01 April 2015

Shapely fragments

Tired of all those planar aromatics in your compound collection? Three-dimensional fragments are all the rage these days, and chemical suppliers are happy to oblige. After the stunning success of their FUNK library, SerpentesOleum has come out with a new offering, Tesseract Products (TP). All of the TP fragments are guaranteed to be nice, plump, and squeezably soft. For example:

Even more exciting, the company has hired a crack team of physicists to produce a line of 4-dimensional fragments with principal moments of inertia greater than 1. Don't delay, order your TP today, and wipe away the 2-D blues!

30 March 2015

Politburo Approved

Viral, tropical diseases are really cool because they have great names. e.g. Dengue or Breakbone Fever or Chikungunya ("that which breaks up").  The great thing about many viral diseases is that they are dependent upon proteases for many things. (And yes, I know how that sounds.)  Proteases have nice, well defined active sites that you can fill quite well and shut them down. In this paper, the authors use fragment-peptide merging to inhibit Dengue protease.  

This is really an extension of previous work.  The original work used capped peptides with a warhead with very good potency (down to 43 nM).  They then investigated retro, retro-inverse, semiretro-inverse, and nonretro di- and tri-peptides.  This lead them to use a tri-peptide (Arg-Lys-Nle) in two generations: first an arylcyanoacrylamide and then to N-substituted 5-arylidenethiazolidinone (thiazolidinediones and rhodanines).  These second generation hybrids had increased membrane permeability, in vitro binding, in cellulo antiviral activity.  Based on docking, they decided to investigate Nle sitting in P1', in contrast to previous site preferences and then merge it with fragments from an optimized capping moiety. 
1.  Starting Point Hybrid Peptide
The investigation of Nle replacements led to the phenylglycine molecule, with 4x greater affinity:
9.  Phenyl-glycine hybrid
They, then chose three hybrids (including 9) and put two different caps on them:
Rhodanine Cap
Acrylamide cap

Compared to the benzoyl cap, the acrylamide was 2x better while the rhodanine was 5x better.  But, wait, doesn't the Politburo condemn all uses of rhodanines?  Of course not.  In this case, the rhodanine was selected through rigorous analysis: and they have selectivity (this assay is fluorogenic).  They are perfectly aware of the general distaste people have for rhodanines and address the concerns. All of this together, leads to the final compound (below).
This is a really nice piece of starting with a tool (covalent peptides) and working to generate drug like molecules with favorable properties. 

25 March 2015

We read these papers so you don't have to

Glycogen Phosphorylase is one of those systems that you hear about all the time; it was the first allosteric enzyme discovered.  It's been discussed here and here previously on this blog.  It is one of those ubiquitous enzymes and has been the subjet of a lot of research looking for allosteric modulators.  The majority of allosteric inhibitors are heterocyclic compounds with a well known history.  This paper wants to add to that history. 
The authors start with what appears to be a dreadful understanding of what fragment-based hit generation is.
"Lead-like discovery refers to the screening of low molecular weight libraries with detection of weak affinities in the high micromolar to millimolar range".
Maybe its just me, but we've been over this before.  Lead-like molecules, as Kubinyi showed, are large and decorated; fragments are not.  So, they got the low molecular weight thing right, but the name of the method wrong. Maybe an error in the proofing...
Starting on previous work, the chose a 21 member heterocycle library (Figure 1.) to investigate a morpholine-based peptide mimetic.
Figure 1.  Fragment Library
Activity was determined by an enzymatic assay with a maximal compound concentration of 222mM.  They also used 22mM, 56 mM, 111mM leading to Table 1 and some crazy SAR (N-Boc-ing 8 yielded 9 with >200x potency).  
Table 1. 
The key compound is 7, with 25 microM IC50;  while 6 (minus the methyl ester) is 1000x less potent.  Strange things are afoot at the Circle K.  They then docked 7 (and a few other "second tier" compounds).  They see "moderate" binding for all compounds; yet, one of these compounds is more than 50x more potent than the others.  We've been down this road before...

23 March 2015

Rad fragments revisited

Two years ago we highlighted a paper in which Cambridge University researchers identified fragments that bind to the protein RAD51, which in turn binds to the protein BRCA2 to protect tumor cells from radiation and chemotherapeutics. In a new paper in ChemMedChem, Marko Hyvönen and colleagues describe how they have grown these fragments into low micromolar binders.

One of the best fragments identified in the previous work was L-tryptophan methyl ester (compound 1), so the researchers naturally tried substituting the methyl group. A phenethyl ester (compound 5c) gave a satisfying 10-fold boost in potency, but this turned out to be the best they could get: shorter or longer linkers were both less active, and modifications around the phenyl ring gave marginal improvements at best. Also, changing the ester to an amide decreased affinity. They were, however, able to improve potency another order of magnitude by acylating the nitrogen (compound 6a).

At the same time, the researchers made a more radical change to the initial fragment by keeping the indole and replacing the rest with a sulfonamide (compound 7a). This also boosted potency. Further optimization of the sulfonamide substituent improved the affinity to low micromolar (compound 7m) and increased ligand efficiency as well.

The original fragments had been characterized crystallographically bound to the protein, but the researchers were unable to obtain structures of the more potent molecules, though they did sometimes see tantalizing hints of electron density. Competition studies with known peptide inhibitors also suggested that the molecules do bind in the same site as the initial fragments.

The thermodynamics of binding were characterized using isothermal titration calorimetry (ITC). Although the initial fragments owed their affinity largely to enthalpic interactions, the more potent molecules were more entropically driven. This, the researchers suggest, could partially account for the failure of crystallography despite extensive efforts: the lipophlic molecules can bind in a variety of conformations.

Some have argued that enthalpic binders should be prioritized, but this study illustrates one of several problems: even if you start with an enthalpic binder, there’s no guarantee it will stay that way during optimization.

This is a nice paper, but I do wonder how much affinity there is to be had at this site on RAD51. Given the micromolar affinity of the natural peptides, nanomolar small-molecule inhibitors may not be possible. Then again, like other difficult PPIs such as MCL-1, perhaps the right molecule just hasn’t been made. How long – and how hard – should you try?

18 March 2015

Mass Spec Screening in Solution

Mass spectrometry is a technique that most people are familiar with, as a QC tool.  It also has been demonstrated as a screening/validation tool.  Native mass spectrometry (nMS) has been discussed here, Weak Affinity Chromatography (WAC) here, and Hydrogen-deuterium exchange (HDX) here.  All of these methods have advantages and disadvantages.  A "new" method is the ligand-observed MS screening (LO-MS).  [I put new in quotes because I know of at least one company that has been using this method for screening for years via a CRO.]

The concept of LO-MS is straight forward (Figure 1) and very similar to WAC.  A mixture of fragments, in this case 384, are mixed with target (NS5B), incubated, and the ultrafiltrated (50kDa cutoff).  This step eliminates the need for the immobilization step in WAC, ensuring the native conformation.  The fragments were at 25 uM, while the target was at 50 uM. 
Figure 1.  Fragments MW 165 and 130 are binders.  MW162 and 150 are not. 
Retained fragments are then dissociated with 90% methanol and those showing intensity higher than the protein-minus control are considered binders (S/N  greater than 10).  In their library, 5% of the compounds were not amenable to mass spec detection, but they included them to increase the complexity of the mixture.  In the end, they ended up with 20 binders in 20 minutes!  They repeated the screen with smaller mixtures (50 and 84 fragments) where they found 12 binders (a subset of the original 20).  As a follow up, they ran the binders by SPR, validating 10 of the binders (50%).  5 out of these 10 gave useable crystals (observable electron density for the fragment) (50%).  They also show how the data can be used to generate Kds (like WAC).

This method raises some issues with me, but first let me say, it sure seems to work, and fast to boot.  From people I know who have used this to screen, they have been very happy.  Here is what bothers me: self-competition in the tube a discussed here and here, this is a non-equilibrium method (variable protein concentration during the ultrafiltration), and it is an indirect method.  For me, I prefer methods that directly detect ligand-target interactions, like NMR, SPR, and nMS.

16 March 2015

Fragments vs p97

The protein p97 is important in regulating protein homeostasis, and thus a potential anti-cancer target. But this is no low-hanging fruit: the protein has three domains and assembles into a hexamer. Two domains, D1 and D2, are ATPases. The third (N) domain binds to other proteins in the cell. All the domains are dynamic and interdependent. Oh, and crystallography is tough. Previous efforts have identified inhibitors of the D2 domain, but not the others. Not to be put off by difficult challenges, a group of researchers at the University of California San Francisco (UCSF) led by Michelle Arkin and Mark Kelly have performed fragment screening against the D1 and N domains, and report their adventures in J. Biomol. Screen.

Within UCSF, the Small Molecule Discovery Center (SMDC) has assembled a fragment library of 2485 commercial compounds from Life, Maybridge, and Asinex. These have an average molecular weight of 207 Da and 15 heavy atoms, with ClogP ~1.5. The researchers used both biophysical and virtual screening.

For the physical screening, the researchers started with surface plasmon resonance (SPR), with each fragment at 0.25 mM. This resulted in 228 primary hits – a fairly high hit rate. Full dose response studies revealed that 160 of theses fragments showed pathological behavior such as concentration-dependent aggregation or superstoichiometric binding. A further 30 showed weak or no binding, 13 were irreversible, and 5 bound nonspecifically to the reference surface, leaving only 20 validated hits which were then repurchased.

The 228 primary hits were also assessed by STD NMR, each at 0.5 mM when possible (some fragments were not sufficiently soluble). Of these, 84 gave a strong STD signal, and 14 of these were also among the 20 SPR-validated hits.

The 20 repurchased fragments were further tested by both SPR and STD NMR, and 13 of them reconfirmed by both methods. The paper includes a table listing all 20 compounds, and one observation that struck me was the fact that all but one of the hits – which had dissociation constants ranging from 0.14 to 1.7 mM – are larger than the library average. Such results could argue for including larger fragments in libraries, though this goes against both molecular complexity theory as well as extensive experience at groups such as Astex.

Next, the researchers sought to discover information on the binding sites. Three fragments could be competed by ADP, suggesting that they bind in the nucleotide-binding site of D1. To narrow things down further, the researchers turned to 13C-1H-methyl-TROSY NMR, in which specific side chain methyl groups of Ile, Leu, Met, Val, and Ala were labeled, and chemical shifts were examined in the presence and absence of fragments. Two of the proposed nucleotide-binding site fragments showed similar shifts as AMP or ADP, further supporting a common binding mode (the third was too weak to test). This was not an easy experiment: the hexamer has a mass of 324 kDa, well above where most people do protein-detected NMR.

Independent of all the biophysical screens, virtual screens were conducted using Glide XP, which suggested that the nucleotide binding site would be the hottest hot spot. Happily, all three fragments that appear to bind to this site scored highly in the in silico work, with two of these within the top 100 fragments. However, the binding sites for the other ten confirmed fragments remain obscure.

This paper serves as a useful guide for how fragment screening is performed on a tough target in a top-tier research group. Although difficult, it is not impossible to advance fragments in the absence of structure. While it remains to be seen whether that will be the case for any of these fragments, the researchers have provided a wealth of data for those who wish to try.

11 March 2015

The Sequel is Never as Good as the Original

We are living in a target-driven environment in Pharma, for both good and bad.  The low-hanging fruit have been plucked and the high-hangers are tough.  But, fragments have proven to be highly utile in liganding these targets.  One drawback with target-based screening is the problem with cellular activity, while it may be easy to generate good activity against the isolated target, in the end you need activity in the cell/animal.  Back in the good ole days, people just skipped the target and went straight into cells: compounds are put on bacterial plates and the microbes die if the compound is anti-microbial.  This is the simplest example of phenotypic screening, the phenotype here being "dead cells". [For a discussion of the history of phenotypic screening, go here.]  Fragments could be the worst case scenario for phenotypic screening as fragment-target interactions are very weak, and very commonly do not exert a biological effect. 

In this paper from Rob Leurs and colleagues, including Iota, the describe a fragment-based phenotypic screen process.  This work is a follow on to previous work from this group discussed here, which I quite liked  So, they have a target (PDEB1) but immediately follow their screening with the phenotypic part.  For the phenotypic screen, they used several different parasitic PDE and MRC5 cell-line as a counter-screen. I won't bore you with any of the experimental details. The compounds are recapitulating known molecules, like benadryl.  Now, I really wanted to like this paper, at least from a process approach.  It appears to my eyes, that all the compounds are pretty much equipotent and cytotoxic.  This is a really disappointing paper in that it doesn't really do anything.  They had shown previously that you could get non-cytotoxic compounds with good inhibition of PDEB1.  They didn't repeat that here.  There is no X-ray, they did before.  The compounds are wholly uninteresting and stretch the imagination to be seen as compounds "with a lot of potential to grow into antiparasitic compounds".

09 March 2015

Are PrATs privileged or pathological?

Pan assay interference compounds – PAINS – have received quite a bit of attention at Practical Fragments. In addition to being a fun topic, the hope is that publicizing them will allow researchers to recognize them before wasting precious resources.

But not all PAINS are created equal. Some, like toxoflavin, simply do not belong in screening libraries due to their tendency to generate reactive oxygen species. I would put alkylidene rhodanines in the same category due to their ability to act as Michael acceptors, their tendency to undergo photochemistry, and their hydrolytic instability. The nice thing about these sorts of molecules is that their clear mechanistic liabilities justify excluding them.

But things are not always so simple, and in a recent paper in J. Med. Chem. Martin Scanlon and co-workers at Monash University, along with J. Willem Nissink at AstraZeneca, describe their experiences with a more ambiguous member of the PAINS tribe: 2-aminothiazoles. (See here for In the Pipeline’s discussion of this paper.)

That 2-aminothiazoles (2-ATs) should be PAINS is not obvious: at least 18 approved drugs contain the substructure. Thus, it was not unreasonable to include 2-ATs in the 1137-fragment library assembled at Monash. But after screening 14 targets by STD-NMR and finding a 2-AT hit in every campaign, the researchers started to become suspicious. They gathered a set of 28 different 2-ATs and screened these against six structurally diverse proteins using surface plasmon resonance (SPR). Many of the 2-ATs bound to 5 of the proteins, and a couple bound to all six. The researchers used 2D-NMR (HSQC-NMR) to further characterize binding and found that the 2-ATs bind to multiple sites on the proteins rather than the desired one-to-one binding mode.

A common source of artifacts is the presence of reactive impurities, so the researchers resynthesized some of the 2-ATs and showed they behave the same, ruling out this mechanism. Solubility was also not a problem. Finally, the ligand-based NMR experiments revealed that the 2-ATs really did appear to be binding to the proteins, ruling out interference from unreacted starting materials or decomposition products.

One structure-activity relationship did emerge: acylation of the amino group dramatically reduced promiscuity of the 2-ATs. However, in the case of 2-ATs with a free amino group, there was little meaningful SAR. Thus, the researchers propose calling these molecules PrATs, or promiscuous 2-aminothiaozles.

Further analysis of high-throughput screening data from the Walter and Eliza Hall Institute and AstraZeneca revealed that 2-ATs were also over-represented among hits. What’s spooky about this result is that most of the screens were done at 10 micromolar – far lower than typical fragment screens.

The researchers freely admit that they have no mechanism for why PrATs bind to so many proteins. I suspect there is something fundamental to be learned about intermolecular interactions here, though how to extract these lessons is beyond me. One gets the impression that the authors themselves have been burned by pursuing PrATs, as they conclude:
On the basis of our findings reported here and our unsuccessful attempts to optimize these fragments against different targets, we have removed 2-ATs from the fragment library.
This paper serves as a thorough, cautionary analysis. As evidenced by multiple approved drugs, PrATs can be advanceable, and we certainly won’t be PAINS-shaming papers that report them as screening hits. If you can advance one to a potent lead, then bless your heart. But be warned that this is likely to be even more difficult than normal.

04 March 2015

Way Down in the X-Ray Weeds

So, what I know about the details of crystallography can fit on the head of a pin...a small pin.  You put pure protein in multiwell plates and then do a huge matrix of crystallization conditions until tiny little crystals form.  Big crystals are best, but you can use tiny crystals or seeds, or with recent advances in technology, to actually collect data.  Then, through some wizardry (some sort of inverse transform) you make spots go to electron density, then with will power and what used to be SGI machines, you thread your protein sequence in, et voila a model of the structure.  I typically don't go for methods papers in fields I have almost no clue in, but this one intrigued me.

This paper aims to increase the efficiency of soaking fragments into crystals to take advantage of 3rd generation synchrotrons. These machines/labs/setups/doohickeys use acoustic droplet injection (ADE), which many people may already be aware of.  In this approach, each fragment soaks into a protein crystal either directly on data collection media or on a moving conveyor belt which then delivers the crystals to the X-ray beam.  The source of inefficiency comes from the time required to soak the fragment in to the crystals (for those where the apparatus is inside the X-ray station. I have no idea what that means, but here is a google image search that might give you an idea.)  A second source is the limit of evaporative dehydration during the fragment soak.  

Using the model system lysozyme and thermolysin the identified factors which can increase efficiency: namely smaller crystals can be used to decrease the soak time.  By small crystals, they are talking things that are 100 microns or less.  The authors go on to state that:
These techniques efficiently use fragment chemicals (~2.5 nL per screened condition), protein (~25 nL per screened condition), space (1120 screened conditions per standard shipping Dewar; no limits using a conveyor belt), and synchrotron beam time (less than 1 second/screened condition).  Evaporative dehydration of the protein crystal limits these fragment screening applications to systems where the fragment soak time is not prohibitive. Slow-binding compounds can be screened (without time constraint) in trays using ADE, but will consume significantly more resources such as purified protein and chemical compounds (~1 µl per screened condition). Hence, it is desirable to identify promising cases where the cost-efficient on-micromesh or on-conveyor soaking methods are adequate.
So, what did I really get out of this paper.  I am amazed by the miniaturization and automation that exists in synchrotrons.  It is really amazing. Its good to get and read the literature for another field.  It can be enlightening.  If I am looking at this correctly, they can screen a 1000 fragments with ~1mg of protein.  With that said, how many people screen for fragments in this way?  It seems not to be resource intensive, if you are sitting at a synchrotron.  But, how much does it cost to sit at that synchrotron?  Are the problems called out here something people encounter every day, or is this a "First World problem" for those sitting at synchrotrons.

What really got me was that the majority of the authors are high school students and undergraduates. This emphasizes to me the commoditization of X-ray, and really all services.  There is a very high level of training that goes in to solving the structure; I get that.  But it seems that many of the steps are commmodities, if you will.  When I was at Merck, they had a directive called (in some form) I-C-E: Innovation-Commoditization-Experimentation.  The concept was the highly trained (and highly paid) scientists needed to focus on innovation.  Once innovation was achieved it led to experimentation (figuring out how to run it routinely).  After that it was a commodity and should be outsourced to enable those scientists to go back to innovating.  It makes sense from a business standpoint, but scary from the scientists standpoint.  I am all for full employment for scientists in industry (trust me on this), but outsourcing can co-exist in industry. Look at the growth in providers from 2011 to 2014. Not sure where I am going with this, but food for thought.

02 March 2015

Fragments vs Factor XIa

Blood clotting is something we’re all familiar with, but the details are devilishly complex; lots of different proteins play a role. Physiologically this makes sense: the many components make for a finely tuned system, and you want clotting to happen when it needs to and then stop. Start too late and you might bleed to death. Start too early (or don’t stop) and you could develop a fatal clot. Not surprisingly, lots of things can go wrong, and many of the enzymes involved are drug targets. In a paper recently published in PLoS One, Ola Fjellström and colleagues at AstraZeneca describe their efforts on one of these.

Factor XI is involved in the “amplification phase” of coagulation, and the activated form (FXIa) is a potential antithrombotic and profibrinolytic target. A high-throughput screen had failed to find anything useful, so the researchers turned to fragments.

The team started with a computational screen of 65,000 in-house compounds with molecular weights < 250 Da. They used Schrödinger’s Glide software and previously determined crystal structures of the protein. The top 1800 fragments were then tested using ligand-detected NMR in pools of 6, with each fragment present at 0.1 mM. The researchers were trying to avoid strongly basic compounds, and they found 13 hits with calculated pKa< 9. Next, 600 structurally related analogs of the hits were screened, resulting in 50 hits total. These were then triaged using inhibition in solution (an SPR technique described here) and taken into crystallography trials. Two fragments gave high-resolution structures and were prioritized. Satisfyingly, the two fragments bound as had been predicted by the initial virtual screen.

Fragment 5 was particularly interesting because it had never been observed as a hit in the S1 pocket of a serine protease. Many enzymes in the coagulation cascade share a conserved S1 pocket. This has a predilection for highly positively charged species, so the neutrality of this fragment was attractive.
Separately, the team found a Bristol-Myers Squibb patent application describing compound 9, which they made and characterized crystallographically. The structure suggested merging a portion of compound 9 with fragment 5, and the resulting compound 13 turned out to be one of the most potent FXIa inhibitors reported.

To better understand the system, the researchers took a deconstruction approach to compound 9, testing the portion (compound 15) that had been used in the merging. This bit has low affinity by itself. Yet, when linked to fragment 5, the resulting compound 13 binds roughly 200-fold more tightly than simple additivity would predict. Similarly dramatic fragment deconstruction results have been reported previously for the related enzymes factor Xa and thrombin.

Unfortunately compound 13 has fairly low membrane permeability, high efflux, and high clearance in rats, though preliminary SAR suggests this is the fault of the Bristol-Myers Squibb piece rather than the new fragment. At any rate, this is another nice example of using fragment screening to replace one portion of a known molecule with a new fragment.

25 February 2015

New PAINS, and their painful mechanisms

Pan-assay interference compounds – PAINS – are a topic that has come up repeatedly at Practical Fragments (see here, here, and here for starters). Indeed, they form the basis of our occasional (and controversial) “PAINS shaming” series (see here, here, here, and here). In a paper recently published online in J. Med. Chem., HTSPains-master Mike Walters (University of Minnesota) and collaborators at the Mayo Clinic College of Medicine and AstraZeneca characterize several new classes of PAINS (also covered at In the Pipeline). I was honored with the invitation to write a Viewpoint on the topic. Since both papers are open-access I’ll just briefly touch on a few key points here.

First, one of the only critics of the PAINS concept is concerned that PAINS were originally defined on the basis of their over-representation as screening hits in one set of assays. The new paper goes beyond empiricism to characterize mechanisms, which involve non-specific reactions with thiols. (The “non-specific” aspect is key to their undesirability, as covalent drugs can be quite attractive.)

Second, just as “not every clam will hurt you”, not every molecule with a PAINS substructure will show activity in every assay. These “structure-interference relationships” (SIR) can be mistaken for “structure-activity relationships” (SAR), making PAINS all the more insidious. The researchers explore some of the reasons for the observed SIR.

Third, one of the saddest parts of the new paper is a list of dozens of references in the supplemental information in which PAINS were reported as screening hits or probes. It’s a safe bet that most – if not all – of these should be disregarded.

Finally, publishing this list of new PAINS will allow people to steer clear of them. To borrow from Hippocrates: chemical space is big, life is short. Why waste time working with chemotypes known to be pathological? 

23 February 2015

Heptares Get Bought

Yesterday brought news that Heptares was purchased by Sosei.  The deal is for 180$MM upfront and 220$MM in royalties.  Similar to the Astex deal, Sosei is not absorbing Heptares, but is keeping them as a wholly owned subsidiary.  In terms of clinical assets, Heptares didn't show up on the 2015 version of fragments in the clinic, but they do have a p1 asset, a M1 agonist.  As if we needed further validation, this deal shows the power of SBDD/FBDD and gives a good idea off how it is valued.  Congratulations to our friends at Heptares.

18 February 2015

19F Target-based Screening Reduced to Practice

If you read this blog you know I love 19F NMR.  I am a big fan of it for ligand based screening or as a secondary screen in target-based mode.  Well, this paper is the first to use target-based NMR to screen small molecules.  Using 3-fluorotyrosine-labeled protein and using what they call Protein observed fluorine NMR (PrOF-NMR), the interrogate a PPI (CBP/p300-KIX) and determine this interaction's ligandability. 

Starting from the Maybridge Ro3 Library, they found 508 19F containing fragments.  These were put into 85 mixtures (5 or 6 compounds each) and screened at 833uM and 2.5 % DMSO (Figure 1, KG-501 is a control compound).  Each experiment was performed in 5 minutes (with a quick reference spectrum) which is faster than SOFAST HSQC (for 15N labeled proteins).  15 mixtures gave hits which upon deconvolution gave 4 actives (>2 SD in chemical shift), a 0.8% active rate.
Figure 1.  Typical 19F Data
 They then titrated the four confirmed fragments to determine the Kd, which for 3 of them was in the mM range.  They followed this up with Analog by Catalog and developed some SAR.  Lastly, they used H-N HSQC to verify that the compounds do bind and where they data shows.  They do. 

Some thoughts on this.  The use of 3FY is only one amino acid that can be used.  Fluorotryptophan can also be used, so this method can easily be applied to other systems.  Secondly, 19F can accomodate much larger pool sizes (within reason).  And there is no reason why both could not be used.  Of course, one of the things not noted here is that they produce single mutants in order to ID each individual residue.  I think you could live without residue specific assignments and still get tremendous value out of this method.  I would be curious what others think.  We bring up impractical tools all the time, so I really want to applaud this paper.  Here is a very practical new method for screening. 

16 February 2015

MELK part 2: fragment deconstruction

Last week we highlighted a paper from Chris Johnson and collaborators at Astex and Janssen in which they used fragment-growing to develop a selective inhibitor of maternal embryonic leucine zipper kinase (MELK). The paper immediately following in ACS Med. Chem. Lett. also describes the team’s efforts to discover MELK inhibitors, but using a very different approach.

In fact, the second paper doesn’t really start from fragments. The researchers were interested in designing compounds that bind MELK in a particular fashion: type II inhibitors fit into the hinge region but also insert themselves deep into a back pocket which is accessible when the so-called DFG-loop swings open (DFG-out). Since Type II inhibitors make more interactions with the kinase, they have the potential to be more selective.

The problem was that all previous crystal structures of MELK were “DFG-in”, so the researchers couldn’t use crystal soaking. Instead, they turned to structure-based design for molecules that would be able to span the hinge region and the back pocket. Happily, they succeeded with compound 2, and further optimization led to the low nanomolar compound 7. Co-crystallization experiments using a related molecule revealed that the compound binds as expected with MELK in the DFG-out conformation.

Compound 7 was tested in a panel of 243 kinases and inhibited 31 of them >50% at 1 µM; besides MELK, six other kinases were inhibited with IC50 values < 100 nM. This isn’t terrible, but it is far from the selectivity seen with MELK-T1, the Type I inhibitor discussed last week. Thus, one can’t assume that Type II binders will necessarily be more selective than Type I binders.

Fragments enter the picture at the very end of the paper, when the researchers “deconstructed” their molecules. Simply removing the aminomethyl group from compound 2 to give compound 8 reduced affinity by more than ten-fold. This was expected because crystallography had already revealed that this moiety makes electrostatic interactions with aspartate and glutamate residues in the protein.

More surprisingly, removing the phenyl group from compound 8 produced a molecule with greater affinity and ligand efficiency than the initial compound 2! The researchers determined the crystal structure of this (compound 9) bound to MELK and found that, in contrast to the other molecules, it binds in the DFG-in conformation. The isoquinoline hinge binder actually binds in a similar manner as it does for its DFG-out binding cousins, it’s just the back pocket that is cut off. The researchers speculate that the DFG-in conformation of the protein may be lower energy, giving the edge to compounds that bind to this state. Whether or not this is the case, it is certainly another reminder of the remarkable plasticity of proteins.

09 February 2015

Fragments vs MELK part 1: a chemical probe

As we recently noted, there are hundreds of human kinases in the human genome, and figuring out what they do is not easy. Selective small molecule inhibitors can probe an uncharacterized kinase’s function, but these don’t exist for the majority of proteins. Such was the case for maternal embryonic leucine zipper kinase (MELK), a potential anti-cancer target. In a recent paper in ACS Med. Chem. Lett., Chris Johnson and collaborators at Astex and Janssen describe how they created one.

The researchers started with a screen of the ~1500 Astex fragment library using both ligand-observed NMR and protein thermal shift assays. Hits were soaked into crystals of MELK, resulting in “a large number” of structures of fragments bound to the hinge-binding region. It is certainly possible to develop selective inhibitors that bind to the hinge region, but doing so is seldom straightforward, and thus the researchers were particularly interested in unusual fragments. Compound 1 caught their attention because it makes just a single hydrogen bond with the hinge region via the carbonyl oxygen in the fragment; most other hinge binders form two or three hydrogen bonds.

Compound 1 was well-positioned for fragment growing, and the addition of a phenol moiety (compound 2) led to a nice boost in potency and maintenance of ligand efficiency. Crystallography revealed that the phenolic oxygen was both a hydrogen bond donor as well as an acceptor, and replacing this moiety with a pyrazole led to compound 4, with slightly better potency. Pyrazoles themselves are often hinge binders (two of Astex’s clinical compounds, AT9283 and AT7519, contain them), but crystallography revealed that the binding orientation remained the same as in the original hit.

Expanding the aliphatic ring of compound 1 by one methylene gave compound 5, with a higher affinity and a slightly better fit to the protein, and adding bits from compound 4 gave mid-nanomolar compound 7, or MELK-T1. Impressively, the researchers improved the ligand efficiency of their molecules even as they became larger.

Finally, the moment of truth: would optimizing a fragment with an unusual hinge-binder lead to a selective inhibitor? The researchers tested MELK-T1 in a panel of 235 kinases, and happily only 6 were inhibited >50% at 1 µM [compound]. Notably, these did not include AMPK, which has 60% identity to MELK in the kinase domain. MELK-T1 was also cell-permeable.

This is a classic example of FBLD enabled by a robust protein construct suitable for crystal soaking. Getting to MELK-T1 required the synthesis of only ~35 compounds, and should lead to some interesting biology. At the same time, the researchers took a different approach to come up with another series of leads, which will be the subject of my next post.

04 February 2015

Structure based Design on Membrane Proteins

GPCRs are a big target class, which have historically be unamenable to FBDD/SBDD.  However, recent work has changed this thinking.   Membrane proteins are being viewed as increasingly ligandable and amenable to FBDD.  In this paper, Vass and colleagues show their computational approach to indentifying multiple fragment binding sites amenable to linking.  

Recent clinical evidence supports the effectiveness of dual dopamine D2 and D3 antagonists or partial agonists in schizophrenia, depression, and bipolar mania. D2 antagonism is required for the antipsychotic effect, and D3 antagonism contributes to cognitive enhancement and reduced catalepsy.  Dual acting compounds should show higher activity to D3 than D2 (due to differential expression levels).  To this end, they apply their sequential docking protocol to identify potential points for fragment linking on the D3 crystal structure and D2 homology model.  These two targets have almost identical primary binding sites, but selectivity can be modulated through the secondary site.

In short, their in house fragment library consisted of 196 amine containing fragments for the primary site.  Second library of 266 fragments of cyclohexyl or piperidines.  Then, the first library was
docked to the apo receptor structures,then the docking poses were merged with the receptor, new grids were constructed including the merged ligands, and the second fragment library was docked to the partially occupied binding sites.  
Table 1.
As shown in Table 1, they synthesized three of their compounds and did generate potent and selective D3/D2 antagonists.  Linking is hard.   It still comes down to the right linker and all that entails.  Finding that right linker is made much easier by having structural data, as shown here.  This is a nice example of experimentally verifying in silico predictions. 

02 February 2015

Fragments vs DsbA: targeting bacterial virulence

The quest for new antibacterial agents can seem quixotic: no sooner have you found a killer molecule than the bugs have developed resistance to it. Evolution is hard to beat, particularly when it comes down to life or death. But what if you could lower the stakes? Many bacteria express virulence factors that are not essential for survival but are important for colonizing their host. Perhaps targeting these would be less prone to generating resistance.

Virulence factors often contain disulfide bonds, and the bacterial protein DsbA is essential for catalyzing their formation. In a paper published recently in Angew. Chem. Int. Ed., Begoña Heras (formerly University of Queensland), Jamie Simpson and Martin Scanlon (Monash University) and collaborators describe a fragment-based approach against the E. coli. version of this target. (See also here for Derek Lowe’s thoughts.)

The researchers started with an STD NMR screen of an 1132 fragment library from Maybridge, with compounds in pools of 3 to 5 (each at 0.3 mM). This yielded 171 hits, 37 of which showed appreciable chemical shift perturbations (CSPs) in a two-dimensional HSQC 15N-1H NMR assay. All of these were relatively weak, with none showing saturation at 1 mM fragment concentration, but they all appeared to be binding in a hydrophobic groove adjacent to the active site.

The 37 hits clustered into eight different structural subclasses, one of which – the phenylthiazoles – is described in detail. The Monash fragment library was designed with SAR-by-catalog in mind, and 22 commercial analogs were purchased and tested in the HSQC assay to assess the SAR. Several of the compounds were soaked into crystals of DsbA, in one case leading to a structure in which two fragments were bound stacked on top of each other in the hydrophobic groove. However, this binding mode was inconsistent with the NMR data, and indeed co-crystallography of the same fragment revealed a 1:1 complex with the protein, also in the hydrophobic groove. (As an aside, this is an interesting case of crystal soaking and co-crystallization giving different results; are readers aware of others?)

The crystal structure was used to inform fragment-growing, ultimately leading to molecules with dissociation constants around 0.2 mM as assessed by surface plasmon resonance and with similar IC50 values in a functional assay. One of these compounds was also tested against E. coli. DsbA is not needed for bacterial growth in rich media but is necessary for motility, and happily the assays showed just this – the compound did not affect growth but did inhibit cell motility.

Although the molecules are still too weak to answer the question of whether targeting DsbA will be a viable antibacterial strategy in vivo, this paper presents promising starting points, along with a wealth of data (including 78 pages of supporting information!) And if you want to learn more, Martin Scanlon is one of the organizers of the FBLD symposium at Pacifichem this December – so you can ask him questions in person in Honolulu!

28 January 2015

Get to Know Your Compounds

One of the first fragment screens I was ever involved with had RNA as the target (this is back when people did anti-bacterial research).  Because of that, I always try to write about targets, not proteins when referring to generic things we wish to find ligands for.  Nucleic acids have secondary and tertiary structure, just like proteins, and thus have ligandable pockets.  We have covered RNA as a target previously.  Well, we get to add another paper to the list.

In this paper from researchers at Goethe-Universität Frankfurt am Main present their results on HIV Tat-TAR.  This target was discussed over three years ago.  I am not particularly impressed with the compounds or the work (even though it included RNA NMR).  I was more impressed with comment made in the paper which hint at the kind of compound understanding we often cite as lacking from academic papers.

First, let's get to the guts of the paper.  They have been trying to identify ligands to this target for years, yielding nanomolar affinities but limited specificity.  Moving to fragments when all else fails, they decided to utilize very simple fragments: benzenes and amines, amidines, or guanidines able to be protonated at physiological pH.  Their fragments were screened in a fluorescent Tat-TAR-peptide assay.   Figure 1 shows the compounds tested.
Figure 1.  Compounds tested.  IC50s shown in parentheses. 
Cpds 1-6 were inactive, but cpd 7 looked promising...at first glance.  As the authors state:
"However, the IC50 value of this compound improves steadily when aqueous solutions are kept under air.  This effect was also found with other compounds, for example tetraaminoquinazoline 23.  The electron rich heterocycles in particular have the tendency to produce false positive results, presumably by forming positively charged oligomers."
I presume that they ran the assay and a few days later went back to re-test the compounds and saw anomolous results.  What really strikes me is that with a 7 mM IC50 upon retesting they saw a number sufficiently different (and that they trusted) to flag it.  They also note that such compounds must be carefully recrystallized and fresh powders ONLY used.   

The rest of the story is not nearly as interesting.  They performed 1H NMR titrations and 2D NOESY to confirm that these compounds are binding to the RNA.  They do some SAR and re-discover cpd 22, a known Tat-TAR inhibitor, that has already been patented.
So, what do we learn here? Understanding your fragments and their potential liabilities in your assay is crucial. 

26 January 2015

Fragments vs PKCθ, selectively

There are more than 500 protein kinases in the human genome, many of which have been tackled with fragments – sometimes all the way to the clinic. Within the universe of kinases, the dozen different isoforms of protein kinase C (PKC) provide an interesting challenge. For example, PKCθ is important in T cell signaling and thus has potential for treating autoimmune and inflammatory disease, but one needs to steer clear of isoforms important for heart function, such as PKCα. In two recent papers in J. Med. Chem., Dawn George and collaborators at AbbVie, WuXi, and Inventiva describe their efforts towards this goal.

The first paper starts as many fragment stories do: a high-throughput screen had come up largely empty. The AbbVie (née Abbott) team had previously constructed a collection of fragment-sized kinase hinge binders, and after screening ~250 of these at 300 µM in a fluorescence (TR-FRET) assay they selected compound 1 because of its structural novelty and ligand efficiency.

Modeling suggested multiple possible binding modes. Crystallography for PKCθ is difficult, but the researchers were able to obtain a structure of the compound bound to a different kinase, FAK. This suggested introducing a positively charged moiety to target an aspartic acid residue in PKCθ, leading to the more potent compound 15a. Additional optimization led ultimately to compound 41, which had moderate potency in cell-based assays, good pharmacokinetics, and 74-fold selectivity against PKCα. The compound also showed activity in a mouse arthritis model, but only at high doses, and was toxic at a slightly higher dose.

That’s where the second paper picks up. The researchers thought that by improving the pharmacokinetics they could lower the dose of the compound required, thereby reducing the potential for off-target effects. By now they had been able to obtain co-crystal structures of some of the more potent compounds bound to PKCθ, which confirmed the proposed binding mode and also gave additional ideas as to how to proceed. Extensive medicinal chemistry ultimately led to compound 17l, with low nanomolar biochemical and cell-based activity as well as good pharmacokinetics.

Unfortunately, this compound did not give stellar efficacy results in the mouse arthritis model. Also, this compound and several others appeared to be toxic to mice, with effects ranging from lethargy to seizures to death. The compounds were screened against panels of kinases and other receptors to try to find the source of these effects, but all to no avail; the compounds were fairly selective. This one-two punch of limited efficacy and unpredictable toxicity led to the termination of the PKCθ program.

These two papers reveal yet again that fragment-based lead discovery is often just the beginning of an arduous medicinal chemistry journey that can lead a long way from Valinor. The final destination here proved to be a dead end, but at least a useful one: it shows that PKCθ is certainly not a straightforward target for arthritis, or perhaps any indication. Kudos to the researchers for publishing this story so other scientists will not have to take the same journey. And at the very least, this compound is a useful probe for dissecting the biology of PKCθ.

21 January 2015

Not Every Clam will Hurt You

I grew up on a wonderful little island called Jamestown (although technically it is Conanicut island and the town is Jamestown).  It was a great place to grow up, especially because in the summer we lived walking distance to the beach.  One of the very cool things about the beach is that it has an awesome sand bar that pokes up at low tide.  That was the most fun part of the beach to me.  One of the things we did was stand on the sand bar and dig our feet into it.  You scrunch your toes into the sand until you hit something hard.  Then you excavate with your toes around it.  If you got a foot or so down (this took some patience) and got lucky you would find a quahog.  Thems is good eating.  Many an hour was spent doing this and bringing home dinner.  Sometimes, you found something hard and started more excavation around it...and WHAM!  Not a quahog, but a razor clam instead! There goes your day as blood starts gushing out of your foot stuck in a foot of mud.  You can come up with a different approach to find the clam, but you still get hurt by razor clams.  Eventually, you give up digging for clams with your feet because you hit one too many razor clams and you get your clams from Zeek's Creek Bait Shop.

We here at Practical Fragments have a great job, we get to pontificate on fragment papers.  As most people know, its Good Cop (Dan)/Bad Cop (Me) by and large.  It works for us and the blog gets read by more than our mothers.  But this is an opinion blog, and as everyone knows (G-rated version): Opinions are like belly buttons, everyone has one.  We welcome contrary opinions, sometimes even try to provoke them.  Dan and I do very little coordinating for this blog beyond the "I will have something for Monday".  So, when we both find something that bothers us, well that's worth discussion.  One topic in particular Dan and I have found is PAINS (Pan Assay INterference Compounds).

PAINS are gaining traction as things to avoid in screening collections; there's even a Facebook page.  The literature is pretty clear as to what these are and why they are bad.  In my eyes, I am fine just removing them all from my screening deck and being done with them.  In fragment space, there is MORE than enough other compounds that I don't worry about missing whatever chemical space they live in.  However, as I have often said, a fragment is like pornography, the viewer knows it when they see it.  As you may know, I am not one for hard and fast rules.  If you want to keep PAINS-like compounds in your collection, fine by me.  BUT, you must be aware that they are PAINS.  You must know that they must be kept to a higher standard of evidence, you must do more controls, etc. And of course, if you are making tools then it doesn't matter if it is a PAIN (Dan and I disagree here.) 

So, Practical Fragments gadfly Pete Kenny has a post up at his (recently renamed blog) about PAINS.  In it, he takes Practical Fragments to the woodshed over PAINS, even though his main point is about how we make decisions on data.  He starts his commentary by pointing to this post and calling it a "vapid rant".  As noted in the comments to my post Pete immediately took exception to it believing the burden of proof should be on the blogger to demonstrate the guilt of the compound(s) in question.  He also cites this post as one that should be wary of calling something crap or pollution.  He then goes in to the ontogeny of PAINS and raises some points:
  • PAINS study is irreproducible because structures and targets are not revealed
  • Only 6 HTS campaigns were analyzed when 40+ were available
  • All screens used Alpha-Screen, so this may not be very "PAN"
He then goes deep into the actual structure of rhodanines and how some are good, or less bad.  I think Pete has lost the forest for the trees, or shrubs.  Its not that there are probably some rhodanines that are NOT bad actors; but we know many are, and these require a higher level of confirmation than other compound classes.  Not every clam you dig for is going to slice your foot open, but when enough do, but after enough do, you change your approach.

19 January 2015

Fragments vs HSP90: Nerviano’s turn

HSP90, an oncology target, is one of those proteins that seems tailor-made for fragments: it has an active site with a predilection for small molecules, it’s easy to work with, and it crystallizes readily. Indeed, at least two fragment-derived molecules targeting this protein have advanced to Phase 2 clinical trials. In a recent Bioorg. Med. Chem. paper, Elena Casale, Francesco Casuscelli, and colleagues at Nerviano describe their efforts against this target.

The researchers started by identifying a fluorinated probe molecule that they could use in a Fluorine chemical shift Anisotropy and eXchange for Screening (FAXS) assay. This is an NMR-based competition method, in which fragments are screened to find those that displace a known ligand, in this case one that binds in the active site. A total of 1200 fragments were screened in pools of 10, each at the relatively low concentration of 50 micromolar. Nonetheless, 23 hits were found, four of which were characterized crystallographically bound to the protein.

Fragment 3 was among the more interesting, both because of its high ligand efficiency as well as its structural novelty. SAR-by-catalog failed to find anything better from 20 compounds tested, and initial fragment growing also proved disappointing. However, a closer inspection of the crystal structure (cyan) revealed the possibility of linking the fragment to the well-known HSP90 fragment resorcinol. This led to compound 8b, which binds about 5-fold more tightly. Crystallography revealed that the molecule (magenta) also binds as expected.

However, the team wisely chose to test synthetic intermediate 7h (in which the hydroxyl groups were still methylated) and this turned out to be even more active than the designed compound. Since the hydroxyls of the resorcinol are essential for binding in other lead series, the team solved the crystal structure of compound 7h (green) and was surprised to find that it binds in a completely different manner than compound 8b; the ligand essentially flips over.
This discovery led to a change in direction for medicinal chemistry, leading ultimately to the low nanomolar compound 12a. Unfortunately this molecule had only modest cell-based activity and was metabolically unstable.

This is a solid, nuts-and-bolts sort of story. Although it does not conclude with a clinical candidate, it does provide a useful window into how fragment-based methods are applied in industry. It is also a reminder to screen all your intermediates and to remember that even subtle changes to a molecule may have dramatic effects on its binding mode. Those surprising shifts can point the way to promising chemical space.

14 January 2015

A Great New Tool....for what?

As has been noted here, frequently, is that in silico design of fragments is very hard, fraught with problems, and often leads to crap.  As was pointed out elsewhere recently, computational tools are getting more powerful, but still don't have chemical intuition leading to suspect structures.  I am assuming that computational scientists have heard the critiques because we are seeing better and better work, with more experimental verification.  Now, what about better structures?  In this paper from Kaken Pharmaceutical and Toyohashi University of Technology, the propose a way to do this.  

In silico tools can be divided into two classes, structure-based and ligand-based design (TOPAS and Flux are two examples of the latter).  These methods are based upon biological evolution: reproduction, mutation, cross-over, and selection.  Mutation and cross-over are vital for creating new chemical structures.  Mutation can be atom or fragment-based.  In a previous study by these authors, the atom-based method was used for the mutation, in which an atom is modified into another atom to explore the chemical space. The method often resulted in a lot of unfavorable structures that contained invalid hetero−hetero

atom bonds such as O−O and N−F. The fragment mutation approach avoids this problem, especially when the fragments are from known molecules (this assumes they were synthesized and thus could be again). This is one key to their approach: chemical feasibility is considered.

Figure 1.
The method (Figure 1) uses a known molecule to "navigate a chemical space to be explored." [I love this phrase, but immediately I think of this.]  The reference molecule is also used to generate the seed fragments (Figure 2), which can be rings, linkers, or side chains.  
Figure 2
 With a good set of seeds, connection rules, and so forth, the key is the mutation and cross-over events.  A parent molecule is randomly selected and then one of three operations occurs: 1. add a fragment, 2. remove a fragment, or 3. change a fragment.  For "Add Fragment", if the base fragment is ring, then a new linker, side chain, or ring is chosen.  If the base fragment is linker or side chain, then a ring is added. "Remove fragment" removes a terminal fragment.  "Replace fragment" is a fragment for fragment swap (Figure 3). The cross-over function is also shown in Figure 3. 
Figure 3
Then they used this protocol to design ligands against GPCR (AA2A and 5HT1A). 
Figure 4.
Figure 4 shows some of the results against AA2A.  They were able to generate a molecule that is very similar to a known active and because of the generation of the fragments these are all presume to be chemically feasible.  
So, my first complaint here is where's the experimental verification?  OK, this is not a medchem journal, but still...  I am not nearly as savvy as some of our regular readers, but I am completely missing the forest for the trees here.  This paper first struck me as pretty neat, but then the "neat-o" factor fell away and I was left asking "what is it for?"  To me, this would seem to be a patent-busting tool.  We need to generate a structure that is very similar to billion dollar compound A, but it cannot contain fragments X, Y, and Z.  Is this better than locking your favorite medchemists in a room with a few pads of paper?  I am not being flippant here.  If I am missing something, please let me know in the comments.

12 January 2015

Choosing fragments and assays

One of the advantages of running lots of fragment screens is that it generates lots of data that you can mine for general trends and insights. Astex and Vernalis have both done this; in a paper just published online in J. Biomol. Screen. Peter Kutchukian and (former) colleagues at Novartis provide their own meta-analysis of 35 fragment screening campaigns.

The Novartis fragment library consists of 1400 fragments with molecular weights ranging from 102 to 306 Da and logP values from -2.19 to 3.9. This library has been screened against dozens of targets using a variety of different methods. The researchers looked at the hit rates and used Bayesian methods to try to answer three broad questions.

What makes a fragment amenable for fragment-based screening?
Many people have found that some fragments hit many targets while others hit none, and the results here are no different. Over a set of 20 targets, only 37% of fragments came up as a hit, as opposed to the 54% that would be expected if the odds of hitting a target were the same for all fragments (and using the hit rates actually observed). Correspondingly, some fragments hit more targets than expected. Indeed, 1.4% hit six or more, which is orders of magnitude more than would be expected by chance. Given justifiable concerns about artifacts, one might be tempted to dismiss these hits, but the researchers found that these frequent hitters turn out to be more likely to generate crystal structures than other active fragments. In other words, these are privileged fragments (think 7-azaindole).

Do these privileged fragments have anything in common? Previous work from Astex and Vernalis has suggested that fragment hits tend to be slightly more lipophilic than non-hits, and this trend is all the more apparent here. In fact, fragments that hit more than five targets had a median logP of 2.47 versus 1.45 for fragments that hit just a single target. Promiscuous fragments also tended to be slightly larger than other fragments, in contradiction to the molecular complexity hypothesis. They also tended to have more aromatic bonds, fewer rotatable bonds, and higher solubility.

How do hits from different fragment screening technologies and target classes compare with each other?
Do different target classes find different sets of hits? An analysis of substructures identified in hits against various target classes suggests the answer is yes. Certain substructures are preferred by kinases, for example, while other substructures are preferred by serine proteases. This suggests that building fragment libraries specific to a target class may be productive, though certainly not essential.

Regarding screening technologies, the researchers examined both biophysical (for example NMR, SPR, and DSF) as well as biochemical (such as fluorescence) assays. In general, the hit rates were similar for different technologies, with two exceptions. In SPR, a number of fragments nonspecifically interacted with the surface of the chip, giving a higher number of false positives. On the other hand, DSF gave an anomalously low hit rate, and on closer inspection the researchers found that about 1% of the fragment library appeared to denature proteins.

Interestingly, there was less overlap of hits between biophysical methods and biochemical methods than among biophysical methods or among biochemical methods. In other words, hits from an NMR (biophysical) screen were less likely to be found in a fluorescence (biochemical) screen than in an SPR (biophysical) screen. This is similar to the results of a previous study, though not stated explicitly there.

What is the best way to pair FBS assay technologies?
Given this finding, the researchers suggest that, to find the greatest number of hits, it is best to pair a biochemical method with a biophysical method. Of course, this assumes that the goal is to find as many hits as possible, but these may come at the expense of false positives. Still, if you’re going after a tough target, you want to find every possible hit you can. And if you are more interested in weeding out false positives than finding every viable hit, choosing fragments that hit in both a biochemical and a biophysical assay is probably a good starting point.

This is a fascinating paper and contains far more data than can be practically summarized here. It will be fun to see whether similar analyses, from different organizations, come to similar conclusions.