Monday, 23 October 2017

War and PAINS



Non-interfering chemotypes are all alike;
 every interfering chemotype interferes in its own way



From afar, the Grande Armée appears invulnerable. The PAINS filters have been written into the Laws of MedChem and celebrated in Nature. It may be a couple of thousand kilometers to Moscow but what could possibly go wrong?

Viscount Wellington (he is yet become the 'Iron Duke') shadows the Grande Armée from the south. Dismissed as 'The Sepoy General' (he just writes blogs), Wellington knows that the best way to win battles is to persuade opponents to first underestimate him and then to attack him. He also knows that seemingly intractable problems often have simple solutions and, when asked years later by Queen Victoria as to how the sparrow problem of the new Crystal Palace might be resolved, his pithy response is, "Sparrowhawks, Ma'am".

Marshal Ney guards the southern flank of the Grande Armée and Wellington knows, from the Peninsular War, that Ney is a formidable opponent. Wellington is fully aware that, on the steppes, it will be all but impossible to exploit Ney's principal weakness (an unquestioning and unwavering belief in meaningfulness of Ligand Efficiency). Wellington knows that he will have to be very, very careful because Ney is a masterful exponent of the straw man defense.


The first contact with the Grande Armée occurs unexpectedly in the Belovezhskaya Pushcha. One of Ney's subordinates has set off in hot pursuit of a foraging party of thiohydantoins (which he has mistaken for rhodanines) and left the flank of Grande Armée exposed. Wellington orders an attack in an attempt to capitalize on the blundering subordinate's intemperance and it is only through the prompt action of Ney, who takes personal charge of the situation, that disaster is averted.

The first skirmish proves to be tactical draw although Ney's impetuous subordinate has been relieved of his command and put on clam-gathering duty. Wellington orders a diversionary attack designed to probe the Grande Armée defenses and then another intended to lure Ney into counter-attacking his carefully prepared defensive position. Ney initially appears to take the bait but soon disengages once he perceives the full extent of Wellington's defensive position. It will prove to be their final clash for the duration of this campaign.

The next contact with the Grande Armée takes place at Smolensk. A regiment of Swiss Guards, on loan from the Vatican, becomes detached from the main force and blunders into Wellington's outer defensive belt. The Swiss Guards' halberds prove to be of little use in this type of warfare and they are swiftly overwhelmed. As they are taken captive, many of the Swiss Guards are heard to mutter that the six assays of the PAINS panel are "different and independent, different and independent..." although none seems wholly convinced by their mantra.

Following the tactical victory at Smolensk, Wellington receives word by messenger pigeon that Marshal Kutuzov will attempt to stop the Grande Armée at Borodino (on the road to Moscow) and that Wellington should do what he can to harass the Grande Armée so as to buy more time for Kutuzov to complete his preparations. Wellington orders another diversionary attack which exposes the narrowness of the PAINS filter applicability domain before proceeding to Borodino where he arrays his troops to the south of the road to Moscow.

The armies of Wellington and Kutuzov are now disposed so as to counter a flanking maneuver by the Grande Armée but it is the army of Kutuzov that will bear the brunt of the attack while Wellington's force is held in reserve. Wellington marvels at Kutuzov's preparations and the efficient manner in which he has achieved optimal coverage of the terrain with the design of the training set. Not a descriptor is wasted and each differs in its own way since they are uncorrelated with each other. Nobody will be able to accuse Kutuzov of overfitting the data. Over a century later, Rokossovsky will tell Zhukov, "everything I know about QSAR, I learned from Kutuzov".


The Grande Armée advances confidently but Kutuzov is ready and up to the task at hand. The Grande Armée is first stopped in its tracks by a withering hail of grapeshot (more than half of the PAINS alerts were derived from one or two compounds only) and then driven back (...were originally derived from a proprietary library tested in just six assays measuring protein–protein interaction (PPI) inhibition using the AlphaScreen detection technology only). Running out of options, the Grande Armée commanders are forced to commit the elite Garde Impériale which temporarily blunts Kutuzov's advance. Wellington maneuvers his troops from their defensive squares into an attacking formation and awaits Kutuzov's order to commit the reserve.



Although the Grande Armée commanders consider it beneath them to do battle with the lowly Sepoy General, they have at least strengthened their southern flank in acknowledgement of his presence there. This in turn has weakened the northern flank which has been assumed to be safe from interference and it is at this point in the battle that the Grande Armée gets an unpleasant surprise. There is the unmistakable sound of hoofbeats coming from the north, quiet at first but getting louder by the minute. Emerging from the smoke of battle, Marshal Blücher's Uhlans slam into the lightly-protected northern flank of the Grande Armée (the same PAINS substructure was often found in consistently inactive and frequently active compounds). Following an attack plan on which Blücher has provided vital feedback, Wellington commits his troops although, in reality, there is little left for them to do aside from pursuing the retreating Garde Impériale.


There are lessons to be learned from the fate of the Grande Armée. The PAINS filters were caught outside their narrow applicability domain on the vast Russian steppes and their fundamental weaknesses were brought into sharp focus by Blücher and Kutuzov who made effective use of large, non-proprietary data sets. Whether you're talking about T-34s or data, quantity has a quality all of its own. Science blogs are here to stay although, from time to time, every blogger should write a journal article pour encourager les autres.

Thursday, 12 October 2017

The resurrection of Maxwell's Demon

Sometimes when reading the residence time literature, I get the impression that the off-raters have re-animated Maxwell's Demon. It seems as if a nano-doorman stands guard at at the entrance of the binding site, only opening his nano-door to ligand molecules that want to get in. Microscopic Reversibility? Stop being so negative! With Big Data, Artificial Intelligence, Machine Learning (formerly known as QSAR) and Ligand Efficiency Metrics we can beat Microscopic Reversibility and consign The Second Law to the Dustbin Of History!

There were a number of things that triggered this blog post. First, I saw a recent article that got me thinking about philatelic drug discovery.  Second, some of the off-raters will be getting together in Berlin next week and I wanted to share some musings because I won't be there in person. Third, my former colleague Rutger Folmer has published a useful (dare I say, brave) critique of the residence time concept that is bang on target. 

I'm not actually going to say much about Rutger's article except to suggest that you read it. That's because I really want to examine the article on philatelic drug discovery in a more detail (it's actually about thermodynamic and kinetic profiling but I thought the reference to philately would better grab your attention). My standard opening move when playing chess with an off-rater is to assert that slow binding is equivalent to slow distribution. In what situations would you design a drug to distribute slowly?

Chemical kinetics is all about energy barriers and, the higher the barrier, the slower things will happen. Microscopic reversibility tells us that a barrier to association is a barrier to dissociation and that the ligand will return to solution along the same path that it took to its binding site. Microscopic reversibility tells you that if you got into the parking spot you can get out of it as well although that may not be the experience of every driver. The reason that microscopic reversibility doesn't always seem to apply to parking is that most humans, with the possible exception of tank drivers in the Italian army, are more comfortable in forward gear than in reverse. Molecules, in contrast, have no more concept of forward and reverse than they do of standard states, IUPAC or the opinions the 'experts' who might quantitatively estimate their drug-likeness while judging their beauty. Molecules don't actually do concepts. Put more uncouthly, molecules just don't give a toss.

I've created a graphic to illustrate to show how things might look in vivo when there is a barrier to association (and, therefore, to dissociation). We can think of the ligand molecule having to get over the barrier in order to get to its binding site and we call the top of the barrier the 'transition state'. This is a simplified version of reality (it is actually the system that passes from the unbound state through the transition state to the bound state and for some ligand-protein association there is no barrier) but it'll serve for what I'd like to say. The graphic consists of three panels and the first (A) of these illustrates the situation soon after dosing when the concentration of ligand (L) is relatively high and the target protein (P) has not had sufficient time to respond. If the barrier is sufficiently high, the system can't get to equilibrium before the ligand concentration starts to fall in what a pharmacokineticist might refer to as the elimination phase. Under this scenario the system will be at equilibrium briefly as the ligand concentration falls and I've shown this in panel B. After the equilibrium point is reached, the rate of dissociation exceeds the rate of association and this is shown in panel C. 



There's something else that I'd like you to take a look at in the graphic and that's the free energy (G) of the unbound state (P + L).  See how it goes down relative to the free energy of the bound state (P.L) as the concentration of ligand decreases. When thinking about energetics of these systems, it actually makes a lot of sense to use the unbound state as the reference but you do need to use a reference concentration (e.g. 1 M) to to do this.

When we do molecular design we often think in terms of manipulating energy differences. For example, we try to increase affinity by stabilizing the bound state relative to the unbound state. Once you start trying to manipulate off-rates, you soon realize that you can't change one thing at a time (unless you draft Maxwell's Demon into your project team).  I've created a second graphic which looks similar to the first graphic although there are important differences between the two graphics. In particular, I'm referencing energy to the unbound state (P + L) which means that the ligand concentration is constant in all three panels. Let's consider the central panel as the starting point for design. We can go left from that starting point and stabilize the bound state which is equivalent to optimizing affinity.  Stabilizing the bound state will also result in slower dissociation provided that the transition stare energy remains unchanged. This is a good thing but it's difficult to show that the benefits come from the slower dissociation and not from the increased affinity. If you raise the barrier (i.e. increase the energy of the transition state) to reduce the off-rate you'll find that you have slowed the on-rate to an equal extent.        



Before moving on, it may be useful to sum up where we've got to so far. First, ask yourself why you think off-rates will be relevant in situations where concentration changes on a longer time scale than binding. Second, you'll need to enlist the help of Maxwell's Demon if you want to reduce off-rate without affecting on-rate and/or affinity. Third, if you want to consider binding kinetics in design then it'd be best to use barrier height (referenced to unbound state) and affinity as your design parameters.

Now I'd take a look at the philatelic drug discovery article. This is a harsh term but it does capture a tendency in some drug discovery programs to measure things for the sake of it (or at least to keep the grinning Lean Six Sigma 'belts' grinning).  Some of this is a result of using techniques such as isothermal titration calorimetry (ITC) and surface plasmon resonance (SPR) that yield information in addition to affinity (that is of primary interest) at no extra cost. I really don't want to come across as a Luddite and I must stress that measurements of enthalpy, entropy, on-rate and off-rate are of considerable scientific interest and are also valuable for improving physical models. Furthermore, I am continually awed by the exquisite sensitivity of modern ITC and SPR instruments and would always want the option to be able to measure affinity using at least one of these techniques. However, problems start when the access to enthalpy, entropy, off-rates and on-rates becomes exploited for 'metrication' and drug discovery scientists seek 'enthalpy-driven' binding simply because the binding will be more 'enthalpy-driven'. It is easier to make the case for relevance of binding kinetics although, as Rutger points out, reducing the off-rate may very well make things worse if the on-rate is also reduced. It is much more difficult to assemble a coherent case for the relevance of thermodynamic signatures in drug discovery. Perhaps, some day, a seminal paper from the Budapest Enthalpomics Group (BEG) will reveal that isothermal systems like live humans can indeed sense the enthalpy and entropy changes associated with drugs binding to their targets although I will not be holding my breath.

Unsurprisingly, the thermodynamic and kinetic profiling (aka philatelic drug discovery) article advocates thermodyanamic profiling of bioactive compounds in lead optimization projects. I'm going to focus on the kinetic profiling and it is worrying that the authors don't seem to be aware that on-rates and off-rates have to be seen in a pharmacokinetic context in order to make the connection with drug discovery. The authors may find it instructive to think about how inhibitor concentration would have varied over the course of a typical experiment in their cell-based assays. They are also likely to find Rutger's article to be educational and I recommend that they familiarize themselves with its content.

The following statement suggests that it may be beneficial for the authors to also familiarize themselves with the rudiments of chemical kinetics:


"Association and dissociation rate constants (kon and koff) of compound binding to a biological target are not intrinsically related to one another, although they are connected by dissociation equilibrium constant KD (KD = koff/kon)."

The processes of association and dissociation are actually connected by virtue of taking place along the same path and by having to pass through the same transition states. The difference in barrier heights for association and dissociation is given by the binding free energy. 

Some analysis of relationships between potency in a cell-based assay and  KD, koff and kon were presented in Figure 6 of the article. I have a number of gripes with the analysis. First, it would be better to use logarithms of quantities like KD, IC50, koff and kon when performing analysis of this nature. In part, this because we typically look for linear free energy relationships in these situations. There is another strong rationale for using logarithms because analysis of correlations between continuous variables works best when the uncertainties in data values are as constant as possible. My second gripe is that the authors have chosen to bin their data for analysis and this is a great way to shoot yourself in the foot. When you bin continuous data you both reduce your data analysis options and leave people wondering whether the binning has been done to hide the weakness of the trends in the data.   I have droned at length about why it is naughty to bin continuous data so I'll leave it at that.

It's been a long post and it's time to wrap things up. If you've found the post to be 'cansativo' (sounds so much more soothing in Portguese) then spare a thought for the person who had to write it. To conclude, I'll leave you with a quote that I've taken from the abstract for Rutger's article:
  
"Moreover, fast association is typically more desirable than slow, and advantages of long residence time, notably a potential disconnect between pharmacodynamics (PD) and pharmacokinetics (PK), would be partially or completely offset by slow on-rate."