SAR by STD: NOT

As noted last week, Practical Fragments has been on something of a crystallography binge. But according to polling, NMR is the most common fragment-finding method. And, according to a different poll, saturation transfer difference (STD) is the most popular NMR technique. Familiarity breeds complacency, and widespread assumptions go untested. A new paper in Front. Chem. by Jonas Aretz and Christoph Rademacher (Max Planck Institute and Freie Universität Berlin) suggests that this is a mistake.

In STD NMR, a protein is saturated by specific electromagnetic pulses, and the resulting magnetization transfers to bound ligands. Assuming that the bound ligands are in rapid equilibrium with ligands free in solution, this “saturation transfer” results in a reduction of NMR signal for the small molecule in the presence of protein compared to no protein. High affinity ligands will remain bound to the protein and thus be missed by STD NMR, but this is usually not relevant in FBLD, where most fragments bind with dissociation constants weaker than 10 µM.

A common assumption with STD NMR is that the strength of an STD signal increases with the affinity of the ligand (again, in affinity ranges between about 10 µM and 10 mM). Indeed, when STD NMR is used as part of a screening cascade, molecules showing the strongest effect are generally prioritized as hits. But is this assumption correct?

To find out, the researchers retrospectively analyzed a fragment screen against langerin, a carbohydrate-binding protein we discussed last year. When they plotted the STD amplification factor against the affinity (measured by SPR) for several dozen fragments, the resulting scatter plot showed no correlation.

Recognizing that experimental errors could obscure a true correlation, the researchers ran virtual STD experiments using COmplete Relaxation and Conformational Exchange MAtrix (CORCEMA) theory. They used well-characterized fragments with published crystal structures and affinities for some dozen diverse proteins. As they conclude, “varying saturation time, receptor size, binding kinetics, and interaction site… there were no conditions in which the STD NMR amplification factor correlated unambiguously with affinity.”

But it gets worse. When the researchers explored the effects of binding kinetics, they found that ligands with slower on-rates or off-rates also had lower STD signals. Several groups have advocated prioritizing compounds with slower-off rates, yet these are the very compounds STD is most likely to miss.

All in all this paper could go some way toward explaining the sometimes poor correlation between different fragment-finding methods.

That said, I’m no NMR spectroscopist, so I’m certainly not as qualified to comment on the importance of this paper as someone like Teddy, who co-wrote this how-to guide for STD NMR. I’d be interested to hear what NMR folks think, and whether we should rethink use of STD. In any case, this work is a useful reminder that skepticism is a scientific virtue.

Fifth NovAliX Biophysics in Drug Discovery Conference

Last week NovAliX held its biophysics meeting outside of Strasbourg for the first time. Naturally they chose Boston, one of the most European of US cities and a major hub of drug discovery. The event brought together 118 participants from 15 countries, roughly 80% from industry. Although the food and drink could not compare to France, the science and discussion were every bit as satisfying. With 30 talks and 22 posters I won’t attempt to be comprehensive, but as with last year just try to capture a few themes. 

One particularly noteworthy session was devoted to single particle cryo-electron microscopy (cryo-EM), which was recently reviewed in Nat. Rev. Drug Discov. by conference chairman Jean-Paul Renaud and a multinational team of experts. The approach involves flash-freezing a thin film of sample and using transmission electron microscopy to capture two-dimensional “projection” images of your target. If the protein is randomly oriented you can computationally combine thousands of individual images into a three dimensional structure. Although the technique has been around for decades, until recently the resolution was too low to be useful for structure-based drug design. Recent advances in hardware and computation have led to what’s come to be known as the “resolution revolution,” explained Gabe Lander (Scripps).

One advance is the 300 keV Titan Krios – a massive (and massively expensive) instrument that is so widely coveted that Gabe showed pictures of happy scientists hugging newly delivered crates. Indeed, of the ~1000 structures solved to < 4 Å resolution, the vast majority of them were solved on one of more than 130 Krios instruments throughout the world. But Gabe showed that high resolution structures can be obtained with more common 200 keV instruments, including a 2.6 Å resolution structure of aldolase (150 kD), a 2.9 Å structure of hemoglobin (64 kD), and a 2.9 Å resolution structure of alcohol dehydrogenase (81 kD) with bound NAD⁺ cofactor. Although only a handful of sub-2 Å structures have been reported, he thought these would become routine in the next few years.

Bridget Carragher (New York Structural Biology Center) described challenges and how to overcome them. Currently it takes at best eight hours to go from data to structure, but she thought getting this to under one hour would be achievable. Moreover, cryo-EM can be used to characterize different conformational or oligomeric states present in a single sample, as Giovanna Scapin (Merck) demonstrated with insulin binding to its receptor. Indeed, even simple visualization – without fancy computational processing – can provide useful information about protein aggregation, as demonstrated by Wen-ti Liu (NovAliX).

Although primary fragment screening still looks a long way off for cryo-EM, it should start to provide useful structural information for fragments bound to targets less amenable to conventional biophysical techniques, such as membrane proteins – the topic of another session.

Miles Congreve (Heptares) discussed how their stabilized “StaR” GPCRs can provide high-resolution crystal structures suitable for FBDD (see for example here). This has allowed them to discover less lipophilic, more ligand-efficient drug candidates against a variety of targets.

According to Anass Jawhari, it isn’t even necessary to make mutant GPCRs: Calixar has developed proprietary detergents that can stabilize full length adenosine A_2A receptor for a week – more than enough time to perform STD NMR screens of 100 fragments and identify 19 hits, some of which turned out to be functional antagonists. Matthew Eddy (University of Southern California) used two-dimensional NMR on this same protein to reveal dramatic differences in conformational dynamics when bound to agonists vs antagonists.

Indeed, conformational changes and dynamics were a running theme throughout the conference. Keynote speaker and Nobel-laureate Martin Karplus (Harvard) quoted fellow Nobelist Richard Feynman: “everything that living things do can be understood in terms of the jiggling and wiggling of atoms.” (As an aside, Martin’s MCSS method pioneered computational FBDD approaches, predating SAR by NMR.) Göran Dahl (AstraZeneca) described how large scale conformation changes well outside of the active site of PI3Kgamma were responsible for freakishly high selectivity of a class of inhibitors.

But how do you detect conformational changes? We’ve previously mentioned Biodesy’s SHG approach, and Parag Sahasrabudhe (Pfizer) described how this proved useful for classifying ligands for IL-17A. Gerrit Sitters (Lumicks) described a completely different “dynamic single-molecule” (DSM) approach, which involves trapping a single fluorescently labeled protein between DNA strands tethered to two microspheres. Changes in protein conformation caused by ligand binding change the distance between microspheres, and these can be detected to within 1 Å.

Kinetics is intimately linked to dynamics, but the factors responsible for slow binding and dissociation are still poorly understood. Chaohong Sun (AbbVie) examined an archive of 8000 data points and found that on-rates and off-rates each varied by more than five orders of magnitude. There was no correlation with ClogP of the ligands, though larger ligands were more likely to have slower kinetics. There were also significant target effects; on-rates were consistently slow for one target.

As we’ve previously discussed, off-rate screening (ORS) can be used to identify hits in crude reaction mixtures, and Menachem Gunzburg (Monash University) described how this technique is being used in hit-to-lead efforts. Lowering the temperature to 4 °C and adding 5% glycerol further slows dissociation, allowing weaker hits to be discovered.

At the extreme, irreversible inhibitors have an off-rate of 0, and Gregory Craven (Imperial College London) described quantitative irreversible tethering of electrophilic fragments to cysteine residues in proteins using a fluorimetric plate-based assay. As we’ve noted, one challenge with irreversible tethering is deconvoluting intrinsic reactivity from proximity-directed reactivity, which Gregory addresses using a reference thiol such as glutathione.

There is much more to say but in the interest of time I’ll stop here. If you missed the conference you have two chances next year: June 4-7 when it returns to Strasbourg, and November 20-22 when it will be held in Kyoto. And there are still excellent events coming up this year – hope to see you at one!

Twelfth Annual Fragment-based Drug Discovery Meeting

CHI’s Drug Discovery Chemistry meeting took place over four days last week in San Diego. This was easily the largest one yet, with eight tracks, two one-day symposia, and nearly 700 attendees; the fragment track alone had around 140 registrants. On the plus side, there was always at least one talk of interest at any time. On the minus side, there were often two or more going simultaneously, necessitating tough choices. As in previous years I won’t attempt to be comprehensive but will instead cover some broad themes in the order they might be encountered in a drug discovery program.

You need good chemical matter to start a fragment screen, and there were several nice talks on library design. Jonathan Baell (Monash University) gave a plenary keynote on the always entertaining topic of PAINS. Although there are some 480 PAINS subtypes, 16 of these accounted for 58% of the hits in the original paper, suggesting that these are the ones to particularly avoid. But it is always important to be evidenced-based: some of the rarer PAINS filters may tag innocent compounds, while other bad actors won’t be picked up. As Jonathan wrote at the top of several slides, “don’t turn your brain off.”

Ashley Adams described the reconstruction of AbbVie's fragment libraries. AbbVie was early to the field, and Ashley described how they incorporated lessons learned over the past two decades. This included adding more compounds with mid-range Fsp³ values, which, perhaps surprisingly, seemed to give more potent compounds. A 1000-member library of very small (MW < 200) compounds was also constructed for more sensitive but lower throughput biophysical screens. One interesting design factor was to consider whether fragments had potential sites for selective C-H activation to facilitate fragment-to-lead chemistry.

Tim Schuhmann (Novartis) described an even more “three-dimensional” library based on natural products and fragments. Thus far the library is just 330 compounds and has produced a very low hit rate – just 12 hits across 9 targets – but even a single good hit can be enough to start a program.

Many talks focused on fragment-finding methods, old and new. We’ve written previously about the increasingly popular technique of microscale thermophoresis (MST), and Tom Mander (Domainex) described a success story on the lysine methyltransferase G9a. When pressed, however, he said it did not work as well on other targets, and several attendees said they had success in only a quarter to a third of targets. MST appears to be very sensitive to protein quality and post-translational modifications, but it can rapidly weed out aggregators. (On the subject of aggregators, Jon Blevitt (Janssen) described a molecule that formed aggregates even in the presence of 0.01% Triton X-100.)

Another controversial fragment-finding technique is the thermal shift assay, but Mary Harner gave a robust defense of the method and said that it is routinely used at BMS. She has seen a good correlation between thermal shift and biochemical assays, and indeed sometimes outliers were traced to problems with the biochemical assay. The method was even used in a mechanistic study to characterize a compound that could bind to a protein in the presence of substrate but not in the presence of a substrate analog found in a disease state. Compounds that stabilized a protein could often be crystallized, while destabilizers usually could not, and in one project several strongly destabilizing compounds turned out to be contaminated with zinc.

Crystallography continues to advance, due in part to improvements in automation described by Anthony Bradley (Diamond Light Source and the University of Oxford): their high-throughput crystallography platform has generated about 1000 fragment hits on more than 30 targets. Very high concentrations of fragments are useful; Diamond routinely uses 500 mM with up to 50% DMSO, though this obviously requires robust crystals.

Among newer methods, Chris Parker (Scripps) discussed fragment screening in cells, while Joshua Wand (U. Penn) described nanoscale encapsulated proteins, in which single protein molecules could be captured in reverse micelles, thereby increasing the sensitivity in NMR assays and allowing normally aggregation-prone proteins to be studied. And Jaime Arenas (Nanotech Biomachines) described a graphene-based electronic sensor to detect ligand interactions with unlabeled GPCRs in native cell membranes. Unlike SPR the technique is mass-independent, and although current throughput is low, it will be fun to watch this develop.

We recently discussed the impracticality of using enthalpy measurements in drug discovery, and this was driven home by Ying Wang (AbbVie). Isothermal titration calorimetry (ITC) measurements suggested low micromolar binding affinity for a mixture of four diastereomers that, when tested in a displacement (TR-FRET) assay, showed low nanomolar activity. Once the mixture was resolved into pure compounds the values agreed, highlighting how sensitive ITC is to sample purity.

If thermodynamics is proving to be less useful for lead optimization, kinetics appears to be more so. Pelin Ayaz (D.E. Shaw) described two Bayer CDK kinase inhibitors having either a bromine or trifluoromethyl substitution. They had similar biochemical affinities and the bromine-containing molecule had better pharmacokinetics, yet the trifluoromethyl-containing molecule performed better in xenograft studies. This was ultimately traced to a slower off-rate for the triflouromethyl-substituted compound.

The conference was not lacking for success stories, including MetAP2 and MKK3 (both described by Derek Cole, Takeda), LigA (Dominic Tisi, Astex), RNA-dependent RNA polymerase from influenza (Seth Cohen, UCSD), and KDM4C (Magdalena Korczynska, UCSF). Several new disclosures will be covered at Practical Fragments once they are published.

But these successes should not breed complacency: at a round table chaired by Rod Hubbard (Vernalis and University of York) the topic turned to remaining challenges (or opportunities). Chief among these was advancing fragments in the absence of structure. Multiprotein complexes came up, as did costs in terms of time and resources that can be required even for conventional targets. Results from different screening methods often conflict, and choosing the best fragments both in a library and among hits is not always obvious. Finally, chemically modifying fragments can be surprisingly difficult, despite their small size.

I could go on much longer but in the interest of space I’ll stop here. Please add your thoughts, and mark your calendars for next year, when DDC returns to San Diego from April 2-6!

Fragment optimization without purification

Compound purification can be a major hassle: separating the desired product from starting materials, reagents, and byproducts often takes far longer than making the compound in the first place. As we’ve previously noted, this is especially true for small, polar fragments – which are particularly attractive for drugs. Two new papers address this challenge. (Shameless plug: my company Carmot Therapeutics also has a solution to this problem.)

In J. Med. Chem., Paul Brough and Vernalis colleagues describe their discovery of inhibitors of all four isoforms of pyruvate dehydrogenase kinase (PDHK), potential targets for diabetes and oncology. The ATP-binding site of these four enzymes is similar to that of oncology target HSP90, in which Vernalis has a long-standing interest.

A screen of 1063 fragments (each at 0.5 mM) against PDHK-2 yielded 78 hits that were positive in three different NMR-based assays and also ATP-competitive. These yielded a whopping 43 structures when soaked into crystals of the related isoform PDHK-3. Compound 6 was one, and the binding mode was very similar to that previously seen for the same fragment with HSP90. Fragment growing rapidly led to molecules such as compound 8, with low micromolar potency. This compound was almost equipotent against HSP90, but modeling suggested that it might be possible to further grow this molecule in a direction that would be accommodated in the PDHKs but not in HSP90.

The next step was to make a bunch of analogs, and here's where avoiding purification becomes advantageous. Specifically, the researchers turned to off-rate screening (ORS), which entails making compounds and then testing the impure mixtures using surface plasmon resonance (SPR) to look for those which dissociate more slowly. Since off-rate is not dependent on the concentration of ligand, a low yield shouldn’t change the results of the assay.

An initial library of 56 compounds led to the discovery of compound 18, and subsequent libraries and medicinal chemistry ultimately yielded VER-246608, which is a potent pan-PDHK inhibitor. As designed, it is also completely inactive against HSP90. The molecule is described more thoroughly in this Oncotarget paper, which reveals that despite activity against PDHKs in cells, VER-246608 is not particularly effective at slowing the proliferation of cancer cells. Still, it does appear to be a useful chemical probe for further exploring the biology of the PDHKs.

Shifting methods but staying with the theme of assaying impure compounds brings us to a paper in SLAS Discovery by Sten Ohlson, Brian Dymock, and colleagues at Nanyang Technological University and the National University of Singapore. The protein tested was HSP90, and the method used was weak affinity chromatography, or WAC (see here, here, and here).

Like SPR, WAC also uses an immobilized protein. However, whereas SPR provides the (kinetic) off-rate, WAC provides the (thermodynamic) dissociation constant, which is calculated from the change in retention time of the molecule as it passes through a column containing protein-bound resin. In this case the researchers synthesized a mixture of five different compounds which varied from 7-24% of the mixture. This crude sample was analyzed by WAC, and the resulting dissociation constants, ranging from 48-147 µM, were satisfactorily similar to the values obtained using pure compounds.

Both of these approaches should accelerate screening and facilitate the analysis of complicated mixtures, such as natural product extracts. It will be fun to watch for more examples.

Dynamic undocking for better predictions

Computational screening continues to improve, due in part to a better understanding of the energetics of protein-ligand interactions. But for low affinity fragments, differentiating binders from nonbinders is still challenging. In a recent paper in Nature Chemistry, Xavier Barril and collaborators at the Universitat de Barcelona, Discngine, Vernalis, and the University of York describe a new approach that sidesteps thermodynamics.

The researchers started with the notion that, in many cases, a single hydrogen bond is critical for the stability of a protein-ligand complex. Rather than trying to calculate the binding energy of the complex, they instead ran “dynamic undocking” (DUck) experiments. This involved “steered molecular dynamics” simulations in which the researchers calculated how much work (W_QB) is required to move the ligand from the bound state to a quasi-bound state in which the key hydrogen bond is broken. The calculations do not consider what happens under equilibrium conditions (ie, unbinding and rebinding), so W_QB should not necessarily correlate with binding affinity. Still, one might expect ligands that require a particularly high energy to dissociate (for example, W_QB > 6 kcal/mol) to have higher affinities. This turned out to be the case for ligands targeting several different proteins: the kinase CDK2, the GPCR adenosine A2A receptor, and the protease trypsin. Indeed, receiver operating characteristic curves (an analysis comparing known binders and decoys) showed a significant enrichment of true binders.

Next, the researchers compared DUck with several commonly used computational docking approaches. Again, and not surprisingly, there was essentially no correlation. However, the researchers argue that this is a feature, not a bug, since the very orthogonality of the approaches should provide better predictions: a molecule that docks favorably and has a high W_QB is more likely to be a real hit.

This is a nice idea, but does it work in practice? To find out, the researchers turned to the old work-horse protein HSP90 and performed docking experiments on 280,000 fragments. Of the top 450 hits, 139 diverse molecules were chosen for DUck. Several dozen of these were then tested for binding using three different ligand-observed NMR experiments.

Of 21 molecules with W_QB > 6 kcal/mol, 8 confirmed as binders by all three NMR methods – an impressive hit rate of 38%. SPR confirmed binding for four of these (with dissociation constants between 0.077 and 0.73 mM), while three yielded crystal structures. In contrast, only one out of 15 molecules with W_QB between 3 and 6 kcal/mol confirmed, while none of 11 molecules with W_QB < 3 kcal/mol were clear hits. In other words, not only is DUck able to improve identification of true binders, it appears to have a fairly low false negative rate.

In a sense, this approach addresses the question of kinetics. Molecules that dissociate slowly from their target are becoming increasingly fashionable; perhaps DUck can be used to identify them. Although the researchers do not make this claim, several of the authors described an experimental “off-rate screening” approach a few years ago. It will be fun to see further developments, particularly as the method is extended to incorporate information beyond a single hydrogen bond.

More Notes from DDC 2015

Dan and I both gave our thoughts on the conference last week.  But there was more than just the talks.  There were roundtables.  I chaired one on using kinetics and thermodynamics to drive medchem for the PPI track.  It was a lively discussion.  It was agreed that dyed in the wool enzymologists are priceless.  Kinetics is useless if clearance is the driving force, so this becomes a PK/PD issue.  But does it always have to be?  Paul Belcher from GE shared the On/off rate map (Figure 1) that shows what realm of binding you are in depending on your reates.  Paul also mentioned that Tony Gianetti, formerly of Genentech, used HSA and SPR to assess a more realistic picture of how compounds interact in plasma.  In terms of earlier phase uses, one of the round table attendees mentioned that she had seen talks of people using kinetic data to drive medchem.  She couldn't recollect who, so if any of our astute readers have references please share.  We also discussed using kinetic data to rank compounds with similar IC50.  A question was raised whether or not kinetics can be a good surrogate for receptor occupancy? 

Figure 1.  On/off Rate Map: A = affinity limited efficacy, B= on rate limited efficacy, C= rapid off rate limited, D= slow off protected efficacy

So, what about thermodynamics?  By and large, this was viewed as retrospective only.  Paul from GE did share that they have an app note of using SPR to generate thermodynamic data (I can't figure out how to link it, so if you want it contact me (or Paul) and we can send it). 

The main thrust was that neither kinetics nor thermodynamics are used to make prospective medchem decisions, rather they are used to justify in retrospection. Specifically for PPIs, the consensus was that the focus should be on on rate because you have to the compound in there when you can (i.e. when the complex is "open" enough). 

Derek Cole of Takeda led one of the FBDD round tables: Practical Aspects of Fragment Screening. Here is a picture, courtesy of Bjorn Walse of Saromics.  

His notes are replicated below:

Round table became figure 8 with two tables, with 2-3 deep seats and 40 -50 participants. FBDD expertise from novice to experts, including Teddy Zartler, Dan Erlanson, Gregg Siegal, and Andrew Petros. Large attendance highlights the number of newcomers to FBDD, confirmed by Dan Erlanson during opening when 2/3 of attendees indicated this was their first CHI FBDD meeting. Very lively debate/discussion covering 4 primary targets.

1. Designing and building and storing libraries. Discussed size of library i.e. 1000 or 40K. Agreed that a good library of 1000 should yield lots of high quality hits. Best to keep HA low, 10 - 16 (majority in 12 - 14 range). Discussed 3D vs. flat fragments. Flat give higher hit rate and should be major part of library. 3D likely give lower hit rate but may yield very exciting hits. Discussed complexity and the need for fragments to have enough complexity, but not two pharmacophores. (ref. Astex work). IF just starting out, best to buy a vendor library, e.g. Maybridge or others, which are fully characterized.

2. Screening techniques. NMR and SPR most common. Both very good. Tm - fast, inexpensive and can correlate with x-ray. What to do if no biochemical activity. Might be fine if below sensitivity of biochemical assay, i.e. very small fragment, however if larger fragment, need to understand why not being detected.

3. Potential pitfalls. Make sure library is soluble above assay conditions, i.e. > 1 mM in aqueous buffer (1 - 2% DMSO). Check for aggregation. Run SPR clean screen.

4. Fragment hit follow up. Think of fragments as seeds to identify protein compatible pharmacophore. SAR by catalog of similar fragments or fragments which present a similar pharmacophore is of great value. May find fragments which are much more potent, efficient, or which crystallize (if original was unsuccessful). Good to design diverse library, but similarity in fragments is different than similarity in large molecules, small 1-atom changes can have profound effect on binding mode, potency, etc.

If I missed any other highlights, please add them in the comments, or email me and I can add it in.  

Off-rate screening (ORS)

Molecules that dissociate slowly from their target proteins are potentially useful because they can have a long-lasting effect even if they are rapidly cleared from circulation. However, it is next to impossible to predict whether a molecule will dissociate slowly or not. Moreover, the correlation with binding affinity is poor: weak binders generally don’t stay bound to their target for long, but even tight binders often rapidly dissociate. In the early stages of lead discovery most folk are focused on affinity, and it is usually only much later that kinetics enters in. In a new paper in J. Med. Chem., James Murray, Paul Brough, and colleagues at Vernalis introduce a technique that moves kinetics to the front of the line.

The technique, off-rate screening (ORS), relies on surface plasmon resonance (SPR), which is already commonly used to study binding kinetics. The trick here is using SPR to screen products in unpurified reaction mixtures. An initial fragment with known affinity is modified, and products screened for slower dissociation. Of course, the concentration of desired compound is likely to vary from mixture to mixture, but the great thing about looking at compound dissociation is that it is a zero order reaction: it does not depend on concentration. The researchers use mathematical simulations to show that even if the yield is only 5%, a product with a 10-fold slower dissociation rate constant could still be detected. Since off-rates can vary by orders of magnitude, this is not such a high bar.

Of course, simulations are one thing, but how does the technique actually work in practice? The researchers show examples on two targets, one using some of the early compounds for their HSP90 program, the other some of their PIN1 inhibitors. For PIN1, the researchers resynthesized some of the molecules in plastic tubes, which caused leaching of plastic into the reaction mixtures. Nonetheless, for both proteins the dissociation rate constants measured for unpurified reactions were very close to purified molecules, generally differing by less than 30%.

The researchers also tried subjecting compounds to eleven reaction conditions typically used in medicinal chemistry, evaporating the solvent, and testing the products; the idea was to see if the reagents or other components in the reaction mixture would interfere with the assay. Happily in all cases the dissociation rate constants differed by less than 20%, again pointing to the robustness of ORS.

Of course, as with any technique, there are limitations. Since the screening compounds are not purified from their starting materials, the desired products must dissociate sufficiently slowly from the protein to be distinguishable from other components in the reaction mixture; dissociation rate constants greater than about 1.2 s^-1 appear to be challenging. Also, if the starting material itself has a slow dissociation rate from the protein, it may be difficult to differentiate this from a low yield of slowly dissociating product. The researchers note that both cases could be addressed by changing the temperature, either lowering it to slow the dissociation rate constant or raising it to increase it.

All in all this is a nice approach, and it will be interesting to see how widely it catches on.

Biophysics in the Alsace

Two weeks ago, the first Novalix conference on Biophysics in Drug Discovery was held in Strasbourg.  I was lucky enough to be one of 160 people in attendance (this was largely a european affair, with ~10% of attendees from outside the EU).  The split of attendees was 60/40 industry/academia.  The conference was split into four themed sessions: Biophysical characterization, Mechanistic Analysis, Emerging Technologies, and Biophysical Methods for Identifying Hits and Leads.  This was not a fragment conference, but many of the talks were specifically about fragments, and the rest could be impactful in fragments.  I want to share my impressions/thoughts on the speakers relevant to the readers here.  You can also go to my website to see my thoughts on the speakers not relevant to FBHG. 

Michael Hennig- Roche: His talk discussed the various methods and showed examples for each.  This was a great talk giving a great overview of the various methods available for active follow up.  Specifically fragments: The Roche fragment library is ~5000 compounds.  In terms of QC, 80% of the samples show >85% purity (by LC-UV-MS).  Purity of fragment libraries has been discussed here previously.  For Roche's uses, every fragment hit is followed up by MC and NMR, so a lower threshold of purity will not have a negative impact.  He also presented results from a 2D-HTS.  This was a new concept for me and I found it intriguing.  The basic concept is to graph the results from two screens (or related proteins) to identify compounds that activate one, but not the other, or activate one and stimulate the other, etc.  He also presented direct and in-direct methods using Mass Spec methods.  To me, this area was one of the more fascinating areas discussed at the conference.  Theoretically, this could be applicable to fragments, but I would really like to see specific applications.  Lastly, he spoke on biophysical methods and membrane proteins. 

Rob Cooke- Heptares:  He presented the STaR approach that has been widely published and presented here, here, here, and here.  The talk was very similar to other talks that Heptares and Rob have presented in various fora over the past year.  The main thing that I was taken by was that there was no mention of NMR.

Matthias Frech - Merck: I really enjoyed this talk.  One of the main things I noted was his use of the phrase "hit affirmation".  Confirmation (according to the dictionary) is a piece of corroboration, while affirmation means it is true.  Is this parsing meaning where none exists?  Maybe, but I think it may also inform on mindset.  He said that SPR is the workhorse for FBHG, but they also use NMR, MST, ITC, stop-flow, and X-Ray.  95-98% of their projects are accomplished using SPR and ITC.  However, he stated that SPR is used to rule out compounds, not rule them in.  This is key to the proper use of SPR.  I would be interested to see if anyone else takes this approach.  They use SPR and ITC to obtain the enthalpic and entropic terms for compound binding.  ITC yields the enthalpy, SPR yields the DeltaG et voila, simple math (my favorite kind) yields the entropic term.  One other very interesting item that he noted was that there was no correlation between affirmation rate and target class for 31 projects they undertook (2009-2012).  

 

Tomorrow I will update the Mechanistic Analysis session.  

Slow-off, albeit tight, fragments

Practical Fragments recently discussed binding kinetics, and that got me wondering whether any fragments have slow off-rates. Turns out some do: a January 2012 review of protein-ligand energetics and kinetics in Drug Discovery Today by Sara Núñez and colleagues at Abbott summarized a paper published last October in Eur. J. Med. Chem. by Jos Lange et al. In it, Lange and colleagues extensively characterize six inhibitors of the enzyme D-amino acid oxidase (DAAO), a potential target for schizophrenia.

The researchers use biochemical assays, surface plasmon resonance (SPR), and isothermal titration calorimetry (ITC) to characterize the thermodynamics and kinetics of their inhibitors binding to DAAO. Although all six molecules are fragment-sized, these are not your typical fragments: the weakest has a Kd better than 1 micromolar, and all have ligand efficiencies of 0.79 kcal/mol/atom or better! Three of them are shown below, along with their dissociation constants (determined by ITC) and their dissociation rate constants (determined by SPR).

One interesting aspect of the kinetics is that compound 6 dissociates from the enzyme roughly 50-fold more slowly than compound 3, even though it binds only about 3-fold more tightly. As an interesting aside, compound 1 has a slower on-rate than any of the other molecules, a phenomenon the researchers attribute to tautomerization around the pyrazole.

The researchers go on to measure a number of other properties of these molecules, including Log P, pKa, thermodynamic and kinetic solubility, cell membrane permeability, and in vivo pharmacokinetics. There is a tremendous amount of data here, and it’s a lot of fun to dig into.

With a predicted half-life of more than 2 hours, compound 6 certainly classifies as a slow-off fragment. So is it a better drug? Well, it’s not orally bioavailable, in contrast to some of the other compounds, and it has faster clearance in rodents. Unfortunately the researchers do not report in vivo target modulation, but one has to assume that a schizophrenia drug would need to be oral. Chemists can optimize affinity, thermodynamics, kinetics, and drug-like properties all we want, but the body still has the final say.

Kinetic efficiency and slow-binding fragments

We’ve previously discussed the proliferation of metrics used to evaluate fragments. Ligand efficiency is by far the most popular, and what it and most other measurements have in common is that they represent binding affinity (or inhibition, or some other surrogate). Binding affinity is associated with thermodynamics – how well a molecule binds to a target – but this measure says nothing about how rapidly a molecule associates and dissociates from the target (kinetics). In the November issue of Drug Discovery Today Geoffrey Holdgate and Adrian Gill at AstraZeneca propose a new metric, kinetic efficiency (KE), to address this issue:

KE = τ / (# of heavy atoms) = t1/2 / (0.693 * (# of heavy atoms))
where τ is the residence time or relaxation constant and is, in the simplest case, 1/koff
koff is the dissociation rate constant
and t1/2 is the half-life for dissociation

Why are the kinetics of dissociation important? Holdgate and Gill list a series of drugs for hypertension and note that compounds that remain bound to the receptor longer avoid rapid clearance and thus have superior clinical activity. On the other hand, drugs for schizophrenia that bind the D2 dopamine receptor can cause side effects if they remain bound too long. Thus, optimal kinetic efficiency is case-dependent .

Though kinetics of ligand binding can be assessed with techniques like SPR, this parameter is often ignored. However, as Holdgate and Gill point out, slow-binders are likely to be lead-sized or drug-sized molecules. Indeed, none of the roughly two-dozen examples they present would satisfy the rule of 3.

This raises an interesting question: how often do fragments dissociate slowly? Slowly-dissociating fragments are often flagged as pathological in SPR studies. Intuitively it seems that smaller molecules would have faster kinetics; a small fragment is likely to be able to dart in and out of a protein-binding site more rapidly than a larger molecule that requires some movement on the part of the protein to accommodate its binding. Still, there must be some cases of fragments with slow dissociation rate constants. If you know of any please mention them in the comments section.