A sharp NMR trick for rapidly measuring affinities

As noted in our poll last year, ligand-detected NMR ranks among the most popular fragment-finding approaches. The various methods are able to detect even weak binders, so determining affinities is important to effectively prioritize hits. This, however, can be time-consuming. In a recent J. Am. Chem. Soc. paper, Ridvan Nepravishta, Dušan Uhrín, and collaborators at CRUK Scotland Institute, University of Edinburgh, and Universidad de Sevilla present a clever way to speed up the process.

 

Normally, NMR spectra of small molecules show multiple spectral lines, with each line corresponding to a different atom or atoms (typically protons). Indeed, depending on the details, the signal from a single proton might be split into multiple peaks. All these signals are great for understanding the details of individual atoms, but the more lines there are, the lower the signal to noise ratio. For maximum sensitivity it would be nice to combine all the lines from all the atoms in a given molecule into a single, intense singlet. This is exactly what the researchers have done.

 

The approach is called Sensitive, Homogeneous And Resolved PEaks in Real time, or SHARPER. For the NMR aficionados out there, “when placed before the acquisition of the NMR signal, a train of spin-echoes in the form of the Carr-Purcell-Meiboom-Gill (CPMG) pulse sequence suppresses evolution due to chemical shifts and J couplings…. All these attributes of the CPMG pulse sequence are maintained when the spin-echo train is employed during the acquisition of the NMR signal. However, this time, the outcome is not a regular spectrum, but under certain conditions, a single spectral line formed as a sum of Lorentzian lines of contributing spins.”

 

The researchers initially applied SHARPER to two commonly used ligand-detected methods: ¹H STD, which we wrote about here, and ¹H CPMG, which we wrote about here. The first test system was human serum albumin (HSA) binding to naproxen. Keeping protein concentration constant at 9 µM and varying ligand concentration gave similar K_D values (210-280 µM) for standard STD, STD SHARPER, and CPMG SHARPER (conventional CPMG failed due to insensitivity at lower ligand concentrations). These values are an order of magnitude higher than those reported using SPR and ITC (25 and 10 µM, respectively) because of the high protein and ligand concentrations needed for conventional NMR approaches; when the SHARPER experiments were rerun at 1 µM HSA, the K_D values were 39 µM. Several other HSA ligands also gave good agreement with the literature.

 

Next, the researchers applied STD SHARPER to the anti-cancer target fascin, which we wrote about in 2019. An examination of 11 ligands from that study gave good agreement with the published dissociation constants. Importantly, SHARPER was faster than conventional approaches, with 15 K_D determinations per day instead of four.

 

Not content with this four-fold improvement in throughput, the researchers developed a new experiment based on line broadening called ¹H LB SHARPER. This allows the determination of 48 dissociation constants per day, and the results for HSA and fascin agreed with the other methods.

 

One of the most time-consuming aspects of most NMR-based affinity measurements is preparing and analyzing samples at multiple ligand concentrations, so the researchers turned to machine learning to choose which ligand concentrations would be most informative and choose just two of them rather than the six or more commonly used. This worked too, thereby potentially increasing throughput to 144 dissociation constants per day.

 

The researchers suggest that SHARPER could also be applied to some of the other recent NMR techniques we’ve discussed, such as PEARLScreeen and photo-CIDNP. Although I always emphasize that I’m no NMR spectroscopist, this strikes me as a neat, practical approach. What do you think?

Fishing for pearls more efficiently with a new NMR method

NMR is the most venerable approach for finding fragments, and ligand-detected NMR is still among the more popular methods. But the amount of protein required for a full fragment library screen can be a limitation, particularly for more challenging targets. A new paper in Angew. Chem. Int. Ed. by Alvar Gossert and collaborators at ETH Zürich, Bruker, and Karlsruhe Institute of Technology provides a new, less protein-intensive approach.

 

I’ll preface the next paragraph by admitting that not only am I no spectroscopist, I don’t even play one on TV. So, spectroscopy-savvy readers, please feel free to provide more details in the comments, especially if I get something wrong. For fellow non-spectroscopists, the takeaway is that clever NMR tricks increase sensitivity.

 

PEARLScreen, short for Perfect Echo for Advanced Relaxation-based Ligand Screen, is related to the classic Carr-Purcell-Meiboom-Gill (CPMG, or T_1ρ) method, which we wrote about most recently here. As in that older method, PEARLScreen relies on the decrease in signal intensity of a ligand that binds to a protein. This is due to slower tumbling of the bound ligand, resulting in faster relaxation of excited protons (see here). Lengthening the time between excitation and measurement should in theory boost contrast between bound and free ligands, but various technical challenges impede this in practice. PEARLScreen overcomes these challenges using “a perfect echo pulse train with water suppression by excitation sculpting.” In addition to lengthening the relaxation delay, PEARLScreen also allows exchange broadening to occur between the ligand and protein, further increasing sensitivity.

 

The researchers simulated multiple conditions to optimize various parameters, and then experimentally tested PEARLScreen on four different proteins with three types of NMR instruments, starting with a standard high-end 600 MHz.

 

The first protein-ligand pair was trypsin binding to a known benzamidine fragment. This interaction was detectable using a standard T_1ρ experiment with 200 µM ligand and 20 µM protein. Using PEARLScreen, the researchers could reduce the protein concentration to 1 µM while maintaining similar signal to noise .

 

Next, they screened 94 fragments in pools of 8 against three different proteins: PPAT, Abl, and FKBP. In all cases PEARLScreen was more sensitive than T_1ρ, allowing screening at 2.5 µM rather than 20 µM protein. PEARLScreen was also more sensitive than the two other most common ligand-detected NMR methods, STD and WaterLOGSY.

 

We wrote recently about benchtop NMR, and the researchers found that PEARLScreen was also more sensitive than a T_1ρ experiment on an 80 MHz instrument, though the difference was not as dramatic as on the 600 MHz machine. On the other hand, on a 1.2 GHz instrument PEARLScreen was so sensitive that the researchers could screen mixtures of 16 fragments with just 1 µM protein.

 

This is a neat paper, which confidently concludes that “due to the superior sensitivity of the PEARLScreen compared to all established screening experiments at standard fields, we expect it to become the standard experiment for ¹H-detected ligand screening.” We look forward to hearing how it performs for others.

The EU-OPENSCREEN fragment library

A well-curated fragment library is usually the starting point for fragment-based lead discovery, and not an insignificant investment. If you are just starting out you may want to use an existing library. One such option is described in an (open-access) paper in RSC Med. Chem. by Jordi Mestres and collaborators at IMIM Hospital del Mar Medical Research Institute and across Europe.

 

The EU-OPENSCREEN European Research Infrastructure Consortium (ERIC) allows researchers to access early lead discovery and chemistry resources. Among other components, it includes a set of more than 96,000 compounds for high-throughput screening, the European Chemical Biology Library, or ECBL. To complement this, the researchers have developed what they call the European Fragment Screening Library, or EFSL.

 

Recognizing that rapid follow-up is a critical next step in fragment-based lead discovery, the researchers designed EFSL based on ECBL. They did this by choosing fragments commercially available from Enamine that were sub-structures of ECBL members. Fragments were chosen to represent as much of the ECBL as possible, as well as for rule-of-three compliance. Fragments with multiple vectors for growing were also prioritized, similar to the “sociable fragments” concept we wrote about here. Finally, a set of 88 very small “minifrags” were also included.

 

Fragments were dissolved in deuterated DMSO at 100 mM (or 1000 mM for minifrags). Solubility and integrity were assessed at 1 mM (or 10 mM for minifrags) in PBS using ¹H-NMR using an internal standard; those with solubility < 0.2 mM were rejected, as were those with missing or extra peaks in the NMR spectra. Of 1056 compounds tested, 913 passed these QC criteria.

 

The EFSL is available for screening (via grant applications), and the paper summarizes the results of eight screens performed over two years using a range of detection technologies including crystallography, ligand-detected NMR, small-angle X-ray scattering, thermal shift, and BLI. Hit rates ranged form just 0.1% to 31.3%, though in the last case only a small subset of the library was tested.

 

After fragment screening and confirmation, four of the projects tested larger compounds from the ECBL in follow-up studies, and two were able to identify hits. One project targeting a bacterial beta-ketoacyl-ACP synthase 2 (FabF) used BLI to identify a fragment with a dissociation constant of 35 µM. Of the 147 compounds related compounds from the ECBL, two had slightly higher affinity, albeit at the expense of lower ligand efficiency. Perhaps exploring Enamine REAL Space as in this example would be more effective at finding significantly more potent molecules.

 

In summary, the EFSL seems to be a useful resource, particularly for academic labs. If you’ve got a target and no internal fragment-screening capabilities, it might be worth putting in an application. 

256th American Chemical Society National Meeting

This week thousands of chemists converged on the venerable city of Boston for the Fall National ACS meeting. One brief but rich symposium was entitled “Best practices in fragment-based drug design,” organized by Amy Hart, David Marcoux, and Heidi Perez (BMS).

After an introductory presentation by me, Anil Padyana described FBDD at Agios. The company is focused on metabolic enzymes, many of which have dynamic, shallow, and polar active sites – challenging even for fragments! Indeed, a summary of 11 targets screened using a variety of methods revealed generally low hit rates, usually < 3%. The company’s first approved drug came out of an HTS screen against IDH2 of 80,000 compounds that yielded just 24 hits. The molecule that ultimately led to enasidenib was essentially a (large) fragment, with 21 atoms. Agios’ current fragment library is just over 5000 about 10,000 molecules, though they are in the process of expanding this to 20,000 – perhaps part of a general trend. Given the history of enasidenib, they are including molecules beyond the rule of 3, with an upper molecular weight limit of 350 Da, far higher than most respondents in our recent poll.

Cullen Cavallaro presented an early, though still unpublished, FBDD story from BMS: KAT II, a brain enzyme implicated in schizophrenia. Screening 3700 fragments using NMR, SPR, and TSA yielded 236 hits, only 6 of which were common to all methods. All 236 hits were soaked into crystals of KAT II, resulting in 43 structures, 13 of which bound in the active site. Strikingly, 12 of these contained carboxylic acids, which generally don’t cross the blood brain barrier. The lucky thirteenth fragment showed no activity in an enzymatic assay, no thermal stabilization, and only a marginal STD NMR signal. However, through a combination of library synthesis and structure-based design the researchers were able to obtain nanomolar inhibitors. Unfortunately the project was stopped when BMS exited neuroscience.

Anna Vulpetti provided an overview of work done by her and her Novartis colleagues to discover inhibitors of Factor D. A high-throughput screen of the serine protease didn’t yield anything useful, but a combination of fragment screening and structure-based design led to multiple series of inhibitors. Anna is a proponent of fluorine NMR, and Novartis has recently expanded its fluorinated fragment library to 4000 members. Like Agios, they have chosen to include some larger fragments, up to 350 Da.

Finally, David Norton described the initial work done at Astex to discover an orally available ERK1/2 inhibitor, which entered phase 1/2 clinical trials in May of this year. We highlighted some of this work a couple months ago so I won’t cover it in detail, but among other lessons David emphasized the importance of initial fragment optimization before starting to grow.

There were plenty of fragment talks outside the symposium too. Last year we highlighted Ben Cravatt’s strategy for performing fragment screening in cells. Chris Parker, the first author on that paper, has just launched his independent academic career at Scripps Florida, and provided an update. Chris noted that, for phenotypic screening, the approach is essentially a target-finding method, and indeed more than 4000 proteins have been identified, varying over five orders of magnitude in abundance. Having proper controls is critical, and recent efforts include screening pairs of enantiomeric fragments and looking for differences.

Taekyu Lee provided an update of the Vanderbilt MCL-1 program, most recently described in this paper. Some of the molecules shown have low picomolar affinity, mid nanomolar cell activity, and are more than 10,000-fold selective for MCL-1 over BCL-2 and BCL-x_L. The program was partnered with Boehringer Ingelheim earlier this year, and they’ve got competition: four other molecules have entered the clinic.

Covalent fragments were also a theme. Peter Wipf (University of Pittsburgh) described the construction of a 300 compound “mercaptophilic” library. In contrast to other academic reactive fragment libraries we’ve covered (see here, here, and here), this one contains a wide variety of different warheads with varying reactivities.

Finally, Jeff Neitz (UCSF) described efforts against Taspase-1, which is involved in cancer cell proliferation. A high-throughput screen of 242,000 molecules yielded seven chemical series – all of which ultimately proved to be artifacts. The enzyme is a threonine protease but contains a cysteine residue near the active site, so the researchers conducted a Tethering screen with 1280 disulfide-containing molecules, which led to 64 hits in five classes. Converting the disulfide to more drug-like warheads ultimately led to nanomolar molecules with cell-based activity, and the researchers even had some success removing the warhead entirely.

If you missed the meeting, you still have time to catch what should be an epic conference: FBLD 2018 returns to San Diego where it originated ten years ago. People still talk fondly about that meeting, so don’t miss this one!

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.  

Poll Results - Hurray for Diversity

In our latest poll, we asked what kind of libraries people like, giving three options:

• I like a maximal diverse library (SAR comes from follow up)    
• I like diversity, but not at the expense of SAR (follow up is easier with some SAR)              
• My target is teflon so any active fragment is welcome news.   

 60% of respondents like a maximally diverse library, 31% like diversity with some SAR, and 8% work of teflon targets, so any hit matter is welcome.  

The way I read this is that 60% of people don't consider the screen done when the first results come in.  In my eyes, the screen is over when there are actives identified with testable SAR hypotheses.  This is probably just my bias of having lived in a very resource constrained environment where follow up to a screen was a second serving of resources.  To me, this is great news; companies that are doing fragment screening are invested and not giving short shrift to these efforts. 

I would be curious to hear in the comments how people develop SAR with a maximally diverse library.  Do you just pick every available fragment that has the same central core and evaluate all possible side chains?  Would you apply a similarity cutoff of 0.9 or something?  How many compounds do you follow up with per active fragment?

FBDD Down Under

Fragment-Based Drug Design Down Under was held at Monash University in Melbourne, Australia earlier this month. The first dedicated FBDD conference in this country was full of enthusiasm: I had the impression many of the 100 or so participants, most of them Australian, were happily surprised to meet so many other fragment aficionados. With 18 oral presentations, nearly as many posters, and a lively panel discussion I can only touch on some of the broader themes here, so please weigh in with your own observations.

Fragment library design received considerable attention, which was nice as this is an area that is all too often ignored in conferences. Pete Kenny's name came up a couple times in helping to put together the CSIRO fragment library. Craig Morton gave an excellent overview of the SVIMR fragment library and some of the challenges constructing it: of roughly 1600 fragments purchased, 450 were either not sufficiently soluble in water or DMSO or not sufficiently pure to be included. David Chalmers of MIPS presented an analysis of the physicochemical properties of approved drugs, noting that roughly three quarters are ionizable, with potential implications for library design.

Three dimensional fragments have been much discussed lately, and Martin Drysdale of the Beatson Institute described a UK consortium, 3Dfrag.org, to put together a library of 3-dimensional fragments, as defined by having a principal moment of inertia closer to a sphere (think adamantane) as opposed to a plane (benzene) or a rod (2-butyne). The project is still in its early stages, with about 200 fragments acquired thus far. Martin also described an interesting collaboration with the Broad Institute to use existing DOS-derived fragment-sized molecules for screening.

There were several talks on fragment screening methods, especially NMR and SPR. In an intriguing comparison, Jerome Wielens of SVIMR described parallel efforts on HIV integrase, both using essentially the same (Maybridge) library. STD NMR screening produced more than 50 hits, ultimately yielding 15 co-crystal structures, while SPR screening (also discussed later by Tom Peat of CSIRO) produced 16 hits and ultimately 6 crystal structures, yet few of the hits were in common. There were differences in the protein constructs and pH, and some of the NMR hits may have been artifactual, while the use of a reference protein in SPR may have weeded out some true positives. All of which underlines the fact that using multiple biophysical methods is ideal.

STD NMR came under scrutiny from others as well: San Lim of MIPS described compounds that showed a signal when screened in mixtures but not when tested individually, and Martin Drysdale discussed one target that gave a 36% hit rate using the technique, leading him to pick SPR as a primary screening method. Still, there are some interesting possibilities: Thomas Haselhorst of Griffith University discussed using STD NMR not just for screening membrane proteins but for screening viruses, cells, and even fungal spores!

Markku Hämäläinen of GE Healthcare discussed the use of both SPR (specifically Biacore) and ITC. In the case of SPR, he termed one class of problematic compounds “selective promiscuous binders”: for example, a positively charged protein may cause negatively charged fragments to aggregate around it, giving anomalously high signals. Using a positive control and setting a maximum Rmax in fitting the data can help weed these out and provide more accurate dissociation constants. In a collaboration with Merck Serono on a kinase target, 105 hits from a 1920-fragment library gave an 80% confirmation rate when tested in ITC, and 41 of 48 produced co-crystal structures.

But as we are increasingly seeing, Biacore is no longer the only name in the SPR game: Olan Dolezal of CSIRO described Bio-Rad’s ProteOn instrument and found that, while it was less sensitive than Biacore, its higher throughput made it an attractive primary screening instrument.

There were also a couple interesting talks on in-situ methods for fragment assembly, including MS-based methods described by Sally-Ann Poulsen of Griffith and click-based methods discussed by William Tieu at the University of Adelaide. One of the problems with assembling a high-affinity molecule in situ is product release: a molecule made in situ might bind so tightly it never leaves the protein, which essentially stops production once a stoichiometric amount of the inhibitor is made. In Tieu’s case, the problem was cleverly overcome by introducing a mutation to lower the affinity.

Finally, Jonathan Baell of MIPS gave an excellent (though disturbing) talk on PAINS – a topic which is still unfortunately not sufficiently appreciated. In one illuminating example, he found that an in-house screen of a histone acetyltransferase produced only a single legitimate hit, along with a plethora of PAINS.

One common theme both in the presentations and offline discussions was the relative lack of chemistry support; definitely a pity, since there are certainly plenty of chemists looking for new opportunities. Of course, funding chemistry is a problem not unique to the Southern Hemisphere.

Australia is clearly a new world for fragments, and it will be fun to see how the field develops there. And on a personal note, I found Aussies to be some of the warmest, most genuine people I have met in any country. I definitely look forward to finding an excuse to return.

Microscale Thermophoresis (MST)

Practical Fragments has a soft spot for new biophysical methods to identify fragments, many of which are given unfortunately non-descriptive initialisms. To a list that includes SPR, ITC, STD, MS, TINS, CEfrag, and WAC, we can now add Microscale Thermophoresis (MST), described in a new paper in Angew. Chem. Int. Ed. by Philippe Baaske and colleagues at NanoTemper Technologies as well as academic collaborators.

Thermophoresis, also referred to as the Soret effect, occurs when particles move in response to a temperature gradient. In this case, the “particles” are proteins, whose movements depend on size, charge, conformation, and solvation, and can be altered by factors such as ligand-binding.

In MST, a fixed concentration of protein is incubated with varying concentrations of ligand in small capillaries. An infrared laser rapidly heats a spot on the capillary, and an ultraviolet light source excites aromatic residues within the protein. The fluorescence in the heated spot changes as the protein moves along the temperature gradient. This movement is affected by ligand binding, and so measurements at different ligand concentrations can be used to construct a binding curve.

The researchers used MST to study the binding of ligands to several proteins, including ionotropic glutamate receptors (iGluRs), p38-alpha MAP kinase, thrombin, and even the calcium sensor Syt1. The dissociation values determined by MST were mostly comparable to literature values, and the researchers could also perform competition studies in which adding an excess of one ligand blocked a different ligand for the same site.

A nice feature of the technology is that, since it uses native protein, one doesn’t need to worry about the effects of immobilization or conjugation, factors that researchers using SPR, TINS, and WAC must consider. On the other hand, the fluorescence signal relies on native amino acid residues (tryptophan in the examples here), which can be obscured by many compounds. Also, in its current incarnation MST doesn’t appear particularly high-throughput, though it also doesn’t use much protein

Still, this seems like a pretty cool approach. I’ve started seeing NanoTemper at more conferences (such as FBLD 2012), so hopefully you will have a chance to check them out and let us know what you think.