Covalent fragments vs a SARS-CoV-2 helicase

Last week we wrote about the difficulties of trying to understand even well-characterized covalent inhibitors of well-characterized targets. Most projects have far less information, as illustrated in a recent paper in J. Am. Chem. Soc. by Ekaterina Vinogradova, Tarun Kapoor, and collaborators at Rockefeller University and Sanders Tri-Institutional Therapeutics Discovery Institute, who report the first inhibitors of a particular SARS-CoV-2 enzyme.

 

The researchers were interested in helicases, enzymes that unwind DNA, RNA, or both. To do so, helicases cycle between “open” and “closed” forms, with conformational changes of as much as 15 Å. That dynamism complicates structure-based drug design, and many screens have yielded false positives. An irreversible covalent inhibitor that remained bound to the enzyme through its gyrations would potentially be easier to optimize.

 

The protein nsp13 from SARS-CoV-2 is essential for viral replication and thus an attractive drug target. The researchers started by testing previously reported and reactive “scout fragments” in a functional assay. Compound 1 inhibited the enzyme, and mass-spectrometry (MS) assays revealed that it modified three sites on the protein. Although multiple modifications are not desirable, the enzyme does contain 26 cysteine residues, so it could be worse. Peptide mapping and mutagenesis experiments revealed that modification of cysteine 556 (C556) is responsible for the inhibitory activity of compound 1.

 

A series of analogs culminated in compound 3b, which had low micromolar activity after a four hour incubation and also seemed more selective than compound 1, with less modification of other cysteine residues. The enantiomer of compound 3b was at least 6-fold less potent, suggesting molecular recognition rather than simple reactivity. In addition to nsp13, the researchers examined two mammalian helicases with disease relevance, WRN and BLM, and found that compound 3b was modestly selective for nsp13. (The researchers find different inhibitors for these two enzymes, though these are weaker and not as extensively characterized as those for nsp13.)

Cysteine 556 is not in the ATP-binding site and does not seem to be involved with RNA binding, and the researchers suggest that compound 3b may act allosterically. It seems to be highly conserved too, which might mean mutational resistance is less likely to evolve.

 

As the researchers acknowledge, compound 3b contains a chloroacetamide warhead, which is likely too reactive and unstable to move forward into in vivo studies, let alone the clinic. Also, had I reviewed the manuscript I would have requested the researchers to provide k_inact/K_I values rather than merely IC₅₀ values; a rough calculation using the methodology in this paper suggests a modest 10 M^-1s^-1 for compound 3b. That said, the discovery that liganding C556 inhibits nsp13 means that working to develop more potent and selective molecules may be worth the effort.

Covalent complexities for kinase inhibitors

Covalent drugs are becoming increasingly popular. But as more researchers search for them, they may encounter pitfalls. A new paper in J. Med. Chem. by  David Heppner and collaborators at the State University of New York Buffalo, AssayQuant Technologies, and Eberhard Karls Universität Tübingen provides a nice roadmap for avoiding them.

 

The researchers focus on covalent inhibitors of epidermal growth factor receptor (EGFR), a kinase that is frequently mutated in cancer. The first drugs against this target, such as erlotinib, were non-covalent, and these have been largely displaced by more effective covalent molecules such as afatinib. Unfortunately, these earlier drugs are not effective against a common mutant (T790M), spurring the development of third generation molecules such as osimertinib, which was approved by the FDA in 2015. Osimertinib has been extensively studied, with more than 2800 references in PubMed. Yet it is not as well understood as you might expect.

 

The team uses this system to demonstrate how characterizing irreversible inhibitors is not simple. For reversible enzyme inhibitors, researchers frequently discuss IC₅₀ values or, when they are being more precise, inhibition constants (K_i). The latter are in theory absolute values that do not depend on concentrations of cofactors such as ATP. But for irreversible inhibitors, the IC₅₀ values change depending on how long (and at what concentration) incubation occurs. The proper assessment of an irreversible inhibitor is k_inact/K_I, which takes into account both the irreversible inactivation step (k_inact) as well as the inhibition constant (K_I). Note that K_i is not the same as K_I ; the former describes only the initial reversible association between protein and inhibitor, while K_I incorporates the irreversible step. Told you it was complicated!

 

And it gets worse. The researchers examined three irreversible covalent inhibitors under various conditions. In one condition, the inhibitors were pre-dissolved in 10% DMSO before being added to the assay mixture to give a final DMSO concentration of 1%. In another condition, the inhibitors were dissolved in pure DMSO before being added to the assay. Despite the final concentration of DMSO being the same (1%), the second condition gave k_inact/K_I values up to 11-times greater (more potent).

 

If subtle experimental variations in one lab can change values by more than an order of magnitude, you might expect the literature to vary even more, and you’d be right. In the case of osimertinib, the reported values of k_inact/K_I vary by nearly 500-fold. Some of the experimental parameters the researchers consider are concentrations of reducing agents such as DTT, which can react with covalent inhibitors, and serum albumin, which also contains a free cysteine residue. Although these did not seem to be problematic for osimertinib itself, they could affect other molecules.

 

Another consideration for kinases in particular is the concentration of the cofactor ATP. The value of k_inact/K_I itself will vary depending on [ATP], and the researchers describe how to calculate a “true” k_inact/K_I which could be used to compare the potency of a given inhibitor against the wild-type vs mutant forms of the enzyme. But while this is more theoretically rigorous, it may be less biologically relevant, since physiological ATP concentrations are less variable than differences in the Michaelis constant (K_M) for ATP for different kinases and mutants.

 

There is lots more to digest in this paper, including analyses of structure-kinetic relationships (SKR, akin to structure-activity relationships, or SAR) for different inhibitors and thorough experimental descriptions. The take-home message is that, due in part to different and often incomplete details, “potency measurements are generally difficult to compare among literature studies,” and “any potency assessments should include appropriate controls under the same conditions as the experimental inhibitors.”

What makes molecules aggregate?

The propensity for some small molecules to form aggregates in water has bedeviled fragment-finding efforts for decades. Indeed, the phenomenon was not fully recognized until early this century. Although plenty of tools are available for detecting aggregates, I still see too many papers that omit these crucial quality controls. As annoying as aggregation can be in activity assays, in certain cases it could actually be useful for formulating drugs. There has been speculation that the good oral bioavailability of venetoclax is due to aggregation. But despite computational methods to predict aggregation, the structural features of molecules that cause them to aggregate are still not well understood. In a new open-access Nature Comm. paper, Daniel Heller and collaborators at Memorial Sloan Kettering Cancer Center and elsewhere provide some answers.

 

The researchers had previously published an article describing how indocyanine green (ICG) could be used to stabilize and visualize aggregates, and they applied the same technique to examine the aggregation potential of a small set of fragments. Benzoic acid and 2-napthoic acid did not aggregate, while 4-phenylbenzoic acid did. Intrigued, the researchers tested a set of 14 4-substituted biphenyl fragments and found that those containing both a hydrogen bond donor and acceptor, such as acids, sulfonamides, amides, and ureas, could aggregate, while those containing only donors (aniline) or acceptors (nitrile) did not.

 

Fourier transform infrared spectroscopy was used to examine the stretching region of the carbonyl of 4-phenylbenzoic acid in various states: in an aqueous aggregate, in solution in either t-butanol or DMSO, or in the solid state. Interestingly, the aggregate most resembled the solid state, consistent with close-packed self-assembly as opposed to free in solution.

 

From all this, the researchers hypothesized that a combination of aromatic groups and hydrogen bond donors and acceptors was necessary for aggregation. However, having these features does not mean aggregation is inevitable. Neither 3-phenylbenzoic acid nor 2-phenylbenzoic acid formed aggregates, with the former precipitating while the latter remained completely soluble. These three phenylbenzoic acid isomers behave very differently despite the fact that they have the same calculated logP values, and the suggestion is that the latter two molecules are less able to form pi-pi stacking interactions that lead to stable aggregation.

 

Next the researchers examined the approved drug sorafenib, which had previously been shown to aggregate. This was confirmed, and the aggregates were characterized with a battery of biophysical methods including dynamic light scattering, transmission electron microscopy, and X-ray scattering, along with molecular dynamics simulations. The conclusion is that sorafenib forms amorphous aggregates whose assembly is driven by a combination of pi-pi stacking and hydrogen-bonding. A series of sorafenib analogs was synthesized, and those that could not form strong intermolecular hydrogen bonds were less prone to aggregation.

 

All of this is fascinating from a molecular assembly viewpoint and will help to explain and predict which compounds are likely to aggregate, for better or for worse. But as of now, experimental assessment is still best practice for any new compound.

Electrophilic MiniFrags vs HDAC8

In fragment-based lead discovery, small is good – at least down to a certain point. While most fragments consist of between 7 and 20 non-hydrogen atoms, some investigators have built libraries of much smaller fragments with at most 7 or 8 heavy atoms. We’ve written about MiniFrags and MicroFrags, which are typically screened crystallographically at high concentrations to find hot spots. In a new open-access J. Med. Chem. paper, Franz-Josef Meyer-Almes, György Keserű, and collaborators at the Budapest University of Technology and Economics, the University of Applied Sciences Darmstadt, and the University of Veterinary Medicine Vienna have applied the concept to covalent fragments.

 

The researchers started with a set of 84 fragments, all heterocycles functionalized with one of six warheads, which we wrote about here. They systematically methylated nitrogen atoms on some of these to generate 58 more fragments containing obligate positive charges, such as compound B6+ below. The intrinsic reactivity of the fragments was assessed by reacting them with the biologically relevant thiol glutathione (GSH).

 

Methylating the heterocycles made them more electrophilic and thus more reactive. For example, only 16 of the 84 non-methylated fragments had a half-life (t_1/2) < 48 hours against GSH, in contrast with 30 of the 58 methylated fragments. In fact, 17 of the methylated fragments had t_1/2 < 10 minutes.

 

Next, all 142 fragments were screened at 250 µM for 2 hours at 30 ºC in a biochemical assay against histone deacetylase 8 (HDAC8), an enzyme important for cell cycle progression. Hits were confirmed in dose-response experiments after 1 hour pre-incubation. Consistent with the glutathione data, only 12 of the non-methylated compounds showed IC₅₀ < 50 µM, while 54 of the 58 methylated compounds were active. One of the fragments, B6+, had a k_inact/K_I value of 4006 M^-1s^-1, not far from that found in approved covalent drugs.

 

HDAC8 contains ten cysteine residues, and sites of modification were determined using both site-directed mutagenesis as well as tryptic digestion followed by mass spectrometry. In total, seven residues could be labeled by one or more fragments. The most reactive cysteine, C153, is close to the binding site of a previously reported inhibitor (compound 1), and the researchers tried merging reactive fragments such as B6+ onto this molecule. The best molecule, compound 3, had a k_inact/K_I value of 1566 M^-1s^-1. However, the drop from B6+ alone suggests that the non-covalent affinity component of compound 1 may have been lost.

 

This is an interesting approach, and as the researchers note, activity assays available for covalent fragments are higher-throughput than the crystallographic screens required for MiniFrags and MicroFrags. On the other hand, there are limitations. For one thing, the obligate positive charge on the methylated fragments could overwhelm other properties, and could even lead to denaturation of proteins at high concentrations, rendering screens uninformative. These fragments are also less likely to be cell permeable.

 

Finally, as we wrote ten years ago, characterizing irreversible covalent fragments presents a challenge in deconvoluting intrinsic reactivity from specific binding. Computational mapping of hot spots on HDAC8 using FTMap revealed that some correlate with modified cysteine residues. But other modified cysteine residues are in surface-exposed flexible loops with no nearby pockets, and hits against these are likely not advanceable. The fact that some of the fragments modify as many as five cysteine residues on HDAC8 suggests they may be too reactive.

 

Still, the systematic characterization of this library is useful experimentally and for training models. It will be interesting to see it deployed against additional protein targets.

Fragment events in 2024

We don't know for sure what 2024 has in store for us, but barring pandemics or other disasters, the year is shaping up to be an annus mirabilis for fragments. For the first time ever, all four of the recurring fragment meetings are scheduled for the same year, and other conferences also look exciting. I hope to see you at one.

March 3-5: RSC-BMCS Ninth Fragment-based Drug Discovery Meeting will be held in Cambridge, UK. This venerable biannual event will be particularly focused on case studies "that have delivered compounds to late stage medicinal chemistry, preclinical, or clinical programmes." You can read my impressions of the 2013 meeting here and the 2009 event here.

 

April 1-4: CHI’s Nineteenth 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 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. 

 

June 2-4:  The theme of the Tenth NovAliX Conference, to be held in the Swiss resort town of Brunnen, is "reinventing drug discovery." You can read my impressions of the 2018 Boston event here, the 2017 Strasbourg event here, and Teddy's impressions of the 2013 event here, here, and here.

 

June 25-27: FBDD Down Under 2024 will take place in beautiful Brisbane. I believe this is the fifth FBDD DU event and the first to be held outside Melbourne. You can read my impressions of FBDD DU 2019 and FBDD DU 2012.
 
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.

 

September 30 to Oct 3: Autumn is usually a nice time of year in Boston, so why not 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.

 

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