Fragments vs DHX8: towards a chemical probe

RNA helicases present an intriguing but challenging opportunity for drug discovery. Their importance for cell growth makes them attractive cancer targets. But to function, they must undergo considerable conformational changes, and this dynamism makes it difficult to find high-affinity inhibitors. In a new open-access J. Med. Chem. paper, Gurdip Bhalay, Rob van Montfort, and collaborators at The Institute of Cancer Research (ICR), Merck KGaA, and Proteros describe their efforts against DHX8.

 

DHX8 is one of 14 or so DEAH-box helicases and helps release mRNA from spliceosomes. Previous research had found it to be important for the cellular stress response as well as malignant cell transformation and progression, and siRNA-knockdown experiments showed that cancer cells were particularly dependent on DHX8 activity. Thus, the researchers set out to find a chemical probe.

 

The 2000-fragment ICR library was screened (at 300 µM) against the helicase domain of DHX8 using both surface plasmon resonance (SPR) and thermal shift assay (TSA). In addition, the full-length yeast homolog of DHX8, Prp22, was also screened by SPR to look for fragments that might bind outside the helicase domain. The TSA screen yielded 18 hits, while the SPR screen yielded 91, of which 63 also bound Prp22, while another 17 fragments bound Prp22 more strongly than the helicase domain of DHX8.

 

Eight-point dose response curves were collected for the hits, and 10/18 TSA hits gave a concentration-dependent response on both DHX8 and Prp22, along with 42/108 SPR hits, while another 5 SPR hits only bound to Prp22. Surprisingly, there were only 2 hits in common between the TSA and SPR hits; the researchers note the importance of using multiple orthogonal screens.

 

Next, the confirmed hits were tested in three ligand-observed NMR assays: CPMG, WaterLOGSY, and STD. Reassuringly, 39 were active in all three assays. Competition experiments suggested that the fragments did not bind in the ATP-binding site, but some of them were competitive with RNA.

 

Crystallography was attempted on several of the fragments, and compound 1 yielded a structure revealing that it did in fact bind in the “RNA-binding tunnel” of the helicase domain, with the carboxylic acid making contacts similar to a backbone phosphate. Although the dissociation constant (assessed by SPR) was > 1 mM, compound 1 was active in an ATP-hydrolysis assay and an RNA fluorescence anisotropy (FA) binding assay with triple-digit micromolar activity (values for the FA assays are shown here).

 

Much of the paper is devoted to the optimization of this fragment, which, true to the reputation of the helicase family, turned out to be difficult. Testing related compounds led to compound 6, with low micromolar activity, but despite extensive efforts it was impossible to improve the affinity much further. Thus, the researchers reexamined their larger compound collection for other similar compounds and identified compound 24. Although weaker than compound 6, a crystal structure revealed that the phenyl ring binds deeper into the RNA-binding tunnel, providing new opportunities for fragment growing. Structure-based design led to compound 34, with low micromolar activity, and further optimization ultimately led to compound 53, with submicromolar activity.

 

The mechanism of DHX8 requires the RNA-binding tunnel to open and close right where compound 53 sits, so its inhibitory activity can be attributed to blocking this motion. In addition to biochemical activity, the molecule also showed low micromolar activity in a cellular target engagement assay. However, no other cellular data are reported.

 

This is a textbook example of fragment finding and growing against a difficult target. The fact that the researchers returned to fragments after the initial series reached an affinity plateau is a useful reminder that it is all too easy to get stuck in a local minimum, and you may need to take a step back to make progress. Although compound 53 is just on the edge of what may be considered a chemical probe in terms of potency, it is the first reported nanomolar inhibitor of DHX8. The researchers also mention a second series derived from a different fragment, and it will be interesting to see if this yields even better molecules.

Site-specific HDX-MS for increased resolution

Most methods to characterize protein-ligand binding interactions have drawbacks. Crystallography, obviously, requires your protein to crystallize, while NMR and cryo-EM both have size limitations and are resource-intensive. Hydrogen-deuterium exchange mass spectrometry (HDX-MS), which we wrote about earlier this year, is theoretically faster and can apply to more proteins, but the technique provides limited resolution. Now a new open-access paper in J. Am. Chem. Soc. by Derek Wilson and collaborators at York University, the Structural Genomics Consortium, and SCIEX have improved the resolution down to single amino acids.

 

As we wrote in March, HDX-MS relies on the exchange between deuterium and protons on proteins; slower exchange is associated with more stable secondary structures. The exchange is detected by digesting the protein with proteases and determining the mass of the resulting peptide fragments using MS; incorporation of deuterons increases the mass of the peptides. If, for example, a peptide has three deuterons incorporated, the mass would increase by 3. However, in conventional HDX-MS, one can’t tell exactly where the deuterons have exchanged.

 

Last year the researchers described a method in J. Am. Soc. Mass Spectrom. to do just this using some clever mass spectrometry experiments. I won’t go into details as the paper is open access, but suffice it to say that it involves electron-activated dissociation (EAD) to fragment the peptides while preventing the scrambling of the protons and deuterons that normally limits resolution.

 

In the new paper, the approach was applied to the oncology target WDR5, which we previously discussed here. The researchers applied site-specific HDX-MS to three small molecule and two peptide ligands. All five of these ligands had previously been characterized by conventional HDX-MS as well as surface plasmon resonance (SPR), and four had also been studied crystallographically.

 

Reassuringly, the results from site-specific HDX-MS were mostly consistent with conventional HDX-MS, but there were some surprises. For example, the site-specific approach revealed protection from exchange for one amino acid (which makes a hydrogen bond to the ligand) and enhanced exchange for the adjacent amino acid on the same peptide. In conventional HDX-MS, the “peptide contains offsetting uptake increases and decreases, resulting in a ‘net-zero’ signal.”

 

The researchers also found that, for another residue, the change in HDX-MS signal correlates with the affinity of the ligand, as assessed by SPR. The mechanism is unclear since the concentrations of ligands were far higher than their affinities, but the results are intriguing.

 

The new paper describes just a single, well-behaved target, but if site-specific HDX-MS applies more broadly, it would offer a significant advance in obtaining structural information. The researchers note that the data analysis is currently “manual and prohibitively cumbersome,” a problem that should be solvable with automation. I look forward to seeing it applied prospectively to more targets, particularly if it works for weak binders such as fragments.

Filtering fluorescent frauds from fragments for PTP1B

Protein tyrosine phosphatase 1B (PTP1B) is a long-standing target for diabetes and other diseases. But as we’ve written previously, it is challenging to drug due to its small and highly charged active site, which is conserved among phosphatases. In a new open-access Drug Design Dev. Ther. paper, Frank Boeckler and colleagues at Eberhard Karls Universität Tübingen screen fragments against PTP1B and demonstrate the importance of distinct, rigorous controls.

 

The Boeckler group previously developed a fragment library enriched in halogens (HEFLib, which we discussed here) and a separate covalent fragment library (CovLib). These, as well as two other small libraries, were screened against PTP1B using a fluorescence activity assay. Compounds were incubated with the enzyme for an hour at 2 mM in the presence of a substrate (DiFMUP, 6,8-difluoro-4-methylumbelliferyl phosphate) that releases a fluorescent reporter (DiFMU) when hydrolyzed by the enzyme. A molecule that inhibits the enzyme should lead to less fluorescence. Samples were run in triplicate, and detergent was included to avoid aggregation artifacts. A total of 515 fragments were tested, leading to 56 preliminary hits, defined as molecules that decreased fluorescence by more than 50%.

 

A major challenge with fluorescence assays is that the compounds themselves can interfere with the readout. To assess this, the researchers retested their hits both before and after incubation of PTP1B with substrate. A fluorescence artifact should give similar activity in both conditions, while a true inhibitor should only cause a decrease in fluorescence when added at the beginning of the assay, before the protein has had a chance to process substrate. Unfortunately, only 11 hits passed this test.

 

To further confirm mechanism, the researchers developed an HPLC-based assay that separates the substrate DiFMUP from the product DiFMU. Because this assay detects PTP1B activity using separation rather than fluorescence, it should be immune from fluorescence artifacts. Only three of the 56 preliminary hits confirmed in this assay. Dose-response experiments revealed them to be quite weak, with IC₅₀ values above 5 mM. All three are potentially covalent inhibitors, and two showed reactivity with glutathione. PTP1B has a reactive active-site cysteine so covalent inhibitors are not surprising, though it remains to be seen how specific they are.

 

This paper is a useful reminder of the importance of validation: an initial 11% hit rate dropped to just 0.6%. Full experimental details for all the assays are provided, as are the structures of the hits, while SMILES strings of all 515 compounds screened are listed in the supplementary material. If you’re running a fluorescent fragment screen for the first time, this paper is worth consulting.

Merck’s journey from flatland

Back in 2009 we highlighted a paper, “Escape from flatland,” suggesting that molecules with higher fractions of sp³-hybridized (ie, non-aromatic) carbons are more likely to become drugs. This hypothesis has been challenged on methodological grounds, and an analysis last year concluded that “Fsp³ may not have been a useful metric to optimize.” Now a new J. Med. Chem. paper by Olivia Garry and colleagues at Merck weighs in on the debate.

 

The researchers calculated Fsp³ (number of sp³-hybridized carbons divided by total carbons) for millions of small molecules (MW < 1200) synthesized at Merck from 2000 through 2024. Interestingly, mean Fsp³ values dropped from 0.34 to 0.31 between 2000 and 2006 or so, coinciding with the increasing popularity of metal-mediated cross coupling reactions during that period. Since then, Fsp³ has risen to 0.40 in 2024, which could be due to the focus on “escaping flatland” as well as the increasing availability of saturated building blocks and new synthetic methodologies.

 

Consistent with the original publication, the average Fsp³ increases as molecules progress through development, from 0.34 overall to 0.36 for those that go into rat pharmacokinetic studies and to 0.38 for preclinical candidates – close to the 0.39 found for drugs approved since 2009 according to the study last year.

 

A key correlation proposed in the original flatland publication was that solubility increased with Fsp³, and this was observed again here. Of 435,280 compounds having Fsp³ between 0.00-0.70 with measured solubility data, 55% of those with more aromatic character had low solubility, while only 15% of those with Fsp³ > 0.65 were poorly soluble. The correlations held for solubility at neutral pH as well as at pH 2. Molecules with lower Fsp³ also tended to have more aromatic rings, and this has previously been shown to lower solubility.

 

In contrast to solubility, lipophilicity (logD) did not correlate with Fsp³ among 503,780 compounds. Apparent permeability showed a complex and noisy correlation for 16,570 compounds, leading the researchers to conclude that “Fsp³ is not a good parameter to optimize P_app.”

 

Inhibition of three cytochrome P450 enzymes, CYP 3A4, 2C8, and 2C9, was examined for 51,760 compounds. Weak trends were observed for the latter two, with highly aromatic compounds being more likely to inhibit the enzymes, but no trend was seen for CYP 3A4.

 

Inhibition of human ether-a-go-go-related gene (hERG) is a major red flag for compound progression, and here there was a correlation, with higher Fsp³ compounds showing lower inhibition. This trend held for both aminergic and nonaminergic molecules, though as with solubility these trends could be driven by aromatic ring count, which has independently been correlated to hERG inhibition.

 

Since the 2009 flatland publication, many solvents have been spilled to replace phenyl rings with more shapely, non-aromatic moieties. The researchers looked at matched molecular pairs for internal compounds to see what effects these changes had on solubility. Simply saturating a phenyl to a cyclohexyl ring tended to decrease solubility, while the best solubility improvements resulted from cyclopropyl or isopropyl substitutions. But these swaps did little for shapeliness: of the eight substitutions for which sufficient data existed, cyclopropyl and isoprproyl had the lowest increase of average Fsp³. As the researchers note, “using Fsp³ without consideration of other properties is not a good strategy to optimize solubility.”

 

Overall this study suggests that leaving the comforts of flatland may be worthwhile. Molecules with higher Fsp³ values are sometimes more challenging to synthesize, but this itself can lead to new intellectual property space.

 

It’s worth emphasizing that the correlations between Fsp³ and solubility, CYP inhibition, and hERG inhibition are limited. In the end, the researchers recommend “considering Fsp³ in combination with other factors in medicinal chemistry optimization as its standalone effect on specific properties is modest.” Just as general risk factors won’t predict whether any given person will contract a disease, metrics won’t predict whether any given molecule will succeed (or fail) as a drug.