GAS41 revisited: a chemical probe

The YEATS domain of the protein GAS41 is an epigenetic reader that modulates gene expression by binding to acetylated lysine residues in chromatin. Multiple lines of evidence suggest it could be a useful target for various cancers, in particular non-small cell lung cancer (NSCLC). Four years ago Practical Fragments highlighted a paper from Jolanta Grembecka, Tomasz Cierpicki, and colleagues at the University of Michigan describing a fragment screen and subsequent optimization of a hit to molecules with some cellular activity. In a new J. Med. Chem. paper, the same team now describes molecules with better cell potency, as well as a negative control.

 

Compound 1, the initial fragment hit, had weak affinity for GAS41, but replacing the t-butyl group with a proline led to compound 7, with low micromolar activity in a fluorescence polarization assay. On the other side of the molecule, modification and growth of the amide moiety led to compound 16, also with low micromolar activity. In the 2021 paper, molecules related to compound 16 were dimerized to bind to two YEATS domains in close proximity in the GAS41 dimer. This yielded mid-nanomolar inhibitors, but the molecules were also large, with limited cell permeability. In the new paper, the researchers instead combined medicinal chemistry learnings and used structure-based design to generate monomeric molecules, culminating in DLG-41.

 

The affinity of DLG-41 for GAS41 was measured as 1 µM using isothermal titration calorimetry (ITC). In accordance with best practices for chemical probes, the researchers also developed a negative control by replacing the thiophene moiety with a thiazole; this compound, DLG-41nc, shows negligible activity in two different biochemical assays.

 

DLG-41 showed high nanomolar activity in a NanoBRET assay, demonstrating that the molecule is both permeable and binds to the GAS41 protein in cells. Importantly, the IC₅₀ for the negative control DLG-41nc was > 25 µM in this assay. DLG-41 blocked proliferation in a panel of NSCLC cell lines, though DLG-41nc also showed some activity, albeit at higher concentrations. Gene expression studies in one cell line showed that DLG-41 caused changes in hundreds of genes, while DLG-41nc was inactive.

 

This is a nice example of fragment optimization in academia. With both biochemical and cell-based potency around one micromolar, DLG-41 is hovering on the edge of the 2015 suggestions for a chemical probe. But used alongside the negative control, the compound should be useful for further exploring the biology of GAS41.

Surprise – a covalent histidine-targeting PDE3B inhibitor

Earlier this year I wrote about archiving crystallographic fragment data, and indeed a meeting is planned for early next year to establish guidelines. A new paper in J. Med. Chem. by Samuel Eaton and David Christianson at University of Pennsylvania illustrates why this is important.

 

The story starts with a paper published in 2024, also in J. Med. Chem., by Ann Rowley, Gang Yao, and collaborators at GSK and 23andMe. They were interested in finding inhibitors of PDE3B, a cyclic nucleotide phosphodiesterase that has been implicated in metabolic disease. However, this enzyme has a closely related counterpart significantly expressed in cardiac tissue: PDE3A, with 95% amino acid identity near the active site. So the researchers sought an inhibitor highly selective for PDE3B over PDE3A.

 

A DNA-encoded library (DEL) screen of 1.9 trillion(!) molecules was screened against both PDE3B and PDE3A. Hits were resynthesized without the DNA and tested in activity assays, leading to several chemical series, only one of which was selective for PDE3B. A key feature of this series was a boronic acid moiety, which was essential for activity. Optimization led to compounds such as GSK4394835A, with high nanomolar activity against PDE3B and >20-fold selectivity against PDE3A. The GSK researchers deposited a crystal structure of this molecule in the protein data bank (PDB), along with the structure factor amplitudes. It showed the boronic acid making non-covalent interactions with side-chain residues as well as the catalytic magnesium atoms and water molecules.

 

Further optimization at GSK led to compounds with as much as 300-fold selectivity for PDE3B, but like GSK4394835A, these were only high nanomolar inhibitors. The researchers could further improve potency, but this came at the expense of selectivity. Cell activity was modest at best, and the researchers noted that “the boronic acid is, in general, a challenge for development of an orally bioavailable drug.”

 

This is where the University of Pennsylvania researchers take up the story. As their paper points out, several drugs do contain boron, most notably bortezomib, which forms a covalent adduct with a threonine in the proteasome. When Eaton and Christianson took a closer look at the PDB entry showing GSK4394835A bound to PDE3B, they “noticed unusual features such as extra density around the boron atom of GSK4394835A, steric clashes between the boronic acid moiety and H737, and aberrant refinement statistics… from ideal bond lengths.” Upon re-refinement, they found that the boronic acid in fact makes a covalent bond with histidine 737. The structure explains why the boronic acid moiety was essential for activity, and the new paper suggest that other covalent warheads could potentially be used in place of the boronic acid. (Eaton and Christianson write that they contacted the GSK researchers in February of 2024, but it is not clear whether they heard back.)

 

This is a nice correction of the literature and a reminder not to take crystal structures at face value. The beauty of the PDB is that, with the experimental data deposited, the new researchers were enabled to re-refine the data even without input from the original authors.

 

As we’ve previously discussed, this example is not the only misleading crystal structure in the PDB. Many fragment structures have lower occupancy and more ambiguous electron density and would be even more prone to misinterpretation. As the community moves to establish guidelines for depositing fragment structures, it will be important to provide access to the raw data to facilitate this type of reanalysis.

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?