Fragments vs KAT6A: ligand efficiency in action

Epigenetic writers such as histone acetyltransferases (HATs) control gene expression, which often goes awry in cancer. The gene encoding the lysine acetyltransferase KAT6A, for example, is amplified in multiple types of cancer, and its overexpression is associated with poor clinical outcomes for patients with ER⁺ breast cancer. A recent paper in Bioorg. Med. Chem. Lett. from Andrew Buesking and colleagues at Prelude Therapeutics reports a new series of inhibitors.

 

The researchers started by considering previously reported molecules such as PF-9363. Recognizing the importance of the central sulfonamide, they generated a library of 150 fragments containing this core and screened them in a biochemical assay. Taking a similar approach as other researchers reporting on a different epigenetic target we discussed last year, the Prelude team explicitly used ligand efficiency to call hits, setting the cutoff at > 0.3 kcal per mol per heavy atom.

 

A direct deconstruction of PF-9363 led to compound 6, but, seeking something novel, the researchers were drawn to compound 8, with similar ligand efficiency. Modifications were made to both of the terminal aromatic groups, leading to compound 13, which was co-crystallized with KAT6A. This led to further structure-guided modifications, with compound 25 being the most potent.

 

Unfortunately, further improvements in potency were not forthcoming, and the ligand efficiency had dropped steadily from both the initial fragment as well as PF-9363. The researchers conclude by stating that they “decided to pursue alternative approaches.” Still, this paper is a nice, concise example of using metrics both for pursuing a chemical series and, ultimately, discontinuing it.

Discovery on Target 2024

Last week Boston hosted CHI's 22^nd Annual Discovery on Target. With dozens of talks spread across seven or eight concurrent tracks over three days, and an additional day of pre-conference symposia, I’ll just touch on a few themes.

 

Computational Approaches

Artificial intelligence and machine learning were well represented. Brandon White described an ML model built at Axiom to predict liver toxicity, responsible for a quarter of clinical trial failures. As we noted last week, good ML models require lots of data, and Axiom has tested 50,000 small molecules in primary human hepatocytes from multiple donors using assays including high-content imaging. Just input a chemical structure and the model will predict toxicity. When run against the FDA’s database of drug-induced liver injury, the model performed with 74% sensitivity and 97% specificity, and even gave good dose predictions.

 

Woody Sherman (Psivant) laid out a series of “grand challenges for computers in drug discovery.” This is the working title for a publication he is spearheading to focus attention on key problems. They fall into five categories: chemistry (including synthesis, stability, and covalency), structure predictions (including protein-ligand structures, dynamics, and cryptic pockets), energetics (including affinity, selectivity, and kinetics), ADME (including everything from solubility and aggregation to bioavailability), and pharmacology (including toxicity). A sixth category, human considerations (including intellectual property and interpreting experimental data), is also being considered.

 

The success of AlphaFold to predict protein structures shows what computers can achieve, but in that case the effort was enabled by massive amounts of high-quality public data in the Protein Data Bank. Few of these challenges can draw on anything approaching the PDB. Indeed, even parameters as seemingly simple as solubility can change dramatically depending on crystal form and subtle changes to pH.

 

Because these computational challenges are so daunting, collecting them into one forum may prove salutary. And other categories may be worth including, such as target discovery. Woody is looking for co-authors, so reach out to him if you’re interested.

 

Covalent approaches

Covalent approaches to drug discovery have gone mainstream, at least if this conference is any indication. But they are not without risk: Doug Johnson (Biogen) described research implicating the piperidine acrylamide pharmacophore in approved BTK inhibitors with inhibition of ALDH1A1 and possible liver injury.

 

Several talks focused on methodologies. Alexander Federation (Talus) described data-independent acquisition (DIA) mass spectrometry methods, which can be more comprehensive than the more commonly used data-dependent acquisition (DDA) methods in identifying peptides in chemoproteomic studies, which we first discussed here. Talus is focused specifically on transcription factors.

 

As we noted earlier this year, Steve Gygi (Harvard) has been at the forefront of increasing the throughput of mass spectrometry methods, and he described how to increase the number of samples that can be analyzed simultaneously from 18 to 35. He also described two approaches, GoDig and CysDig, to look for up to 200 pre-specified proteins in a sample, ensuring identification of even low-abundance targets.

 

Turning to specific targets, Wai Cheung Adrian Chan described work done at Harvard to find covalent inhibitors against deubiquitinating enzymes (DUBs), reporting that screens of a small library of 178 covalent fragments in cell lysates found hits against several dozen DUBs. (We previously wrote about non-covalent USP7 inhibitors.)

 

Brooke Brauer described the optimization of a covalent inhibitor of Bfl-1 at AstraZeneca, an interesting oncology target. AZ has published some nice papers on this project which I’ll write about soon.

 

Last week we mentioned work Michelle Arkin and collaborators had done on 14-3-3 proteins, and Lynn McGregor described work done at Novartis on the same system. A screen of 6000 covalent compounds identified hits that modified a specific cysteine in 14-3-3 more rapidly in the presence of a peptide derived from the estrogen receptor. Stabilizing this interaction could be useful for treating certain cancers.

 

Not everyone is focused on cysteine: Andrea Zuhl described work done at Hyku Biosciences, which as the name suggests is targeting histidine, tyrosine, and lysine. This has necessitated building a fragment library of more than 6000 compounds, more than 70% of which are stable in buffer. Andrea presented one example targeting the catalytic lysine residue of the oncogenic ALK fusion protein, though the selectivity against other kinases was not disclosed.

 

All of these examples focused on covalent molecules in which the warhead is maintained during optimization. But as we first wrote about here, fully functionalized fragments (FFFs) contain a photoreactive moiety that reacts covalently with nearby proteins but is subsequently discarded. Sherry Niessen described how Belharra has industrialized this process by creating a library of about 11,000 FFF probes. Because of the low efficiency of protein crosslinking (typically <5%), most of the library consists of enantiomeric pairs to facilitate hit identification. Also, the average molecular weight of the library is around 350 Da, and these super-sized fragments tend to perform better than the strictly rule-of-three compliant molecules.

 

Covalent success stories

At least two presentations covered covalent fragment-based drug candidates. Shota Kikuchi (Vividion) described the discovery of VVD-214/RO7589831, a WRN inhibitor we wrote about earlier this year. As I speculated at the time, the cyclopropyl group was introduced to lower the reactivity of the vinyl sulfone warhead. Interestingly though, even early molecules were quite selective for WRN. Like sotorasib, binding is largely driven by the k_inact term of k_inact/K_i, again demonstrating that high reactivity for the target does not necessarily mean high chemical reactivity.

 

Finally, in his plenary keynote Steve Fesik (Vanderbilt University) covered multiple success stories, including the discovery of the KRAS^G12C inhibitor BI 1823911, which we wrote about here. Boehringer Ingelheim has since published molecules that hit multiple KRAS mutants as well as KRAS degraders, and Steve noted that all of these contain the same “squirrely-looking” fragment identified from SAR by NMR, an illustration of the power of fragment-based methods to explore new regions of chemical space.

 

I’ll close there, but please add your thoughts. There are is still at least one good conference coming up this year, and 2025 is quickly approaching.

FBLD 2024

The FBLD meetings have always been calendar highlights. Starting in 2008, before Practical Fragments even existed, they have graced cities around the world in 2009, 2010, 2012, 2014, 2016, and 2018. The plan was for 2020 to be held in Cambridge, UK, but for obvious reasons that didn’t happen. Last week, Boston hosted a triumphant return of the event. With more than 30 talks and dozens of posters I’ll just touch on a few major themes.

 

Crystallography

High-throughput crystallography was prevalent, as befits its growing role in fragment finding. (If you haven’t yet voted in our methods poll on the right side of the page please do so!) Debanu Das (XPose Therapeutics) described how crystallographic screens of just a few hundred fragments identified hits against DNA-damage response proteins such as APE1; these have been advanced to high-nanomolar inhibitors with cell activity. And Andreas Pica described the ALPX platform that enabled screening >4000 hits from an HTS screen against PDEδ resulting in >500 structures.

 

The Diamond Light Source was a pioneer in developing high-throughput crystallography methods, and several speakers described continued progress. Blake Balcomb noted that since 2015 they have collected >240,000 datasets and identified >30,000 ligands. Of these, some 3750 have been deposited into the Protein Data Bank.

 

A crystallographic fragment hit is just the start, and Frank von Delft emphasized that “fragment progression is neither fast nor cheap.” His goal is to take a 100 µM binder to a 10 nM lead in less than a week for less than £1000. Toward this end he and his team are using rapid chemical synthesis and crude reaction screening along with various computational approaches and crowd-sourced science. The COVID Moonshot, which we wrote about here, is one model, and Diamond is trying to create a “Moonshot factory” to pursue other viral targets.

 

Computational Approaches

Computational methods are potentially the least expensive fragment-to-lead method, and these were well represented. One challenge is screening the massive chemical space represented by make-on-demand libraries, and Pat Walters (Relay) described how this can be done using Thompson Sampling, an active-learning method that traces its origins to 1933. Applied to lead discovery, the method involves breaking larger molecules into component fragments and iteratively searching for better binders. Pat showed that searching just 0.1% of a library of 335 million molecules consistently found 90% of the best hits.

 

Most computational methods rely on experimental data, and over the past 25 years Astex has generated >100 crystal structures on each of more than 40 targets, with >6600 bound fragments in total. Paul Mortenson described how these are being used to develop generative models, with chemists providing feedback on suggested molecules.

 

Artificial intelligence is the centerpiece of Isomorphic Labs, which has unfettered access to AlphaFold 3. Rebecca Paul described an example starting from a literature fragment in which the predicted affinities matched well with experiment – and the molecules were considerably more potent than those suggested by an experienced medicinal chemist.

 

Recognizing the need for experimental affinity data for fragments, Isomorphic worked with Arctoris to screen 5420 fragments against 65 kinases covering the diversity of the kinome. After carefully curating the data, including rescreening the actives at a different CRO, they found 485 fragments with an IC₅₀ of 300 µM or better. Interestingly, only about half of these fragments are known kinase binders.

 

Sandor Vajda (Boston University) suggested there may be limitations to machine learning models. He found that using AlphaFold 2 to find cryptic pockets was dependent on their representation in the PDB, with rare experimental states not being predicted. Sandor also proposed an interesting hypothesis that cryptic pockets created only by the movement of side chains are not very ligandable because the side chains move on such a rapid time scale that they effectively act as competitive inhibitors to ligands.

 

Success Stories

No FBLD meeting would be complete without success stories, and FBLD 2024 was no exception. Chaohong Sun noted that nearly 80% of the targets at AbbVie taken into fragment-based screening are novel. Of these, more than 80% yield actionable hits, though 44% are not pursued for a variety of reasons, including finding hits from other sources, hits at novel sites with no obvious function, and changes to the portfolio. Chaohong described a series of STING agonists that was taken forward to low nanomolar leads with in vivo activity.

 

Michelle Arkin (UCSF) described progress on creating molecular glues to link 14-3-3 proteins to the estrogen receptor, which we last wrote about here. Covalent binders to the 14-3-3 protein stabilize the interaction with ERα by more than 100-fold and show activity in cancer cell models.

 

Multiple talks focused on SARS-CoV-2 targets. Ashley Taylor (Vanderbilt) described fragment screens against the papain-like protease PL^Pro that led to both covalent and non-covalent inhibitors. James Fraser (UCSF) described how a massive crystallographic screen against the Nsp3 macrodomain Mac1 led to high nanomolar compounds, which we wrote about here. And Adam Renslo (UCSF) discussed the further optimization of Mac1 inhibitors to yield molecules that could protect mice from a fatal challenge of the virus.

 

A drawback of pursuing novel targets is that sometimes the biology proves uncooperative. Andrew Woodhead described a successful fragment screen at Astex against the oncology target elF4E that led to mid-nanomolar binders that could disrupt the protein-protein interaction with eIF4G in cells. Surprisingly, these molecules had no effect on cell viability, and a series of mutational and targeted-protein degradation experiments suggested that blocking a larger region of the protein-protein binding site might be necessary.

 

Drugs are the ultimate success stories, as David Rees reminded participants in “25 years of thinking small.” In addition to providing an overview of FBLD at Astex, David added up the sales of all seven FDA-approved fragment-derived drugs, which totals more than $3 billion. Harder to quantify—though infinitely more valuable—are the added years of life for patients with once-untreatable cancers. These numbers will only grow as the dozens of fragment-derived molecules in the clinic continue to advance.

 

I’ll close on that note. If you missed FBLD 2024, you’ll have another chance next year: FBLD 2025 is planned for Cambridge (UK) September 21-24 next year. Barring global pandemics.

New poll: structural information needed for F2L and fragment-finding methods

With elections taking place around the world, Practical Fragments is getting into the action. Our new poll revisits two questions from past years to see how things have changed.

 

Our first question asks, “how much structural information do you need to begin optimizing a fragment?” When we ran this poll back in 2017 a third of respondents needed crystallography to begin a fragment-to-lead campaign, while only a quarter would move forward with SAR only. But when Wolfgang Jahnke, Ben Davis, and I published a review in 2018 about advancing fragments in the absence of crystal structures, we found an abundance of approaches. It will be interesting to see whether these numbers have shifted.

 

Our second question asks what method(s) you use to find and validate fragments. For consistency with previous polls please click every method you use, whether as a primary screening technique or for validation. Please note too that we’ve added cryo-electron microscopy. You can read about these methods below, and if you select “other” please describe in the comments.

 

• Affinity chromatography, AS-MS, capillary electrophoresis, or ultrafiltration
• BLI (biolayer interferometry)
• Computational screening
• Cryo-EM (cryogenic electron microscopy)
  
• Functional screening (high concentration biochemical, FRET, cell-based, etc.)
• ITC (isothermal titration calorimetry)
• Literature or known fragments
• MS (mass spectrometry, native or covalent)
• MST (microscale thermophoresis)
• NMR – ligand detected
• NMR – protein detected
• SPR (surface plasmon resonance)
• Thermal shift (or DSF)
• X-ray crystallography
• Other

 

Please vote on the right hand side of the page; click the vote button for each question. (If you don’t see the poll you may need to (1) turn off private browsing, since the free Crowdsignal version we use for the blog cannot support surveys in this mode or (2) view web version on your phone.)

Casting light on target-guided synthesis

Target-guided synthesis, in which a protein templates the formation of its own inhibitor, is a concept first proposed decades ago. There are roughly two flavors. Dynamic combinatorial chemistry (DCC) involves reversible formation of the product, and we wrote in 2017 about some of the challenges. Kinetic target-guided synthesis (KTGS) involves irreversible chemistry, for which the options are limited. The classical click chemistry azide-alkyne cycloaddition is so slow that reactions usually take days, which can be a problem for delicate proteins. A recent (open-access) paper in Angew. Chem. Int. Ed. by Cyrille Sabot et al. describes a bright way to accelerate things.

 

The researchers turned to photochemistry, specifically diazirine chemistry. Illuminating 3-trifluoromethyl-3-phenyldiazirines leads to loss of nitrogen and formation of highly reactive carbenes. The carbenes are so hot that they can react indiscriminately with proteins, as we described here. However, the reaction with thiols is faster than the reaction with other functional groups on proteins, so the researchers reasoned that a library of thiols could out-compete the protein.

 

The carbonic anhydrase bCA-II was chosen as a model protein. Sulfonamide-containing molecules such as compound 5 are known to be good inhibitors. This “anchor” molecule was incubated at 60 µM with seven different diazirines, each at 400 µM, in the presence or absence of 30 µM bCA-II and then irradiated with 365 nM light for a few minutes. Most of the reactions produced similar amounts of product in the presence or absence of bCA-II, but compound 1b yielded about threefold more of compound 2d in the presence of bCA-II, suggesting the reaction was being templated by the protein. 

 

Control experiments lend credence to this hypothesis. First, adding a known competitive bCA-II inhibitor reduced the formation of compound 2d to background levels. Second, other proteins did not cause a similar enhancement in the formation of compound 2d. Finally, conducting the experiment with phenylmethanethiol (ie, a variant of compound 5 lacking the sulfonamide moiety essential for interaction with bCA-II) did not cause an enrichment of the photochemical product in the presence of the enzyme.

 

Chiral HPLC was used to show that compound 2d was slightly enriched for the (R)-enantiomer, with an enantiomeric excess of around 10%, when the reaction was conducted in the presence of bCA-II but not in the absence. The two enantiomers were synthesized and tested, and the (R) form did indeed have slightly better activity (300 nM vs 330 nM).

 

This is a thoughtful, well-conducted investigation. But it makes me even less sanguine about the practicality of KTGS for finding new chemical matter, for several reasons. First, the efficiency of the reaction is poor: the researchers calculate the yield of compound 2d at around 1% of the enzyme concentration, so low that they used single-ion monitoring (SIM) mass spectrometry to detect it. Because of this low efficiency, the concentration of enzyme used needs to be quite high.

 

The most serious strike against KTGS is the fact that all of the diazirines generated potent (sub-micromolar) inhibitors. One of them was even slightly better than compound 2d but did not show enrichment in the presence of bCA-II. False negatives seem to be a major problem, as we’ve written previously.

 

One caveat to my caveats is that compound 2d is only marginally more potent than the starting compound 5. NMR experiments conducted with diazirine 1b suggest binding to the protein, though the affinity was not quantified. Perhaps a different fragment linking system, in which both fragments have measurable affinity for the target, would be better suited to demonstrate the utility of KTGS. For now, this paper does a nice job highlighting its drawbacks.

Fragments vs herpesviridae

The name herpes makes most people think of painful ulcers in the mouth, or worse. But herpesviruses are actually a family of viruses that can also cause chicken pox, mononucleosis, and other diseases. Some 95% of adults are infected by at least one type of herpesvirus, and these can become deadly if people become immunocompromised, such as during an organ transplant. A drug that would inhibit all forms of herpesviruses would be useful, and the first steps are described in a recent ACS Med. Chem. Lett. paper by Michael Plotkin and colleagues at Merck.

 

The details of the primary screen are sparse, though the researchers did say they physically screened more than 100,000 compounds to identify molecules such as compound 5, a modest inhibitor of the DNA polymerases from both cytomegalovirus (CMV) and varicella zoster virus (VZV). (For most compounds the paper reports biochemical activity towards both of these polymerases as well as antiviral activity for CMV, VZV, herpes simplex virus 1 (HSV-1), and HSV-2, but for simplicity I’ll only show data for CMV here. The compounds generally have comparable activity towards different viruses.)

 

Hydrogen bond acceptors such as the ketone in compound 5 were found to be essential for activity, and exploring a variety of analogs led to compound 12, which in addition to submicromolar biochemical activity against the DNA polymerases also showed antiviral activity against CMV and other herpesviruses.

 

The paper goes into considerable detail on the lead optimization. The (S) enantiomer of compound 12 was an order of magnitude more potent than the (R) enantiomer. Modifications made to both of the phenyl rings ultimately led to compound 44, with low nanomolar biochemical activity against the polymerases and sub-micromolar antiviral activity against CMV, VZV, HSV-1, and HSV-2. Importantly, the researchers note that they did not have crystal structures during optimization, a useful reminder that structural information is not always necessary.

 

Compound 44 had modest oral bioavailability in rodents, but closely related compound 42 containing a trifluoromethyl group in place of the bromine was better, albeit with slightly lower biochemical potency. This molecule led to high survival rates in mice when dosed either before or after being exposed to HSV-1. In separate studies, the compound reduced CMV viral load. For both HSV-1 and CMV compound 42 compared favorably to acyclovir and ganciclovir, two commonly used drugs.

 

Although there is still some way to go to a drug, the researchers end by promising to describe “further progress of this series.” I look forward to reading about this.

Fragments in Brazil

Most of the fragment events we’ve highlighted are in the US, Europe, and Australia, but that does not fully reflect where all the good science is happening. In a recent ACS Med. Chem. Lett. paper, Carolina Horta Andrade, Maria Cristina Nonato, and Flavio da Silva Emery introduce CRAFT: the Center for Research and Advancement in Fragments and molecular Targets.

 

Established in 2021, CRAFT is a collaboration between the University of Saõ Paulo and the Federal University of Goiás. The center is focused on endemic diseases of Brazil. As the researchers note, only one of the 60 or so fragment-derived drugs that have entered the clinic is an anti-infective, so there is clearly significant need. CRAFT also has an educational and training component reminiscent of the European FragNet and the Australian Centre for Fragment-Based Design.

 

One focus of CRAFT is fragment library design, including underexplored heterocyclic systems. Importantly, the researchers are investigating new synthetic methodologies to be able to functionalize different regions of the fragments. They are also exploring fragments similar to or derived from natural products.

 

Targets are of course essential, and CRAFT is investing in protein production and characterization, such as the enzyme DHODH from Leishmania; we’ve written recently about a fragment approach to the mammalian counterpart.

 

Finally, CRAFT is investing in structure-based design, ligand-based design, and phenotypic screening. And in 2024 no venture would be complete without use of machine learning.

 

Academic laboratories often struggle with downstream drug discovery efforts such as drug metabolism and pharmacokinetics. CRAFT recognizes this and has partnered with the Welcome Centre for Anti-Infectives Research to train participants in DMPK.

 

The researchers “invite the global scientific community to collaborate with us in addressing neglected diseases.” I hope they succeed. Five years ago we highlighted the consortium Open Source Antibiotics, but that site seems to be updated infrequently. The COVID Moonshot has been more successful but is arguably less urgent given the billions of dollars of industry money that poured into research on SARS-CoV-2. From an ethical perspective society should invest more on combating tropical diseases. And as the planet warms, these diseases will increasingly move out of the tropics.

Fragments in the clinic: Lirafugratinib

With crystal structures of protein-ligand interactions becoming increasingly accessible, it is easy to forget that proteins do not exist as the static structures seen on page or screen. Indeed, back in 2018 we quoted Karplus quoting Feynman that “everything that living things do can be understood in terms of the jiggling and wiggling of atoms,” and even the smallest proteins have lots of atoms. In an open-access paper published in Proc. Nat. Acad. Sci. USA earlier this year, Heike Schönherr, David Shaw, and collaborators at Relay Therapeutics, D.E Shaw Research, Pharmaron, and Columbia University take advantage of these movements.

 

The researchers were interested in finding selective inhibitors of fibroblast growth factor receptor 2 (FGFR2), which is activated in many cancers. The four members of the FGFR family are so closely related that finding selective inhibitors is difficult. Inhibiting FGFR1 can lead to hyperphosphatemia, while inhibiting FGFR4 can cause diarrhea, side effects seen with the approved fragment-derived drug erdafitinib.

 

Although the structures of FGFR1 and FGFR2 are very similar, extended (25 µs) molecular dynamics simulations revealed that the so-called P-loop of the proteins behaved differently: in FGFR1 it became disordered, while in FGFR2 it remained more rigid. The researchers sought to take advantage of these differences with a covalent inhibitor.

 

The researchers started with a non-selective hinge-binding fragment, compound 1. Adding an acrylamide warhead led to a nanomolar inhibitor with modest selectivity for FGFR2. (All IC₅₀ values are measured after 30 minute incubations.) Growing the molecule into the so-called back pocket of the kinase led to compound 5, with nearly 100-fold selectivity for FGFR2 over FGFR1. 

 

 

The path from compound 5 to lirafugratinib (also called RLY-4008) looks straightforward but was anything but. First, the aryl acrylamide was a metabolic liability, so the researchers attenuated the reactivity by adding a methyl group. Mechanistic studies with this molecule revealed that while it had only a slightly better affinity (K_I) for FGFR2 than FGFR1, it had a k_inact value about 15-fold higher for FGFR2. Molecular dynamics studies suggested that the relevant cysteine in FGFR1 is locked in a position too far from the acrylamide to react, while the corresponding cysteine in FGFR2 may be able to more closely approach the acrylamide warhead.

 

Further optimization, guided by extended molecular dynamics simulations, led eventually to lirafugratinib with ~250-fold selectivity for FGFR2 over FGFR1 and >5000-fold selectivity over FGFR4. Remarkably, the noncovalent version of lirafugratinib, compound 11, shows dramatically lower affinity for both FGFR1 and FGFR2 and very little selectivity between them. The ligand seems to assume a different binding mode after covalent bond formation, which could explain these differences in selectivity.

 

Mouse studies of lirafugratinib showed tumor stasis or regression without increased serum phosphate levels. More importantly, early clinical data has shown “minimal hyperphosphatemia and diarrhea.”

 

This is a lovely example of structure and dynamics-based design (SDBD?). Commonly cited advantages of covalent drugs include improved potency and extended pharmacological effects, but this work shows that they can also achieve remarkable selectivity between closely related proteins, even when both proteins contain cysteine residues in the same location. Moreover, an open-access paper in Cancer Discov. that dives more deeply into the biology shows that lirafugratinib is selective across the kinome, inhibiting just two of 468 kinases other than FGFR2 by >75% at 500 nM.

 

The next time you’re trying to find a selective inhibitor for one member of a protein family, it may be worth taking a covalent approach, and paying close attention to dynamics along the way.

Fragments vs β-glucocerebrosidase

The protein β-glucocerebrosidase, also called GCase and GBA, is a lysosomal enzyme that cleaves glucosylceramide. People with inactivating mutations in both copies of GCase develop Gaucher’s Disease, which can be treated with a recombinant form of GCase. Heterozygous mutations increase risk for Parkinson’s Disease and for dementia with Lewy bodies, and though the mechanism is unclear, stabilizing the enzyme and/or boosting activity of residual GCase might help. This approach is described in a recent J. Med. Chem. paper by Nick Palmer and colleagues at Astex Pharmaceuticals.

 

The researchers started with a crystallographic screen of 440 fragments, resulting in a whopping 91 hits. In parallel, 1800 fragments (including the aforementioned 440) were screened using ligand-observed NMR, SPR, and thermal shift assays, and hits were confirmed crystallographically to yield another 15 structures. Astex has previously reported that multiple ligand binding sites are common in proteins, and GCase is no exception, with the 106 ligands binding to 13 distinct sites.

 

With this embarrassment of riches, prioritization became critical. Sites formed by crystal packing and shallow solvent-exposed sites were deprioritized, along with those near the active site, since ligands binding there might inhibit the enzyme. SPR was not well-suited to measuring ligand affinities due to non-specific binding, and ligand-observed NMR was similarly complicated due to multiple binding sites. However, isothermal titration calorimetry (ITC) proved to be effective, and this technique was used to narrow in on two binding sites.

 

Site A was particularly attractive: it had 31 fragment hits, one of which has a respectable dissociation constant of 12 µM. Screening of analogs did not lead to anything better, but merging this fragment with another Site A fragment led to compound 15. Interestingly, crystallography revealed that this molecule binds not at Site A but at Site B. Although the affinity is low, the ligand efficiency is respectable. The fragment also makes several polar interactions and has multiple vectors for growing the molecule.

 

 

Testing analogs of compound 15 led to compound 16, and growing led to compound 17, with low micromolar affinity. Further structure-based design ultimately led to compound 22, with low nanomolar affinity. The molecule increased GCase activity in a cellular assay, albeit at a fairly high (mid-micromolar) concentration. The molecule was found to be cell permeable with no efflux, so the source of the disconnect between affinity and cell activity is unclear.

 

This lovely example of structure-guided fragment-based ligand design holds several lessons. First, as noted above, finding fragments is often the easy part; selecting among them and figuring out what to do next can be challenging. Second, especially at the earliest stages of optimization, fragments can change not just their binding mode but their binding site entirely.

 

Finally, figuring out which sites will be best for high-affinity allosteric ligands isn’t necessarily straightforward. Of the 105 fragment hits at 13 sites, only four bound in Site B, yet this site turned out to be more fruitful than Site A, which had many more bound fragments. The researchers note that Site B had previously been identified as ligandable by FTMap, supporting the utility of computational approaches.

 

The researchers conclude, “we hope that our findings will be of use to the wider community.” Certainly from a best practices perspective the paper succeeds. And although the most advanced molecules described do not meet all the criteria for robust chemical probes, and it is unclear whether they will work with mutant proteins, they could still be useful to better understand the complicated biology of GCase.

A bright idea for rapid affinity measurements

Finding fragments that bind to a target is important but so is measuring their affinities. NMR methods can find even weak fragments, but accurately assessing affinities takes time. In a recent (open-access) J. Am. Chem. Soc. paper, Felix Torres, Roland Riek, and collaborators at the Institute for Molecular and Physical Science and NexMR provide a new, fast method.

 

The approach is based on photochemically induced dynamic nuclear polarization (photo-CIDNP), which we wrote about here; Felix also spoke about it at the FBDD-DU meeting in June. As the name implies, the technique involves illuminating NMR samples to electronically excite ligands, thus increasing the signal to noise ratio of the NMR signal by as much as 100-fold. Previous work focused on using the method to identify binders, even with cheap, benchtop NMR instruments.

 

The new paper describes how to quantitatively measure dissociation constants using photo-CIDNP. The theory gets a bit hairy, but the basic idea is that the more photochemically excited ligand that binds to the protein, the more the signal decreases. A series of samples are prepared with increasing concentrations of ligand and either no protein or a fixed concentration of protein. After measuring the NMR signals, the data are plugged into equations to derive the K_D values in a method called CIDNP-K_D.

 

As the researchers have previously noted, not every ligand can be photosensitized. However, dissociation constants can still be measured for these using competition experiments with previously characterized reporter ligands that can polarized, akin to using to NMR competition studies with ¹⁹F reporter ligands (see here).

 

So how well does the technique work? The researchers first turned to the PDZ2 domain of a phosphatase called hPTP1E, which is involved in cell proliferation. They measured the affinities of a series of peptides having 4 to 8 amino acid residues and compared these values to those obtained using two dimensional [¹H,¹⁵N]-HSQC chemical shift perturbation, the gold standard NMR technique. Affinities ranged from low micromolar to low millimolar, and there was reasonable agreement (generally within about two-fold) between both techniques. Most of the peptides contained tryptophan, which is suitable for photo-CIDNP, but CIDNP-K_D also worked in competition mode when non-tryptophan containing peptides were competed against peptides containing tryptophan. And the technique was fast, with each datapoint taking only 30 seconds for photo-CIDNP compared to as long as 80 minutes for HSQC NMR.

 

Next the researchers turned to fragments. They had previously conducted a screen against the oncology target PIN1 and identified a number of fragment hits, two of which had been characterized in detail. The affinities of these were measured by CIDNP-K_D, and the low millimolar values agreed with those from HSQC NMR.

 

Another neat application described in the paper is “CIDNP-based epitope mapping,” which is based on the fact that an excited proton on a ligand that is in close proximity to the protein will relax more rapidly than one that is distant from the protein. This phenomenon is similar to STD epitope mapping, and the two methods yielded similar information for the two PIN1 ligands: one region of each molecule was buried in the protein, consistent with crystal structures.

 

One drawback of the technique is that, because measurements require fast protein-ligand exchange, CIDNP-K_D is limited to relatively weak binders (K_D > 10 µM), but this is usually not a problem in the early stages of a fragment program. A full affinity measurement takes about 15 minutes, which compares very favorably to two hours using [¹H,¹⁵N]-HSQC and without the need for isotopically labeled protein. It would be interesting to run head-to-head comparisons with two ligand-based NMR techniques we wrote about last year, imaging STD NMR and R2KD, to see how they compare in terms of speed, accuracy, and generality. Please let us know if you’ve done so.

Fragments vs GPx4 – in reverse micelles

Membrane proteins account for more than half of drug targets, but the fraction is far smaller for fragment-derived drugs. In part this is because biophysical methods, the mainstay of FBLD, have been harder to apply to membrane proteins. A recent (open-access) paper in JACS Au by Courtney Labrecque and Brian Fuglestad at Virginia Commonwealth University tackles this challenge.

 

The researchers use an approach called membrane-mimicking reverse micelles, or mmRM: tiny water-filled bubbles surrounded by lipids and suspended in an organic solvent. We last wrote about reverse micelles back in 2019, where they were being used to study high local concentrations of water-soluble proteins and ligands. Here, the researchers turned to membrane proteins.

 

There are actually two types of membrane proteins: integral membrane proteins and peripheral membrane proteins. The former, as their name implies, have at least part of the protein anchored in the membrane at all times; GPCRs are a prominent class. Peripheral membrane proteins are water soluble but associate with the membrane, and this interaction is often required for folding or function. One example is glutathione peroxidase 4 (GPx4), which reduces oxidized lipids. It is an intriguing but  challenging cancer target, with the only ligands being fairly reactive covalent modifiers. Thus the researchers turned to mmRMs, hoping these could both stabilize the protein in a biologically relevant state and also present binding opportunities unavailable in standard screens.

 

A library of 1911 fragments from Life Chemicals was screened against mmRM-encapsulated GPx4 using ¹⁵N-¹H HSQC protein-detected NMR. Fragments were chosen to have high aqueous solubility (at least 1 mM in PBS) and were screened in mixtures of 10 at 400 µM per fragment. After deconvolution, 14 hits were identified, and dose-response titrations revealed that 9 had apparent dissociation constants < 1 mM, with the most potent having a K_d = 105 µM.

 

Three fragments were studied in greater detail, and these were chosen to have a range of hydrophobicities from clogD = -2.1 (most polar) to clogD = 2.1 (most hydrophobic). Chemical shift perturbation (CSP) analyses suggested that the two more lipophilic fragments bind to the membrane-interacting region of the protein, while the more polar fragment likely binds to a water-exposed site. SAR-by-catalog was applied to find analogs, some of which had increased affinity for the protein, with the best being around K_d = 15 µM.

 

Interestingly, the fragments showed minimal binding to GPx4 under normal aqueous conditions (ie, in the absence of the mmRMs), even at very high fragment concentrations. The researchers suggest this is because the fragments are binding to the membrane-bound state of the protein found in mmRMs, which may adopt a different conformation than that in the absence of membranes. Perhaps. But as prior work shows, it is possible to detect extraordinarily low affinity interactions inside reverse micelles, so maybe these are just very weak binders. Ultimately it remains to be seen whether these fragments will have practical applications. I hope so, and look forward to seeing how they progress.

How to avoid metal artifacts

Back in 2017 we observed with characteristic subtlety that “heavy metals suck.” That post described a hit-finding campaign which foundered when the apparent activity of the fragments turned out to be due to contaminating zinc. A new paper in J. Med. Chem. by Thomas Gerstberger, Peter Ettmayer, and colleagues at Boehringer Ingelheim (BI) describes a similar story, along with suggestions of how to avoid being misled.

 

BI had a collaboration with FORMA Therapeutics that entailed screening roughly 1.7 million compounds against ten targets using biochemical and cell-based assays. The effort resulted in chemical probes against BCL6 and SOS1 and a clinical compound against the latter. Another target was the activated (GTP-loaded) form of KRAS^G12D. Of the 6917 hits from the primary AlphaScreen assay, 1535 gave dose-response curves and passed various counter screens. Of these, 87 representative compounds were tested in STD NMR and thermal shift assays. Only seven confirmed by STD NMR, but these did not confirm by SPR or crystallography.

 

In parallel, the researchers were successfully using FBLD to develop inhibitors of KRAS^G12D, which we wrote about here. Some of the fragment hits were structurally similar to those from the HTS screen, and further searching of the FORMA library led to fairly potent (high nanomolar or low micromolar) hits in the AlphaScreen assay. Two of these even yielded crystal structures, though despite their chemical similarity to one another they bound to the protein in completely different orientations.

 

Unfortunately, follow-up work “revealed erratic structure-activity relationships,” and upon resynthesis the compounds were much less active. At this point the researchers became suspicious, and analyses of the original samples showed they contained >20,000 ppm of palladium contamination. Furthermore, PdCl₂ itself turned out to be a low micromolar inhibitor in the assay.

 

Metals are frequently used as catalysts or reagents in organic synthesis and can be difficult to completely remove during purification. Worse, their presence is often not detectable using standard purity assessments such as HPLC and NMR. Particularly in the case of fragments, which are expected to have low affinities, a small amount of metal contaminant could give a reasonable-looking but misleading signal in an assay.

 

To avoid this problem in the future the researchers developed a Metal Ion Interference Set, or MIIS, consisting of a dozen different metal ions and other salts, all soluble in DMSO so as to be compatible with typical screens. The MIIS is now routinely screened before initiating HTS campaigns, and the results of 74 assays are summarized in the paper. Pd²⁺, Au³⁺, and Ag¹⁺ are particularly nasty, often giving IC₅₀ values < 1 µM, but every metal gave IC₅₀ values < 10 µM in at least two assays. Biochemical assays such as AlphaScreen or TR-FRET were more susceptible to artifacts, with 20.9% showing IC₅₀ < 10 µM, while biophysics assays such as mass spectrometry were better behaved, with only 2.3% showing IC₅₀ < 10 µM. Cellular assays were also surprisingly robust, with 6.3% showing IC₅₀ < 10 µM.

 

This is a nice paper showing that even a massive screen may produce no useful chemical matter. Soberingly, the fact that some of the fragments gave reasonable-looking crystal structures even though the functional activity came from metal contaminants is a salutary reminder that just because you have a crystal structure of a bound ligand doesn’t mean you have a viable starting point.

 

Forewarned is forearmed, and the MIIS appears to be a valuable tool for assessing assay sensitivity to metal ions, which are all too often lurking invisibly in compound samples.

Multiplexing (native) mass spectrometry

Native mass spectrometry (nMS) is one of the less commonly used fragment-finding methods. The approach entails mixing proteins and ligands and gently ionizing them under non-denaturing conditions to look for complexes. As with many other methods, multiple fragments can be screened in a single sample. In a new ACS Med. Chem. paper, Ray Norton and collaborators at Monash University and CSIRO report screening multiple proteins in a single sample.

 

The researchers were interested in fatty acid-binding proteins, or FABPs. As their name suggests, these transporter proteins shuttle lipophilic molecules such as fatty acids around cells. The ten human isoforms are expressed in different tissues and have different functions in metabolic signaling, but their similarity to one another has made finding selective chemical probes difficult. Enter nMS.

 

FABP isoforms 1-5 are the most heavily studied, and these were first assessed individually. They ionized well, though in some cases peaks corresponding to both the native protein and a complex with acetic acid was observed, not surprising given that the buffer contained 50 mM ammonium acetate.

 

Next, all five proteins were mixed together at 10 µM each. All the proteins could still be observed (with or without bound acetate), though some proteins did give stronger signals than others due to differences in ionization efficiency.

 

Adding small molecule WY14643, which the researchers had previously found to bind to FABPs in a fluorescence polarization (FP) assay, led to a more complex spectrum, with peaks corresponding to unbound proteins, proteins bound to WY14643, proteins bound to acetate, and proteins bound to both acetate and WY14643. When WY14643 was added at 10 µM, the selectivity profile was consistent with the FP data. Interestingly though, when ligand was added at the total concentration of all protein isoforms (50 µM), the selectivity profile changed. The researchers suggest this may be due to nonspecific binding at higher ligand concentrations, as has been seen previously for nMS.

 

To explore the generalizability of multiplexing nMS, the researchers turned to more potent (nanomolar) ligands. As with WY14643, these molecules showed good agreement with published selectivity rankings at lower ligand concentrations with some non-specific binding at higher concentrations.

 

When I first wrote about nMS back in 2010, I noted that “the stability of protein-small molecule complexes in native mass spectrometry assays does not necessarily correlate with the (more relevant) solution-phase affinity,” and this fact is investigated in the paper. Careful optimization of the experimental conditions, including ionization voltage and temperature, led to good relative selectivity rankings for a given ligand across the different FABP isoforms but differences in absolute values from those measured by ITC.

 

Another challenge is the fact that the five FABP isoforms tested have similar molecular weights; in one case a ligand complexed with FABP3 was difficult to distinguish from free FABP2. The researchers could solve this by using different protein constructs, such as a hexa-histidine-tagged version of FABP3.

 

Overall this is an interesting approach, and the paper does an excellent job describing the technical details and limitations. Along with protein-observed ¹⁹F NMR, mass spectrometry is a rare experimental technique suitable for screening mixtures of proteins in solution. Indeed, this becomes even easier when screening covalent binders, as seen in this paper from 2003, since there is no need to worry about ligand dissociation during ionization. And with the increasing interest in covalent drugs, the use of MS is only likely to increase.

SAR by TR-HT-SAXS

Well that’s an acronym soup! SAR by NMR was the first practical fragment-finding method, and over the years Practical Fragments has covered lots of other techniques. Small-angle X-ray scattering, or SAXS, has not been among them. As the name suggests, this technique uses X-rays, typically produced at a synchrotron. However, unlike conventional crystallography, it doesn’t require crystalline material. Instead, proteins in solution are analyzed to provide information on their size and shape. The resolution is too low to assess small molecule binding, but suitable for observing dimerization or changes in conformation.

 

Time-resolved SAXS, or TR-SAXS, examines SAXS over time in response to a trigger. For example, you can rapidly add a ligand to a protein and watch for changes in conformation. And HT simply means high throughput. A recent Nature Chemical Biology paper from Chris Brosey, John Tainer, and collaborators at the University of Texas MD Anderson Center, Lawrence Berkeley National Laboratory, University of California Santa Cruz, and University of Arkansas for Medical Sciences Little Rock describes structure-activity relationships by time-resolved high throughput small-angle X-ray scattering (TR-HT-SAXS).

 

The researchers were interested in apoptosis-inducing factor (AIF), a mitochondrial protein with potential implications for cancer and other diseases. AIF normally exists as a monomer in complex with an FAD cofactor. Binding of NADH causes reduction of FAD to FADH^- and concomitant dimerization of the protein. Could fragments do the same, allowing dimerization on demand?

 

A library of 2500 fragments purchased from Life Chemicals was screened at 0.75-1.5 mM against the AIF-FAD complex using differential scanning fluorimetry (DSF), and those that raised or lowered the temperature by more than 1.7 ºC were further characterized by microscale thermophoresis (MST). This led to 32 binders and 7 negative controls, or molecules that did not confirm either by DSF or MST. (Side note: although many people discount compounds that give negative thermal shifts, the natural ligand NADH lowers the melting temperature of AIF by a whopping 10.8 ºC.)

 

Next, the fragment binders and negative controls were screened at 0.5-1 mM by TR-SAXS. Intense X-rays cause reduction of the FAD cofactor, but in the absence of NADH or other ligands the AIF protein remains monomeric. However, some fragments did cause dimerization of the protein during TR-SAXS. Interestingly, these fragments were structurally related to one another. Subsequent crystallography revealed that they bind where NADH normally binds and make some of the same interactions to induce protein dimerization. The paper includes much more detailed characterization, including mutagenesis, spectroscopic, and protein crosslinking experiments to further understand the mechanism.

 

TR-SAXS is an interesting addition to our toolbox of biophysical methods suitable for fragment screening. It does have some disadvantages, such as the need for large amounts of protein at high concentrations: 67 µM in this case. Also, the “HT” may be somewhat aspirational, with a current throughput of 100-200 compounds per synchrotron shift. Finally, the technique is probably best suited to well-characterized proteins where SAXS data can be carefully modeled. With these limitations in mind, it will be fun to see how generally TR-SAXS finds fragments that alter the conformation and multimerization of proteins.

Fragment-based Drug Discovery Down Under (FBDD-DU) 2024

The end of June brought me to Brisbane for the fifth FBDD-DU Conference, which was meeting for the first time outside Melbourne. This was also my first FBDD-DU conference since 2019, and it was nice to see a wide range of talks from around Australia and beyond. As always, I won’t attempt to be comprehensive, so if you attended, please feel free to add your observations.

 

Techniques

Experimental techniques received considerable attention. Félix Torres (NexMR) described using an inexpensive benchtop NMR that doesn’t require liquid helium. Fragments were screened using photochemically induced dynamic nuclear hyperpolarization (photo-CIDNP). The method is so rapid that it is limited more by sample handling than data collection, and the Torres team is speeding things up using flow technology. Right now photo-CIDNP is still very much DIY, but rumor has it that Bruker may soon launch a photochemical module for their benchtop instrument.

 

We’ve written about high-throughput crystallographic screening at the Diamond Light Source, and synchrotrons around the world are building similar platforms. Kate Smith described integrated systems at the Swiss Light Source which automate crystallization, fragment screening, data collection, and data processing. She also described increasing automation of fragment screening using the free-electron laser (FEL), which we wrote about here. Current throughput is around 40 compounds per day and requires large amounts of protein, but these are still early days.

 

Australia is building their own high-throughput crystallography platform, and various components were described by Roxanne Smith (University of Melbourne), Gautham Balaji (Monash Univesrity), and Yogesh Khandokar (ANSTO-Australian Synchrotron). Watch this space!

 

Speaking of Australia, Nyssa Drinkwater described Compounds Australia, a national repository of more than 2.5 million molecules, including several fragment collections. Members, who can be from outside Australia, can store their own libraries within the facility to ease collaborations with other groups, and they can also access public libraries of compounds, including unusual Antipodean natural product extracts. I was fortunate to be able to visit the facility at Griffith University and can attest that it is easily the equal of those in large pharma.

 

Turning to mass spectrometry, Sally-Ann Poulsen (Griffith University) described covalent library screening against PRMT5, a target we’ve written about here. Sally-Ann is also a pioneer of (conventionally non-covalent) native mass spectrometry, and she described applying this methodology to screen small molecules against RNA.

 

But the star of the conference was SPR, appearing in multiple talks. Long-time readers may recall an instrument made by SensiQ, with its gradient injection capability to accelerate data collection. This is now marketed by Sartorius, and Lauren Hartley-Tassell (Griffith University) described using it to screen a glycoprotein. The larger plumbing in the instrument is less prone to clogging, and Lauren said it can even accommodate screening of whole cells.

 

Anything to accelerate the (sometimes painful) process of advancing fragments is always welcome. As Jason Pun (Monash University) noted, eight of nine targets screened in Martin Scanlon’s group started with fragments having affinities worse than 100 µM. Off-rate screening, an SPR technique we wrote about here, can rapidly identify more potent molecules from crude reaction mixtures, but data processing can be tedious. Jason described new software tools to automate this process, and hopefully he will publish the methodology and code. (An aside: over coffee Yun Shi of Griffith University noted that off-rate screening, or ORS, should really be called off-rate constant screening, which would give the more amusing acronym ORCS.)

 

Targets

Turning to targets, Ben Davis (Vernalis) described a collaboration with Servier to advance oncology target USP7 inhibitors from a literature fragment to a preclinical candidate. Crude reaction mixture screening was used extensively, not just by SPR but even in microsome stability studies. Unfortunately the project ended when on-target toxicology effects emerged, which were perversely more severe in higher animal species than they were in mice.

 

Yun Shi described finding tiny heterocyclic fragments that react with the NAD⁺ cofactor of neurodegenerative target SARM1 in situ to generate a potent inhibitor, as we wrote about here. Yun is using ¹⁹F NMR to follow the base-exchange reaction to identify inhibitors to other glycohydrolases too.

 

Deaths due to E. coli are – somewhat surprisingly – more common than those caused by any other pathogen, and Christina Spry described her work at the National Australian University to discover inhibitors of the essential dephosphocoenzyme A kinase (GPCK) enzyme, which catalyzes the final step in the synthesis of Coenzyme A (CoA). Fragment screening by DSF and NMR identified a weak (K_D=380 µM) binder, and fragment growing has led to a low nanomolar inhibitor that is selective against the human form of the enzyme.

 

Continuing the E. coli theme, several talks discussed efforts against the challenging bacterial virulence target DsbA, a twenty-year campaign in Martin Scanlon’s group at Monash as noted by Yildiz Tasdan. The enzyme has a shallow, hydrophobic active site, but the discovery of fragments binding to a cryptic site and crude-reaction screening by ORS (ORCS?) and affinity-selected mass spectrometry (ASMS) has finally led to molecules with dissociation constants around 1 µM.

 

Finally, in his closing keynote address Alvin Hung, who recently founded NeuroVanda, described a wide range of fragment success stories, many of them covered on Practical Fragments, against targets including pantothenate synthetase, GSK3β, PKC-ι, and MNK1/2. Although structural enablement helped in many cases, Alvin was not rigid about the need for atomic-level details: in response to the question whether he would advance a fragment in the absence of structure, he answered simply, “of course.” Perhaps it's time to redo my poll on this subject.

 

I’ll wrap up here, but if you missed this or earlier events this year there are still a couple more conferences in Boston, and 2025 is already starting to take shape.

Fragment events in 2024 and 2025

The year is half-way done, and we've seen some great events; I'll share my thoughts on FBDD Down Under 2024 next week.

Boston is where it's at in the second half of 2024, and it's not too soon to start planning for 2025.

September 22-25: After a six year hiatus, FBLD 2024 will be held in Boston. This will mark the eighth in an illustrious series of conferences organized by scientists for scientists. You can read impressions of FBLD 2018, FBLD 2016, FBLD 2014, FBLD 2012, FBLD 2010, and FBLD 2009. Early-bird registration ends August 12, so don't delay!

 

September 30 to Oct 3: Autumn is usually a nice time of year in Boston, so stick around to attend CHI’s Twenty-Second Annual Discovery on Target. As the name implies this event is more target-focused than chemistry-focused, but there are always plenty of FBDD-related talks. You can read my impressions of the 2023 meeting here, the 2022 meeting here, the 2021 event here, the 2020 virtual event here, the 2019 event here, and the 2018 event here.

 

Finally, from December 3-5 CHI holds its first-ever Drug Discovery Chemistry Europe in beautiful Barcelona. This will include tracks on lead generation, protein-protein interactions, degraders, and machine learning, with several fragment talks. (Updated July 8.)

 

2025

April 14-17: CHI’s Twentieth Annual Fragment-Based Drug Discovery, the longest-running fragment event, returns as always to San Diego. This is part of the larger Drug Discovery Chemistry meeting. You can read impressions of the 2024 meeting here, the 2023 meeting here, the 2022 event here, the 2021 virtual meeting here, the 2020 virtual meeting here, the 2019 meeting here, the 2018 meeting here, the 2017 meeting here, the 2016 meeting here; the 2015 meeting here, here, and here; the 2014 meeting here and here; the 2013 meeting here and here; the 2012 meeting here; the 2011 meeting here; and 2010 here. 

 

May 5-6: Returning after a four five year hiatus, Industrial Biostructures of America will be held in Cambridge, MA and includes a session on FBLD. (Updated Aug 21 and Oct 6.) 

  

Know of anything else? Please leave a comment or drop me a note.

Fragments vs LTA4H: LipE in action

Three years ago we described the discovery of LYS006, an inhibitor of leukotriene A4 hydrolase (LTA4H) from Novartis currently in phase 2 clinical trials. Companies often pursue multiple chemical series for important targets, and in a recent J. Med. Chem. paper Gebhard Thoma and colleagues describe another fragment-derived lead against LTA4H.

 

A biochemical high-throughput screen yielded compound 2, which is quite potent for a fragment-sized molecule. However, despite good ligand efficiency, the LipE (or LLE) was less impressive due to the high lipophilicity of the fragment. (Note that throughout the paper LipE is calculated based on measured logD rather than logP.) A co-crystal structure revealed that it bound in a similar fashion to other previously characterized LTA4H inhibitors such as compound 1, derived from LYS006 and reported in a J. Med. Chem. paper last year. Adopting elements from these led eventually to compound 12, which though less potent was also much less lipophilic and more soluble while still remaining fragment-sized.

 

 

Continuing to borrow from the rich literature around this target, the researchers added a basic amine group to get to the very potent compound 14. This was metabolically unstable, but further optimization led to compound 3.

 

Compound 3 was profiled extensively in a battery of tests. In addition to good biochemical potency, it showed mid-nanomolar activity in a human whole blood assay and was also active in other assays, including a mouse arthritis model. Other attractive features included a clean profile against a plethora of off-targets, good oral bioavailability in mice, rats, and dogs, and a predicted human oral dose of 40 mg once daily. However, a two week toxicology study in rats and dogs was “slightly less favorable” than compound 1.

 

This is a lovely example of property and structure-guided drug design, and the researchers are refreshingly open about borrowing elements from other molecules, even from outside Novartis. Interestingly, a crystal structure of compound 3 bound to LTA4H revealed that while the overall binding mode was similar to compound 1, which contains the same left-hand portion, the pyrazole and pyridine rings rotated 180º to make different hydrogen-bond interactions. Another reminder that despite our leaps in predictive capability, molecules can still provide many surprises.