25 July 2022

Fragments vs TEAD: noncovalent this time

Last week we described a fragment-derived covalent probe that targets the four closely related TEAD transcription factors, which are part of the Hippo signaling pathway implicated in some cancers. A new paper in J. Med. Chem. by Timo Heinrich and collaborators at Merck KGa, iBET, and Cancer Research Horizons brings us another fragment-derived probe, this one noncovalent.
The researchers started by screening 1930 fragments, each at 2 mM, against TEAD1 and TEAD3 using SPR. Perhaps not surprisingly given the high concentration used, this led to a whopping 560 hits. These were then tested in dose-response format against TEAD1 with or without the coactivator YAP; 254 compounds showed differential affinity, among them compound 1. This molecule was crystallized bound to TEAD3, which revealed that it binds to the hydrophobic pocket normally occupied by a covalently-bound palmitoyl group required for activity. Despite being a fragment, compound 1 was active in a cell reporter assay, and the researchers state that further optimization was done using cellular assays rather than biophysical or biochemical experiments.

Analysis of the crystal structure suggested that enlarging the cyclopentyl moiety could fit more snugly into a hydrophobic pocket, while adding a small propyl moiety could extend into a separate pocket, leading to compound 6, with a 10-fold boost in activity. Replacing the propyl with an additional ring led to sub-micromolar compound 9. Finally, replacing the saturated ring with a substituted phenyl moiety led to MSC-4106, with low nanomolar activity in the cell reporter assay.
Thermal stabilization (specifically, nanoDSF) assays showed that MSC-4106 stabilized TEAD1 and TEAD3 but not TEAD2 or TEAD4. Palmitoylation assays confirmed this selectivity profile. The paper also includes a nice table comparing experimental selectivities of seven other non-covalent TEAD inhibitors, which vary from having activity only against TEAD1 to activity against all four homologs.
MSC-4106 was clean when tested at 10 µM against a panel of 58 receptors and 1 µM against nearly 400 kinases. It did not inhibit hERG or any of the common CYP450s. Finally, PK studies in mice, rats, and dogs showed that the compound is orally bioavailable with a long half-life. Given these favorable properties it was taken into xenograft studies, where it showed tumor growth inhibition at 5 mg/kg and tumor regression at 100 mg/kg. Analysis of tumor tissue showed downregulation of a TEAD-regulated gene, Cyr61.
Can we draw any lessons from comparing covalent MYF-03-176 (discussed last week) with non-covalent MSC-4106? Probably not, given that the former hits all TEAD homologs while the latter is selective for TEAD1 and TEAD3. Both molecules look to be excellent chemical probes for further dissecting Hippo signaling. I look forward to seeing how TEAD inhibitors ultimately fare in the clinic.

18 July 2022

From covalent fragment to lead against TEAD

As noted just last month, covalent fragment-based drug discovery is becoming ever more popular. However, many papers report relatively weak hits with little or no optimization. A new preprint posted to bioRxiv (HT Covalent Modifiers) by Tinghu Zhang, Nathanael Gray, and collaborators at Stanford and elsewhere describes a fragment-to-lead story for the TEAD family of transcription factors.
The four highly homologous members of the TEAD family play a role in the Hippo signaling pathway. When spurred by the coactivator YAP they cause gene expression that has been implicated in certain cancers, particularly mesothelioma. To bind YAP, TEAD needs to be palmitoylated on a specific cysteine residue. A covalent inhibitor that binds to this cysteine could prevent palmitoylation and thus block Hippo signaling.
Multiple academic and industrial groups have been pursuing this target, and one previously reported inhibitor is flufenamic acid. This molecule was used in the new paper to design a small library of analogs each functionalized with an acrylamide moiety. These were screened against TEAD2 and analyzed by mass spectrometry; MYF-01-37 modified the protein (though unfortunately time and exact concentrations are not specified). Proteolysis and tandem mass spectrometry confirmed that the molecule binds to C380, the site of palmitoylation.
Analysis of previously published crystal structures revealed a side pocket off the main hydrophobic channel that normally binds the palmitoyl group. The researchers created a focused library of analogs to try to access this pocket, which led to molecules such as MYF-03-69. This compound was active in a biochemical assay and showed rapid labeling of the protein as assessed by mass spectrometry. A crystal structure of the compound bound to TEAD1 confirmed the molecule forms a covalent bond to the target cysteine and does in fact bind in both pockets. 

MYF-03-69 inhibited palmitoylation of all four TEAD paralogs in biochemical assays. More importantly, it showed activity in several cell assays, including blocking palmitoylation and disrupting the interaction between TEAD and YAP. The molecule downregulated YAP-TEAD transcription in reporter gene assays as well as RNA sequencing assays. Finally, MYF-03-69 showed mid-nanomolar antiproliferative activity in mesothelioma cells but not in non-cancerous cell lines.
Despite this promising activity, MYF-03-69 lacked acceptable oral bioavailability. Further medicinal chemistry led to MYF-03-176, which has improved bioavailability and showed even better activity in reporter gene assays and better antiproliferative activity in mesothelioma cell lines. The molecule also led to tumor regression in a mouse xenograft model when dosed orally.
This is a nice story with lots of information, though were I a reviewer I would ask for the kinact/KI values for the molecules. This ratio describes the rate of covalent modification and is time and concentration independent, which makes comparisons with other molecules more straightforward (see this 2017 open-access paper for a good discussion). Since this is a preprint hopefully the final published paper will include these values. 
Regardless, MYF-03-176 looks like an excellent chemical probe for studying the effect of irreversible inhibition of Hippo signaling.

11 July 2022

Fragments in the clinic: HTL9936

Of the 50+ fragment-derived drugs that have entered the clinic, only two (both from Sosei Heptares) target transmembrane proteins, reflecting the difficulty of structure-based design for this hard-to-crystallize class of proteins. The story behind one of them was published late last year in Cell by Malcom Weir, Andrew Tobin, and a large group of collaborators.
The researchers were interested in the M1 muscarinic acetylcholine receptor, which is involved in memory and learning. By activating the receptor the hope is to be able to treat symptoms associated with Alzheimer’s disease. The M1 receptor has been a long-standing target for this disease, but previous drugs have caused side effects ranging from salivation and sweating to gastrointestinal distress and seizures. The M1 receptor is one of five closely related subtypes, and some of the side effects have been attributed to hitting the M2 and M3 receptors. However, the M1 receptor itself may also not be entirely innocent, so the goal was to develop a partial agonist, the idea being that this may be more effective in the brain, where the M1 receptor is highly expressed, while sparing other tissues where the M1 receptor is rarer.
The campaign began with a virtual screen of 1.6 million molecules (with molecular weights up to 400 Da) against a homology model of the human M1 receptor bound to a known agonist. This led to the purchase of 322 compounds, of which 16 were active in a cell-based functional assay, including compound 4. Fragment growing led to compound 6 and ultimately to HTL9936, which is selective for M1 over M2, M3, and M4 receptors. It also showed no significant agonism against a panel of 62 GPCRs even at 10 µM concentration.

Sosei Heptares pioneered the use of mutagenesis to stabilize specific conformational states of GPCRs, and this process was used to produce co-crystals with HTL9936 to understand its binding mode. Like other reported agonists, which were also characterized crystallographically, HTL9936 binds in the orthosteric site of the M1 receptor, but the increased size of the homopiperidine ring relative to other ligands provides selectivity over other receptors such as M2.
HTL9936 was tested in mice, rats, dogs, and cynomolgus monkeys, and in general showed good safety and brain penetration. The molecule even showed cognitive benefits in a mouse model of neurodegeneration and in aged beagles. It did cause an increase in heart rate and blood pressure in dogs, and there was a single convulsive episode, but only at a very high dose.
The paper also summarizes the results of human clinical trials which demonstrated that HTL9936 is well tolerated up to 100 mg doses, though at higher doses sweating, salivation, and changes in heart rate and blood pressure were observed. A small trial in healthy elderly people did not show any improvement in memory tasks, though functional magnetic resonance imaging studies did show that the molecule activated regions of the brain associated with cognition.
And that’s where the story ends. The Sosei Heptares website does not list HTL9936, though a different M1 receptor agonist (HTL0018318) is described. This paper also illustrates the long gap that can occur between research and publication: ClinicalTrials.gov lists three Phase 1 studies for HTL0009936, one of which began in 2013, and all of which ended by early 2017. Like most approaches to Alzheimer’s disease that have been tested, perhaps targeting the M1 receptor is a dead end. But reaching that conclusion requires highly selective chemical probes. Kudos to the team at Sosei Hetpares for their efforts.

03 July 2022

What belongs in the Protein Data Bank?

The rise of high-throughput crystallography is among the most exciting recent developments for fragment finding. Historically deemed too slow for primary screening, crystallography was reserved for select hits from an assay cascade. Now crystallographic screens up-front sometimes yield hundreds of hits. Many have been deposited in the Protein Data Bank (PDB). In a recent (open access) Protein Sci. commentary, Mariusz Jaskolski (Mickiewicz University), Bernhard Rupp (Medical University Innsbruck), and collaborators in the US question this practice.
In particular, the researchers ask whether molecules processed using Pan-Dataset Density Analysis (PanDDA) belong in the PDB. The method, which we described here, is typically used when hundreds of compounds have been soaked into crystals of the same protein. Most molecules will not bind, and these empty structures can be averaged to provide a background map to better identify weakly-bound ligands that may have only partial occupancy.
The researchers seem suspicious of this technique, referring to “supposed ligands” that may “confuse most biomedical researchers” and “degrade the PDB integrity,” the effect of which “could be disastrous.” To support their argument, they provide two examples from the PDB where the atomic models diverge from the electron density calculated using conventional methods and one with wonky statistics.
To avoid “contamination of the PDB by suboptimal structures,” the researchers suggest depositing structures from large-scale crystallographic screens in a separate database. Alternatively, they suggest clearer annotation. (To be fair, all three of the examples cited are already prominently marked “PanDDA analysis group deposition.”)
Needless to say, this is controversial. In a bioRxiv preprint, Manfred Weiss (Helmholtz-Zentrum Berlin) and collaborators in the US, Germany, Sweden, and the Netherlands, some of whom co-developed PanDDA, take a different view.
The researchers agree that group depositions need to be marked clearly, but they argue that they squarely belong in the PDB rather than in a separate repository. Moreover, “commentaries that underestimate the knowledge of PDB users, that ignore the opportunities present in heterogenous crystallographic data, and that miss out on chances for education on structure quality do more harm than good.”
The three examples described by Jaskolski and colleagues are re-examined, and while it is true that two of them do show poor occupancy using conventional methods, the ligands are clearly visible when PanDDA is used. (In the third case, there was an error in the resolution cutoff during automated processing, but the data could be successfully reprocessed manually.)
PanDDA was developed specifically to identify small, low occupancy ligands, so the researchers argue that these entries “cannot and should not be treated in the same way” as other ligands. Banning them from the PDB would potentially impede future research.
Weiss and colleagues refer to the Structural Genomics campaign of the late 1990s and early 2000s to solve myriad structures of diverse proteins, most of which were not being otherwise studied. At the time some commentators derided this effort as “stamp collecting.” Yet the number and diversity of structures thus deposited into the PDB likely contributed to the success of automated protein folding algorithms such as AlphaFold2.
Similarly, including structures from PanDDA processing could lead to unforeseen advances. For example, Weiss and colleagues suggest we may be able to “extract all aspects of conformational as well as of compositional heterogeneity out of all these data sets.” A better understanding of the role of protein dynamics in ligand binding is likely to require thousands of similar datasets of the kind being uploaded.
Personally, I believe that scientists should be wary of all published information. As the old saying goes, trust, but verify. As evidenced by my five-part series “Getting misled by crystal structures,” even conventional structures in the PDB should not necessarily be taken at face value. With that precaution, I’ll hold with the conclusion of Weiss and colleagues: “As long as the data is there, let’s embrace it and make it available!”