Stabilizing protein-protein interactions

Despite the fact that the second FDA-approved fragment-derived drug targets a protein-protein interaction (PPI), these types of targets have a well-earned reputation for being difficult. Most researchers try to disrupt PPIs. An alternative is to stabilize PPIs. This is not as crazy as it sounds: rapamycin, tafamidis, and PROTACs all stabilize PPIs. In a paper just published in J. Am. Chem. Soc., Michelle Arkin, Christian Ottmann, and collaborators at UCSF, Eindhoven University of Technology, Novartis, and the University of Duisburg-Essen bring fragments to bear on the problem.

The researchers were interested in the protein 14-3-3δ, a “hub” protein that binds to more than 300 other proteins (not all at the same time). One of these is estrogen receptor α (ERα): binding prevents the transcription factor from dimerizing and binding to DNA. The natural product fusicoccin A (FC-A) binds at the interface of 14-3-3δ and ERα and stabilizes that interaction, thereby inhibiting the growth of breast cancer cells. Because FC-A is a structurally complex natural product, the researchers sought fragments that would have a similar effect. They used Tethering, in which reversible disulfide bond formation stabilizes a protein-ligand complex, allowing its identification (see here and here). Specifically, fragments that bind near a cysteine residue are resistant to reduction, and the extent of binding can be detected by mass spectrometry.

The 14-3-3δ protein conveniently contains a cysteine residue in the vicinity of the ERα binding groove; the researchers used this native protein and also created two additional mutant proteins in which the native C38 cysteine was removed and new cysteine residues were introduced nearby. These three proteins were then screened against a library of 1600 disulfide-containing fragments under mildly reducing conditions in the presence or absence of a phosphopeptide derived from ERα. Most of the hits against the native protein were weak, but several hits against the N42C mutant were both resistant to reduction and also bound preferentially to the 14-3-3δ/ERα peptide complex compared to 14-3-3δ alone. Thus, ERα could enhance the binding of fragments to 14-3-3δ.

Next, the researchers used a fluorescently labeled peptide derived from ERα to show that one fragment could improve the apparent dissociation constant for the peptide and 14-3-3δ about 40-fold, from 1.3 µM 32 nM. Crystallography revealed that the cooperative fragments bound at the PPI interface, as expected given the location of the cysteine residues. The cooperative fragments placed a phenyl group in close proximity to a valine residue from the ERα peptide.

The researchers then examined the selectivity of one of their stabilizing fragments for other 14-3-3δ client proteins. In the case of a phosphopeptide derived from TASK3, which has a similar sequence to that of the ERα peptide, the fragment also showed cooperative binding. However, two peptides from other client proteins competed with the fragment for binding, and crystal structures revealed that the binding modes would be incompatible.

This is a nice illustration of site-directed fragment discovery to identify fragments that can modulate protein function in a more sophisticated manner than simple inhibition. One of the nice features of Tethering is that – like crystallography – it is able to identify extraordinarily weak binders. Unfortunately, this sometimes makes the hits challenging to advance: NMR experiments do show binding between a non-disulfide-containing derivative of one of the fragments and the 14-3-3δ/ERα peptide complex, but at high concentrations. It will be interesting to see whether this can be built into a potent non-covalent binder, and/or whether other types of covalent modifiers will be able to produce useful chemical probes for this target.

Metal-binding fragments vs GLO1

Practical Fragments has occasionally highlighted examples of metal-binding fragments. Strong interactions between low-molecular weight compounds and zinc, iron, or magnesium ions in metalloproteins makes for impressive ligand efficiencies. Unfortunately, some metal binders are PAINS and thus likely to inhibit a variety of targets; for others, the pharmacokinetic properties are not characterized. In a new J. Med. Chem. paper, Abraham Palmer, Seth Cohen, and colleagues at University of California San Diego describe a metallophilic molecule with in vivo efficacy.

The researchers were interested in glyoxalase 1 (GLO1), a zinc-dependent enzyme that catalyzes the clearance of the reactive metabolite methylglyoxal (MG). Although cytotoxic, MG may also have antidepressant effects. Thus, the researchers sought to find an inhibitor of GLO1.

They started by screening a library of 240 metallophilic fragments in a functional assay at 200 µM; more than 50 hits produced at least 50% inhibition. A second screen at 50 µM yielded 25 hits, including 8-MSQ.

Initial SAR studies revealed that both nitrogen atoms were essential for activity, suggesting a bidentate binding mode to the active-site zinc. Researchers at Chugai had previously reported a crystal structure of a very different molecule bound to GLO1, and this structure was used to model the binding mode of 8-MSQ. This exercise suggested growing from the sulfonamide, leading to compound 23. Incorporating information from other GLO1 inhibitors ultimately led to compound 60, with high nanomolar activity.

Those of you who have worked on drugs targeting the central nervous system may be concerned that compound 60 tends towards the large and lipophilic. However, when tested in mice at 12.5 mg/kg, it achieved a concentration of roughly 30 µM in the brain after two hours. Moreover, brain MG levels were increased 11-fold. Finally, mice dosed with compound 60 spent less time immobile in the forced swim test, a behavioral test used in rodent models of depression.

Overall, then, it seems that compound 60 has on-target activity in the brain and produces behavioral effects consistent with antidepressant activity. No selectivity data are provided, and because it could well be hitting other targets it is probably premature to use this as a chemical probe. Also, whether increasing the level of a toxic metabolite is a viable treatment for depression is likely to be hotly debated. Still, given the paucity of effective treatments for this widespread and devastating disease, it is nice to see researchers exploring bold mechanisms.

What will you do with hundreds of thousands of new ligands?

Ten years ago we highlighted a paper out of Brian Shoichet’s group in which 137,639 commercially available fragments were screened against the anti-bacterial target AmpC β-lactamase, resulting in a couple dozen weak hits, one of which was ultimately optimized to a picomolar covalent inhibitor. As evidenced by the devices in our pockets, computers have improved over the past decade. This is beautifully illustrated in a paper just published in Nature by Brian Shoichet, Bryan Roth, John Irwin, and an international team of collaborators at UCSF, UNC Chapel Hill, and labs in China, Ukraine, and Latvia.

Rather than limiting themselves to commercially available compounds, the researchers turned to a virtual set of make-on-demand molecules available from Enamine. These are built from 70,000 building blocks using 130 different two-component chemical reactions; 350 million molecules are currently available, with one billion expected by next year. The molecules exist virtually in the ZINC database, but can be physically ordered from Enamine as well. According to the Methods section of the paper, 93% of compounds ordered were successfully synthesized and delivered within six weeks.

The researchers screened 99 million virtual molecules using the program DOCK3.7. On average, 280 conformations of each molecule were fit into the active site in 4054 orientations. The top million compounds were then grouped by scaffold, and only molecules that differed considerably from known AmpC ligands and commercial compounds were considered further. Fifty one compounds were actually made and tested, of which five were active with affinities between 1.3 and 400 µM. Next, 90 analogs of these were synthesized, and more than half were active; the best came in at 77 nM, among the most potent non-covalent AmpC inhibitors ever reported. Crystal structures of several ligands from different scaffolds showed good agreement with the docking predictions.

For a test case against a very different binding pocket, the researchers turned to the D₄ dopamine receptor, against which they screened 138 million molecules in silico: 70 trillion different complexes, a process that took just 1.2 days using 1,500 cores. As with AmpC, the top hits were clustered, and anything resembling commercially available or known ligands was discarded. Of 549 compounds purchased and tested, 81 had K_i values of 8.3 µM or better. Many of the molecules were also active in functional assays, including full and partial agonists and even a couple antagonists. One molecule, a 180 pM agonist, was 2500-fold selective against the related D₂ and D₃ dopamine receptors. By way of comparison, in work published by some of the researchers just two years ago, the best hit from 600,000 commercial compounds was a 260 nM agonist which required three rounds of medicinal chemistry optimization to get to 4 nM.

How well did the hit rates correlate with the docking scores? The researchers separated the molecules screened against the D₄ receptor into a dozen “bins” and randomly chose 444 molecules from across the bins to make and test. Happily, the hit rates did in fact vary by score: among top bins, hit rates were 22-26%, dropping to 12% in the middle, and 0% at the bottom. Based on these numbers (and considerably more sophisticated analyses, including Bayesian statistics), the researchers suggest that the library of 138 million molecules contains more than 453,000 D₄ receptor ligands in more than 72,600 scaffolds with inhibition constants of at least 10 µM, and perhaps 158,000 with K_i values of 1 µM or better. These may well be conservative estimates, as they assume no hits among poorer-scoring molecules.

In a human-machine head-to-“head” contest, the researchers chose 124 of the top-ranked molecules manually and another 114 based on docking scores alone. Reassuringly, carbon-based systems held out over silicon, with hit rates for both sets around 24% but the human-chosen molecules typically having higher affinities, including the 180 pM winner. But while human performance will likely remain steady for the near future, machines will continue to improve.

On an academic level, the approach described in this paper could allow empirical tests of the molecular complexity hypothesis. It would be fascinating to see whether hit rates are higher for smaller molecules than larger ones, though of course smaller ligands are likely to have lower affinities and are thus less likely to be among the top hits. As in a previous analysis from Astex, one would need to compare hit rates among molecules with equal numbers of non-hydrogen atoms.

On a practical level, ultra-large library docking could be a game-changer for targets that have been structurally characterized. If the method proves generalizable, the question a decade hence may not be how to find hits, but rather how to choose between hundreds of thousands of them.

Taking a step towards STEP activators

Most drugs – and small molecule modulators in general – inhibit something, often an enzyme. Enzyme activation, on the other hand, is rare; we’ve highlighted just a few cases on Practical Fragments over the past decade. A new example is described in J. Med. Chem. by Christofer Tautermann and collaborators at Boehringer Ingelheim and the Beckman Research Institute of the City of Hope.

The researchers were interested in the protein tyrosine phosphatase non-receptor type 5 (PTPN5), also known as striatal-enriched protein tyrosine phosphatase (STEP). As its name suggests, this enzyme is found in the brain, and has been implicated in multiple neuropsychiatric disorders. However, phosphatases are tough targets due to their small, polar active sites. The problem is exacerbated for CNS targets, because negatively charged molecules have a hard time crossing the blood-brain barrier. Thus, the researchers sought allosteric modulators.

They began with a screen of 3083 fragments using STD NMR, differential scanning fluorimetry, and microscale thermophoresis. Validation of the several hundred hits by 2-dimensional NMR confirmed just seven, and comparison of the protein chemical shifts with those caused by a non-specific active site binder (sodium vanadate) suggested that compound 2 bound outside the active site. Crystallography confirmed this, revealing that the compound binds on the “back side” of the protein, about 20 Å from the catalytic pocket. The affinity was extraordinarily weak, with no functional activity, so the researchers used NMR to drive the SAR. Ultimately this led to fragment-sized BI-0314, with measurable affinity by isothermal titration calorimetry (ITC). Crystallography revealed that it binds in the same pocket as compound 2.

Surprisingly, far from being an inhibitor, BI-0314 actually showed activation of the enzyme in functional assays, increasing the activity by up to 60% at 0.5 mM. Careful mechanistic analysis revealed that this was due to an increase of k_cat, while the K_M for substrate was mostly unchanged. Molecular dynamics simulations suggested that BI-0314 increases the rigidity of the enzyme, and also stabilizes the active conformation. As expected of an allosteric modulator, the molecule was selective for STEP, with no activity (activating or inhibitory) for a couple other phosphatases.

As it turns out, the researchers were actually interested in STEP inhibitors, so they didn’t pursue BI-0314 further. As they note, there is still much to be done to generate a useful chemical probe, in particular improving potency. Laudably, the researchers are making BI-0314 available to other researchers free of charge. Perhaps someone else will be able to take this forward, as we’ve seen for other published fragments. And indeed, as researchers at Novartis have shown with asciminib, the transition from an allosteric binder with no functional activity to an inhibitor is possible – perhaps the same will hold true for an activator. If you are interested in STEP, you now have a new site to explore, and even a well-characterized starting point.