two experiments, or in general, these two parameters for the natural binding substrate for the protein. Only if these two are the same for both inhibitor experiments is the IC50=Ki. So make sure you confirm this. Otherwise, extrapolate and calculate the new IC50s based on identical values for these parameters. Then rationalize the IC50s based on binding interactions.

2. For many kinases, three events are absolutely essential for activation:
a. Phosphorylation of one Ser, Thr or Tyr residue,
b. Binding of ATP (duh), and
c. Dephosphorylation of another Ser, Thr or Tyr residue.
Think of it like a logic gate. IF the answers to all a. b. and c. are YES, THEN the kinase will be activated and proceed to perform its function. (I got this from Alberts et al.'s Molecular Biology of the Cell)
In the assays that are run, it is important to know (and not very easy to always determine as I have been told) whether the necessary residue is phosphorylated or not. For one thing, inclusion of this knowledge in your docking and modeling can naturally make a big difference. And secondly, depending on the state of phosphorylation, you can think of different modes of inhibition for your inhibitor (eg. ATP blocking + substrate blocking).

As usual, it's important to know what the biologists are doing. They don't know the nuances of modeling/crystallography and you don't know the nuances of their assays. But it's important for both camps to think of questions which the other camp should answer that will affect their own work.