20 June 2022

KinaFrag: a free, searchable database of kinase fragments

Four of the six approved fragment-derived drugs are kinase inhibitors, and three of these bind in the active site. Despite these successes, there are plenty of opportunities for new kinase-directed drugs, particularly those targeting cancer resistance mutations. In a recent Brief Bioinform. article, Guang-Fu Yang and colleagues at Central China Normal University describe a new tool to facilitate these discoveries.
 
The researchers started by trawling multiple databases such as kinase.com, DrugBank, ChEMBL, and the Protein Data Bank for kinase inhibitors. The results were combined and collated to yield a set of 7783 kinase-inhibitor fragment complexes, with more than 3000 unique fragments. Most of these bind in the “front cleft” of the active site, where the adenine of ATP normally binds, but several hundred also sit in the so-called back pocket or the intervening area.
 
What’s nice is that all this information is available on a free website called KinaFrag. You can download the structures yourself, but the site can also be browsed or searched. Fragments are annotated with links to various databases; here’s an example.
 
 
There are some bugs. While I was able to search by physicochemical parameters such as molecular weight and number of hydrogen bond donors, I could not get the substructure search to work. I’d be curious as to whether readers could do so.
 
To demonstrate the utility of KinaFrag, the researchers describe a case study in which they started with the anticancer drug larotrectinib, which inhibits TRK family kinases. However, the molecule is less effective against several mutations observed in the clinic. Examining the bound structure revealed that the mutations introduce steric clashes. Retaining the hinge-binding fragment while performing virtual screening of fragments from KinaFrag led to molecules such as YT3, potent against both wild type TRKA and two resistance mutants, and further optimization resulted in YT9. 
 

Not only was YT9 active against the wild type and mutant forms of TRKA, it showed good oral bioavailability and pharmacokinetics in rats. Encouragingly, the molecule slowed tumor growth in both wild type and mutant TRKA mouse xenograft models.
 
One could debate whether this is an example of FBLD; the discovery of YT9 could also be considered a classic case of scaffold hopping. But semantics aside, this is a nice example of thinking in terms of fragmenting molecules. More broadly, KinaFrag looks like a useful tool for work on kinases – especially if the substructure search works.

13 June 2022

Fragments vs HIV-1 Protease: Pocket-to-Lead

The drugging of HIV-1 protease is a classic structure-based design success story, as discussed in a guest post by Glyn Williams from the early days of the SARS-CoV-2 pandemic. The peptide origins of approved inhibitors such as saquinavir are obvious, and the residual structural features can present problems for oral bioavailability. Although there have been fragment screens against the enzyme, the hits do not seem to have been pursued, perhaps in part to the number of approved drugs. But viruses never stop mutating, and developing new chemical matter is prudent. In a recent J. Med. Chem. paper, Yuki Tachibana and colleagues at Shionogi describe a fragment-based approach.
 
The researchers started by performing a virtual screen, but none of the hits were active when tested in a biochemical assay. The active site of HIV-1 protease contains four hydrophobic subsites, and none of the virtual hits filled all four of them. Thus, the researchers chose to focus on fragments that could make some of the interactions while providing growth vectors to additional subsites. They call this a “pocket-to-lead” strategy.
 
Fragment 5 docked nicely into the active site; the hydroxyl group makes interactions with the catalytic aspartic acid residues, while the phenyl ring tucks into the S2 pocket. Growing into the S2’ and S1’ pockets led to molecules such as compound 9, which showed weak but detectable activity. (Astute readers will notice that the stereochemistry around the hydroxyl moiety has changed; both diastereomers are active.) A crystal structure of compound 9 bound to HIV-1 protease confirmed the predicted binding mode

 
Examination of the crystal structure revealed that the parafluorobenzyl substituent was not completely filling the S1’ pocket, and was also in a strained conformation. Replacing this with an alkyl substituent led to low micromolar compound 12. Finally, growing into the S1 subsite led to compound 14, a low nanomolar inhibitor with sub-micromolar antiviral activity.
 
This is a nice example of structure-guided, computationally-enabled fragment-based lead discovery that bears some similarity to the V-SYNTHES method we highlighted earlier this year. As the researchers note, the cyclic lactam found in fragment 5 had been used previously in HIV-1 protease inhibitors. It might have been possible to get to something similar to compound 14 from that earlier molecule. But regardless, compound 14 is emphatically non-peptidic. Whether it will lead to superior drugs remains to be seen, but the paper does say that further optimization is underway.

06 June 2022

What to make first? A new “Ring Replacement Recommender” provides suggestions

So you’ve run a fragment screen, gotten some hits, and validated them. What then? Looking for in-house or commercial analogs is always a good idea, but if you’re serious about a project you’ll eventually need to do chemistry, for example replacing one ring with another (say, a pyridyl for a phenyl). The possibilities are almost endless, especially if you don’t know how your fragment binds. In a new Eur. J. Med. Chem. paper, Peter Ertl and colleagues at Novartis describe a “Ring Replacement Recommender” to rapidly improve biological activity.
 
To determine which replacements are likely to improve affinity, the researchers turned to ChEMBL, a database of more than 2 million molecules and associated biological activity extracted from tens of thousands of publications. From these, more than 68,000 chemical series were chosen for analysis. Each series had on average 16 members, and at least three. The biological activity of each member of a series was compared with other members of the same series. (Importantly, the researchers intentionally excluded anti-targets such as hERG and CYPs so the tool wouldn’t inadvertently improve binding to these.) Focusing only on ring replacements that were reported in at least five publications led to a set of 26,762 changes. Changes could be as modest as adding a methyl substituent or more elaborate such as changing a single aromatic ring to a fused aromatic-aliphatic ring system.
 
One would think that most changes would have little effect, as had previously been seen in the case of methyl additions. Indeed about 65% of the replacements caused shifts in potency of 2-fold or less, which is probably within experimental error. However, 2860 replacements of 245 rings improved affinity at least 2-fold (averaging 3.5-fold), with 223 cases yielding greater than ten-fold improvements.
 
Analyzing the data further, the researchers found 80 ring systems that frequently led to improvements in affinity, and they suggest these could be used as “universal” or privileged building blocks. Strikingly, 74 of these are aromatic, confirming work from Cohen we highlighted in 2020 that proteins may favor “flat” rather than shapely molecules.
 
The researchers also extracted 9515 drugs and clinical compounds from ChEMBL and examined the component fragments. Of the 80 ring systems in the universal set, 19 are found in 50 or more drugs, with another 37 found in at least 5 drugs. This set may be a particularly attractive go-to list.
 
Importantly, not only are all the replacements available in the Supporting Information, the researchers have created a handy and free online tool. Just click on a ring of interest and the Ring Replacement Recommender provides suggestions, along with the average fold improvement observed and the number of publications used for the calculation.
 
To see how well it works, I looked at a couple recent examples which entailed ring changes. The indole to indazole replacement used in the TLR7/8 work described last month was not suggested by the Recommender, though in that case the researchers had the benefit of a crystal structure. On the other hand, a cyclobutyl to phenyl substitution for SARS-CoV-2-3CLp was correctly predicted to be beneficial.
 
Of course, as we’ve said repeatedly, affinity is only part of the battle in drug discovery, and the researchers emphasize that their recommendations may not improve physicochemical or pharmacokinetic properties. But for the earliest stage of a program, and especially in the absence of other data, it’s worth giving the Recommender a try.

30 May 2022

Covalent fragments vs Rgl2

Just over a year ago the FDA granted accelerated approval to sotorasib, the first marketed inhibitor of KRAS and the first approved fragment-derived covalent drug. In a recent ChemMedChem paper, Samy Meroueh and colleagues at Indiana University School of Medicine describe their efforts against a protein in a related pathway.
 
KRAS is a GTPase which cycles between an “on” state, where GTP is bound, and an “off” state, where GTP is hydrolyzed to GDP. KRAS is just one member of a superfamily of GTPases. Two other members also associated with cancer include RalA and RalB. Sotorasib acts by binding to a mutant form of KRAS in which a glycine is replaced by a cysteine, but this mutation does not occur in RalA or RalB. An alternative approach to targeting GTPases is to prevent them from becoming activated by guanine exchange factors (GEFs), which help exchange GDP to GTP. We’ve previously written about how fragments have led to noncovalent inhibitors of the GEF SOS1, which activates RAS proteins.
 
To sum up, there’s more than one way to block GTPase activity: directly, or by preventing activation by an associated GEF. The new paper focuses on Rgl2, a GEF that serves RalA and RalB.
 
Rgl2 sports four surface-exposed cysteine residues, so the researchers screened the protein against a library of 1260 electrophilic fragments at 75 µM for 24 hours at 4 °C and then assessed whether it could still activate RalB. 50 fragments inhibited guanine nucleotide exchange by at least 30%, and a dozen were studied in detail. All were time-dependent inhibitors and had EC50 values from 2.6 to 120 µM at 24 hours.
 
Next, the researchers mutated each of the four surface-exposed cysteine residues to serine. The twelve fragments still inhibited all the mutants except C284S. SOS1 does not contain a cysteine at the position corresponding to C284, and indeed none of the twelve fragments significantly inhibited SOS1 activation of KRAS. All this suggests the fragments act via modification of C284.
 
The easiest and most direct measurement of covalent binding is with intact protein mass spectrometry, and the researchers confirmed that 10 of the 12 fragments did in fact form adducts. Interestingly, Rgl2 was modified two or three times by each fragment, which is perhaps not surprising given that they had relatively reactive warheads (chloroacetamides or propiolamides). Mass-spec studies with the mutants revealed that most of the modifications were at C284 and C508.
 
Whether or not these fragments are advanceable, the discovery that modification of C284 inhibits Rgl2 is useful. Interestingly, C284 is near but not at the Ral binding interface, and the researchers suggest that their fragments block protein activity allosterically. I believe such allosteric sites are common throughout the proteome, and readily addressable using covalent approaches. Watch this space!

23 May 2022

A fragment-sized chemical probe for Notum

Practical Fragments has written previously (here and here) about the enzyme Notum, which shuts down Wnt signaling by removing a palmitoyl group. Aberrant Wnt signaling is implicated in maladies from cancer to osteoporosis, but Paul Fish has been particularly focused on neurological conditions such as Alzheimer’s disease. In a paper just published in J. Med. Chem., Fish and collaborators at University College London, University of Oxford, and The Francis Crick Institute describe their discovery of a chemical probe for this target.
 
As we discussed last year, the researchers conducted a crystallographic screen of the 768-member Diamond-SGC Poised Library, which resulted in 59 hits. Biochemical confirmation studies revealed that fragment 6b, a close analog of a fragment described earlier, is remarkably potent. The substituted phenyl ring nicely fills the lipophilic active site, and the triazole forms a hydrogen bond with a backbone amide of the protein. Structure-based design subsequently led to compound 7y, with low nanomolar potency.
 

The previous fragment-based efforts against Notum also yielded potent molecules, but they had poor brain-penetration. In contrast, compound 7y has a high brain-to-plasma ratio, though the compound also has high clearance, which was attributed to phase 2 metabolism at the hydroxyl. The researchers explored a variety of replacements and substitutions, all of which led to loss in potency, but interestingly removing the hydroxymethyl substituent altogether was tolerated.
 
The resulting molecule, ARUK3001185, is a potent inhibitor of Notum both in biochemical and cell assays. It has good oral bioavailability and pharmacokinetics in mouse and rat. Importantly, it also has excellent brain penetration in both species. The molecule showed virtually no inhibition of 39 other serine hydrolases or 485 kinases and was fairly clean in a safety panel of some four-dozen human targets, including hERG. In other words, ARUK3001185 appears to be an excellent chemical probe.
 
This is a nice example of how a fragment-sized molecule can nonetheless achieve high affinity and selectivity. As we’ve seen repeatedly, potency is not enough; one often needs to spend considerable effort to optimize other properties such as brain penetration. It will be fun to see what this new probe can teach us about Wnt signaling in the brain.

16 May 2022

SAMPL7: Epic computational fail or just no solution?

Every few years computational chemists are invited to compete in the Statistical Assessment of Proteins and Ligands (SAMPL) challenges. Researchers are asked to solve a problem for which the solution is known but not yet published; this blinded format allows a more rigorous test of methods than the typical retrospective studies. SAMPL7 focused on fragments binding to proteins, and the results have been published (open access) in J. Comp. Aided Mol. Des. by Philip Biggin and collaborators at University of Oxford and elsewhere.
 
The subject of this challenge was PHIP, a multidomain protein implicated in insulin signaling and tumor metastasis, though the biology is a bit complicated. PHIP contains two bromodomains, small modules that act as epigenetic readers by binding to acetylated lysine residues (Kac), and the researchers chose to focus on the second bromodomain (PHIP2). Bromodomains have proven to be highly ligandable, though this one is unusual in having a threonine in place of a conserved asparagine.
 
The experimental results that contestants were challenged to predict came from fragment screening using high-throughput crystallography at Diamond Light Source’s XChem. PHIP2 crystals diffracted to high resolution (1.2 Å) and were soaked with 20 mM fragment for 2 hours at 5 °C. In total 799 fragments were screened: 768 from the DSI-poised library (see here) and 31 FragLites (see here). The team took great pains to gather high-quality data, screening the FragLites twice and re-soaking 202 fragments that produced poor R factors or resolution worse than 2 Å. This resulted in 52 hits, a hit rate of 6.5%, consistent with the 2-15% typically seen at XChem. Most (47) of these were in the Kac-binding site, and these were the focus of the SAMPL7 challenge.
 
The first task was for modelers to simply predict which of the 799 fragments bound and which did not. Full experimental details were provided, including pH and the crystallization conditions. Entrants were given 1 month. There were eight submissions plus a control, which randomly selected compounds as binders or non-binders. Most of the contestants used some sort of docking strategy; details are provided in the paper.
 
Shockingly, none of the submissions scored better than random. Three of the entrants failed to correctly identify a single binder, and four identified between 1 and 5 of the 47.
 
The second task was to predict the binding modes of the crystallographically identified ligands. Contestants were provided with the 47 hits and asked to submit up to five poses for each. Perhaps stung from their performance on the first task, or perhaps put off by the two-week requested turnaround time, only five groups submitted entries.
 
Performance was assessed by calculating the root mean square deviation (RMSD) between the experimental and docked structure(s), with RMSD ≤ 2 Å considered successful. Despite this fairly lenient cutoff, “the performance of the methods was disappointing.” The best scored 24%, while two methods scored 2% and 0%. I’ll leave it to chemists to opine whether even a 24% success rate for docking would give confidence to embark on analog synthesis.
 
The third task was to select follow-up molecules from a large database for experimental validation, but alas “the COVID-19 pandemic resulted in a diversion of funds before this follow-up study could be done.” Nonetheless, four intrepid groups submitted entries, and these are discussed in the paper.
 
Taken at face value, this is downright damning for computational chemists. It is also at odds with many nice success stories, for example those described at last month’s DDC conference. So what’s going on?
 
For one thing, not everyone paid attention to the information provided. The crystals were at pH 5.6, but some of the entrants nonetheless assumed pH 7.4.
 
This raises a second and more important point. As the researchers acknowledge, “there is the possibility that our fragments do not necessarily bind in solution, whereas scoring functions are almost always calibrated and validated against solution and structural data.” In other words, perhaps the fragments were not identified computationally because they only bind extremely weakly to a crystalline protein soaking in dilute acid.
 
This highlights perhaps the biggest drawback of fragment screening by crystallography: no matter how beautiful the structure may appear, you get no measure of affinity. Indeed, a paper we highlighted last year was able to confirm binding by NMR for only a minority of crystallographically identified fragments against the SARS-CoV-2 main protease. This does not mean that the crystal structures are “wrong,” but the ligands may be so weak as to be unadvanceable.
 
A picture can be worth a thousand words, but it can also be misleading. Advancing fragments is best done with the help of multiple orthogonal methods.

09 May 2022

Fragments vs TLR7/8, starting from HTS

The toll-like receptors TLR7 and TLR8 are closely related proteins that respond to single-stranded RNA, often associated with viral infection, to activate the immune system. While this is useful to ward off disease, when the proteins become overactivated they can lead to autoimmune disorders such as lupus (see here for a recent discussion by Derek Lowe). In a recent ACS Med. Chem. Lett. paper Claudia Betschart and colleagues at Novartis describe advancing a fragment to a potent inhibitor of both proteins.
 
The researchers built a biochemical (specifically, a TR-FRET competition) assay in which they screened 50,000 molecules, each at 20 µM. The campaign yielded some 1500 hits, and this 2020 paper describes the optimization of one of these.
 
The new paper describes the optimization of a completely different molecule, compound 2. This rule-of-three compliant fragment was not only potent in the biochemical assay, it also showed low micromolar cell activity. A crystal structure of the compound bound to TLR8 revealed that it binds at the interface of a homodimer, making hydrogen bonds to both monomers and stabilizing an inactive conformation of the receptor. 
 

A carbon atom in compound 2 was replaced with a nitrogen in compound 3 in the hopes of picking up an additional hydrogen bond, and this led to a ten-fold increase in potency. TLR8 is located in acidic endosomes, and adding a basic piperidine moiety to try to optimize the subcellular localization did in fact improve cellular potency for compound 5. However, basic amines are often associated with hERG binding, which can cause cardiac problems, and this turned out to be the case for this series. This liability was addressed by adding a fluorine to lower the pKa of the amine. Further addition of small moieties to complement the protein led to additional increases in potency, ultimately yielding compound 15.
 
In addition to low nanomolar and even picomolar cellular activity against TLR7 and TLR8, respectively, compound 15 is selective against other TLRs as well as a panel of 100 off-targets. The compound has good DMPK properties in mice and reduced TLR7-dependent interferon-α release in a mouse model.
 
This is a nice medicinal chemistry story focusing on all aspects of optimization, not just potency. Like last month’s Notum and SARM1 posts, it is also another example of a fragment rising to the top of a high-throughput screen. Fragments don't have to be weak.

02 May 2022

Fragment events in 2022 and 2023

The first third of 2022 has already been graced with two major fragment conferences. Two more have recently been added, and 2023 is starting to take shape.

May 9-11:  While not exclusively fragment-focused, the Eighth NovAliX Conference on Biophysics in Drug Discovery will have several relevant talks, and for the first time will use a hybrid model, both online and in Munich. You can read my impressions of the 2018 Boston event here, the 2017 Strasbourg event here, and Teddy's impressions of the 2013 event herehere, and here.
 
May 24-25:  BioSolveIT is holding a DrugSpace Symposium, with a heavy emphasis on fragments. It's both virtual and free, with an impressive lineup of speakers.

September 28-30: FBDD Down Under 2022 will take place in beautiful Melbourne. If you've been longing to travel, Australia has recently opened its borders. This is the fourth major FBDD event in the country, and given the success of the first and third, it should be excellent.
 
October 17-20: CHI’s Twentieth Annual Discovery on Target will be held both virtually and in Boston, as it was last year. 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 2020 virtual event here, the 2019 event here, and the 2018 event here.
 
 
2023
April 10-13: CHI’s Eighteenth Annual Fragment-Based Drug Discovery, the longest-running fragment event, has already been scheduled for 2023 in San Diego. This is part of the larger Drug Discovery Chemistry meeting. You can read impressions of 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 herehere, 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
 
September: FBLD 2020 was sadly canceled due to COVID-19, but FBLD 2023 is scheduled to be held in Boston (exact dates TBD). This will mark the eighth in an illustrious series of conferences organized by scientists for scientists. You can read impressions of FBLD 2018FBLD 2016FBLD 2014,  FBLD 2012FBLD 2010, and FBLD 2009.
 
Know of anything else? Please leave a comment or drop me a note!

25 April 2022

Seventeenth Annual Fragment-Based Drug Discovery Meeting

Last week the CHI Drug Discovery Chemistry (DDC) meeting returned triumphantly to San Diego. This was the best conference I’ve attended in years, which reflects not just the quality of the meeting itself but the fact that three-dimensional events are vastly superior to their 2D counterparts.
 
About 75% of the more than 700 attendees were physically present, though having a virtual option turned out to be wise; at least three of the speakers had COVID but were still able to present remotely. Although the FBDD track lasted just a day and a half, fragments were well-represented across the four days and ten tracks. I won’t attempt to summarize the more than 40 talks I attended but will just cover some broad themes.
 
Computational Methods
Seva Katritch (USC) described the V-SYNTHES approach we highlighted in January. This modular method enables computational fragment growing, in effect facilitating a search of 11 billion molecules from just 600,000 scaffolds. The method as described makes heavy use of Enamine’s make-on-demand molecules, and I think everyone in the audience was excited to hear that the company has started making and shipping compounds from Kyiv again.
 
In the comments to the blog post on V-SYNTHESES someone mentioned BioSolveIT, and Paul Beroza (Genentech) described using their software for a similar approach. One of the targets they investigated, ROCK1, was also investigated with V-SYNTHES, and both techniques yielded unique nanomolar inhibitors.
 
Jan Wollenhaupt (Helmholtz Zentrum Berlin) also mentioned BioSolveIT in the context of fragment growing by catalog. Fragments identified crystallographically from their F2X libraries (see here) were grown to low micromolar endothiapepsin binders. Interestingly an unbiased docking screen did not find these molecules, illustrating the utility of stepwise computational approaches.
 
DOTS is another approach to computational growing and docking enabled by rapid synthesis we’ve previously written about, and Xavier Morelli (CNRS) gave an update, including the fact that they plan to launch a webserver soon.
 
Physical Methods
Tim Kaminski (InSingulo) described an intriguing method for screening liposome-bound proteins such as GPCRs. Dyes incorporated into the liposome are visualized using single molecule microscopy, and the liposomes can be observed in real time binding to immobilized targets in 384-well plates. Tim mentioned that the instrument should be available for purchase next year.
 
A new take on an old method was described by Félix Torres (ETH), who discussed using photochemically induced dynamic nuclear polarization (photo-CIDNP) to increase the sensitivity of NMR, thereby reducing experimental times by a factor of 100. The method requires specialized fragments and a customized NMR, but they can currently screen 1500 fragments per day, and the approach could be particularly valuable for screening hard-to-express proteins.
 
Sticking with the theme of photochemistry, Rod Hubbard (Vernalis by way of Hitgen) discussed a DNA-encoded library of more than 130,000 fragment-linker combinations each containing a photoaffinity tag. Screening this against PAK4 yielded 425 hits, and of the 30 chosen for validation more than 90% confirmed by NMR or crystallography. As we noted in 2020, combining DEL and FBLD provides new opportunities for exploring chemical space.
 
It’s been a few years since we discussed weak affinity chromatography, and Kirill Popov (WAC) provided an update. They’ve applied the approach to more than 50 targets and have obtained hit rates up to 20%. An example against SMARCA4 yielded hits that were subsequently found to bind at two sites, one of which had not previously been described.
 
Covalent fragments continue to increase in popularity. FragNet alum Lena Muenzker (BI) described an intact-protein mass spectrometry screen of the E3 ligase SIAH1 against 1260 acrylamides, resulting in 214 hits. Crystallography has been successful, and they are planning to use these to generate covalent PROTACs.
 
We’ve previously written about screening covalent fragments in cells, and Benjamin Horning (Vividion) and Madeline Kavanagh (Scripps) described a nice chemoproteomics case study in which an alkynamide-containing fragment was identified that binds to cysteine 817 in the kinase JAK1. Optimization led to a low nanomolar binder that inhibits JAK1 signaling.
 
Cysteine is not the only amino acid amenable to covalent modification. Plenary keynote speaker Laura Kiessling (MIT) described squarate derivatives as tunable “Goldilocks” warheads for lysine, with the right balance of reactivity and stability.
 
Success Stories
Cases studies were abundant, including some new disclosures that I’ll hold off describing until they publish. Of course, drugs are the ultimate success stories, and several of these were presented. Svitlana Kulyk recounted the discovery of MRTX1719, Mirati’s MTA-cooperative PRMT5 inhibitor, including some interesting tangents not discussed in the publication.
 
Steve Fesik (Vanderbilt) gave two presentations on near-clinical compounds, one targeting MCL1 and the other WDR5. In both cases weak fragments were advanced to picomolar binders within one to two years, but it has taken much longer to optimize other properties of the molecules.
 
Indeed, this turned out to be something of a theme. Valerio Berdini (Astex) discussed the discovery of erdafitinib, the third approved FBLD-derived drug. The program started in 2006, and it took just nine months to go from the fragment hit to late lead optimization. But the compound didn’t enter the clinic until 2012, and it took until 2019 to be approved.
 
Similarly, Wolfgang Jahnke (Novartis) described the story of the sixth approved fragment-based drug. The fragment screen against ABL was conducted in 2006, but the project went through two near-death experiences. Asciminib finally entered the clinic in 2014, and it was approved last year.
 
But timelines are not destined to be long. We’ve previously written about vemurafenib, the first FBLD-derived drug, which took just six years from project initiation to approval. Ryan Wurz (Amgen) gave a retrospective on sotorasib, the fifth approved FBLD-derived drug. Amgen started the program in August 2012, sotorasib was first synthesized in early 2017, first dosed in humans in 2018, and approved in May of last year. Fast doesn’t mean easy: it took 110 co-crystal structures, and I counted more than 100 names on the acknowledgement slide. But success against KRAS is a welcome reminder that sometimes we really can accomplish the impossible when we work together.
 
This is a good point on which to close. Assuming SARS-CoV-2 doesn’t intervene, DDC is scheduled to return to San Diego April 10-13 next year. I hope to see you there!

18 April 2022

Fragments win in a virtual screen against Notum

Wnt proteins are implicated in a variety of diseases, from Alzheimer’s to colorectal cancer. The enzyme Notum shuts down signaling by removing a palmitoyl group from Wnt. Last year Practical Fragments highlighted several series of Notum inhibitors identified from biochemical and crystallographic fragment screens. The researchers behind those efforts, including Paul Fish and Fredrik Svensson (University College London), have now published a successful virtual screen against the enzyme in J. Med. Chem.
 
Starting with 1.5 million compounds available from ChemDiv, the researchers chose 534,804 based on a variety of computational filters including molecular weight (200-500 Da), number of hydrogen bond donors (<=2) and ClogD (-4 to 5). A virtual screen of these (using Glide) produced 1330 high-scoring hits, of which 1088 were chosen for purchase. Of these, 952 were available, a much higher percentage than the ZINC15-reliant paper we wrote about earlier this year.
 
All 952 compounds were tested in a biochemical assay, and the 44 that gave >50% inhibition at 1 µM were then tested in dose-response format. This yielded 31 compounds with IC50 values < 500 nM. These could be subdivided into four structurally related clusters and eight singletons. Further triaging removed compounds likely to cause assay interference as well as those similar to known Notum inhibitors. This left two clusters and two singletons.
 

Compound 1f was the most potent member of a series of 9 related (and possibly covalent) inhibitors. Although these strongly inhibited the enzyme in the biochemical assay, they were essentially inactive in a cell-based assay. They were also highly insoluble and showed low cell permeability, and were thus dropped.
 
Compound 2a was one of two related molecules that were also quite potent when initially tested. Unfortunately, when the molecules were resynthesized they turned out to be significantly weaker and were also not very soluble, so this series was also halted.
 
The singleton compound 3 turned out to be a covalent inhibitor; the catalytic serine formed an ester with the molecule. The mechanism is more fully described in this open-access J. Med. Chem. paper.
 
That leaves the second singleton. Compound 4d was not just active in the biochemical assay, it also showed sub-micromolar cell activity. SAR, guided by crystallography, ultimately led to low nanomolar inhibitors. The pKa of compound 4d was measured to be 7.9, which is less acidic than many previously reported Notum inhibitors and thus more likely to be cell permeable. This turned out to be the case experimentally, and the compound was also stable in mouse liver microsomes. Pharmacokinetics in mice were promising for several compounds, but unfortunately brain penetration – which the researchers were hoping for – was negligible. (This could be an advantage for peripheral diseases.)
 
This is a nice example of lead discovery in academia. Like last week’s post, it also illustrates that fragments themselves can be quite potent. Indeed, although the researchers were looking for molecules up to 500 Da in their virtual screen, all of the best hits were fragment-sized. Another illustration that small is beautiful.

11 April 2022

Nucleophilic fragments vs SARM1: in situ inhibitor assembly

Recently Practical Fragments wrote about nucleophilic fragments that could react with proteins or cofactors. Previously we’ve also written about in situ chemistry, in which a protein catalyzes the formation of an inhibitor. An interesting marriage of these concepts has just been published (open access) in Mol. Cell by Robert Hughes (Disarm Therapeutics), Thomas Ve (Griffith University) and a group of international collaborators.
 
The researchers were interested in the protein SARM1, which is implicated in the axon degeneration associated with several neurodegenerative disorders. Last year the researchers published a Cell Rep. paper (also open access) in which a biochemical screen of roughly 200,000 molecules led to the discovery of isoquinoline as a 10 µM inhibitor of SARM1. Optimization led to 5-iodoisoqinoline, dubbed DSRM-3716, a 75 nM fragment-sized inhibitor. The paper goes on to demonstrate that the molecule not only prevents axonal degeneration but can even promote recovery of injured axons. The new paper explores the mechanism of action.
 
SARM1 is an NADase: it cleaves the critical cofactor nicotinamide adenine dinucleotide (NAD+). While using NMR to study the mechanism of inhibition, the researchers found that DSRM-3716 reacts with NAD+ to form the new compound shown. In this sense, DSRM-3716 acts as a prodrug, somewhat analogous to sulfanilamide antibiotics which act as PABA mimics to block folate biosynthesis.
 

What’s behind the inhibition of SARM1? A series of crystallographic and cryo-EM studies of SARM1 reveal that the protein can self-associate into multimers which are either inactive or active depending on the relative orientations of the individual proteins. NAD+ normally binds at the interface between two SARM1 proteins. The compound made from NAD+ and DSRM-3716 binds here as well, blocking further activity. The crystal structures also revealed a clear halogen bond (see here) with the iodine in DSRM-3716, explaining the increased activity over isoquinoline itself.
 
Unlike the nucleophilic fragments we wrote about last month, isoquinoline probably won’t raise too many eyebrows among medicinal chemists, as the moiety is found in a handful of approved drugs. The researchers also demonstrated that DSRM-3716 itself is selective for SARM1 in a panel of other enzymes that use NAD+.
 
This is a lovely case of high-throughput screening in which the hit turns out to be a fragment. Indeed, the highly charged compound that actually inhibits SARM1 would not be cell-permeable, but that's just fine since it is formed inside cells. It is worth noting that nearly 1000 approved drugs could be classified as fragments in terms of molecular weight. In the case of CNS drugs, small is beautiful, and it will be fun to watch how far DSRM-3716 derivatives will be able to advance.

01 April 2022

Fragments in space!

Practical Fragments has discussed fragments on Mars and Venus, but those planets are just two small specks in a vast universe. Always thinking big, the luminaries at DREADCO (who previously brought us fragment screening in cells using cryo-EM) have set their sights on deep space. Their theoretical proposal has just been published in the Journal of Extraterrestrial and Space Technologies.
 
One of the big unknowns in molecular recognition is precisely how small molecule ligands approach proteins. To find out, the researchers propose creating a library of fragments, each of which is attached to a very tiny mirror. Proteins of interest would also have tiny mirrors affixed to them. Laser interferometry would be used to study the interactions of proteins and ligands in extremely dilute solutions.
 
One potential problem with this approach is gravity, which is hard to escape on Earth, so the researchers propose running their experiment at a Lagrange point. They had hoped to catch a ride on the James Webb Space Telescope, but the mirror fabrication has taken longer than expected.
 
Even for a secretive multinational megacorporation like DREADCO this will be an expensive endeavor, so they’ll probably have to wait until they’ve eradicated human disease before launching this project. In the meantime, they’re taking suggestions for protein targets – feel free to leave yours in the comments!

28 March 2022

Why HDX-MS is rare in FBLD – and practical tips to change this

Hydrogen/deuterium exchange mass spectrometry (HDX-MS) can help identify the binding site of a ligand, sometimes. Briefly, a protein-ligand complex is diluted into a solution of D2O; exchangeable hydrogens on the protein will be replaced by deuterium, and those that interact with the ligand will be protected. A comparison with the protein alone will thus reveal which region interacts with the ligand. Practical Fragments discussed the technique back in 2012 and 2014, but since then it has been mentioned only a handful of times. In a new paper in J. Am. Soc. Mass Spectrom. Yoshitomo Hamuro and Stephen Coales (ExSAR) provide insights into why it is rarely used in FBLD, and offer solutions.
 
The researchers argue that the main problem with using HDX-MS in FBLD is that fragments often have low affinities and low solubilities. A theoretical analysis reveals that “the concentration of a ligand, not the molar excess of a ligand over a protein, is the key to drive the equilibrium to complex formation.” A series of calculations with hypothetical ligands having dissociation constants of either 100 µM or 1000 µM reveals that changing the concentration of protein is unlikely to have much effect on the outcome of the experiment, whereas increasing the concentration of ligand will give cleaner data. The problem is that many fragments may not be soluble at sufficiently high concentrations.
 
To solve this challenge, the researchers provide two solutions. First, they suggest spiking ligand into the D2O exchange buffer; this will keep the ligand from being diluted.
 
A second fix is similar: rather than diluting a protein-ligand complex 1:9 into D2O, the researchers suggest a 1:1 dilution, so the ligand concentration drops only by half rather than by 10-fold.
 
High concentrations of ligand can potentially interfere with the mass spectrometry measurements, so the researchers also suggest using smaller volumes with higher concentrations of protein.
 
These all seem like simple, practical measures to make HDX-MS more applicable to FBLD, but unfortunately the paper does not actually provide any experimental proof of concept data, so I’ll put the question to you, dear readers: have you found HDX-MS useful in FBLD? If so, under what conditions?

21 March 2022

Nucleophilic fragments: the other kind of covalent inhibitors

Covalent fragment-based lead discovery is becoming increasingly popular, spurred on by the rapid discovery and approval of sotorasib. In general, covalent inhibitors contain cysteine-reactive electrophiles, though efforts are also targeting other amino acid residues such as serine and lysine. In all these cases though, the fragment contains an electrophile, while the protein contains the nucleophile. A new paper in J. Am. Chem. Soc. by Megan Matthews and collaborators at University of Pennsylvania and Oberlin College turns things around.
 
None of the twenty standard amino acids are electrophilic, but some proteins do use electrophilic cofactors, such as pyridoxal phosphate. Moreover, some proteins undergo post-translational modifications which introduce a pyruvoyl (Pyvl) or glyoxylyl (Glox) group onto the N-terminus; these contain, respectively, an electrophilic ketone or aldehyde. As we wrote about here, aldehydes and ketones can react covalently with hydrazines, and the new paper shows that the kinetics of this reaction vary – as expected – with the nucleophilicity of the hydrazine.
 
Next, the researchers assembled a library of 17 fragment probes containing both a nucleophile as well as an alkyne that could be used for click chemistry. These probes were screened against cells for 30 minutes at 37 °C, the cells were lysed, labeled proteins conjugated to a dye, and the whole gemish run on a denaturing gel; the results showed a wide range of reactivities for the different probes.
 
To assess which proteins were reacting with which probes, the researchers turned to isoTOP-ABPP, a chemoproteomic method we previously wrote about here in the context of electrophilic fragments. (Chemical biologists are fond of abbreviations, and they call this new approach with nucleophilic fragments “reverse-polarity activity-based protein profiling”, or RP-ABPP.) Three probes, P11, P12, and P13, were found to modify 98, 60, and 16 proteins, respectively. Remarkably, despite their small size and common hydrazine nucleophile, only a single protein was labeled by all three probes.
 

Two of the proteins labeled by P11 include secernin-2 and -3 (SCRN2 and SCRN3). The functions of these proteins are unknown, though genome-wide studies have associated SCRN3 with several diseases.
 
The requirement for the probes to contain both an alkyne handle and a nucleophile increases complexity, and the researchers recognized that they could use the probes in competition mode against fragments lacking the alkyne. They assembled a set of 45 nucleophile-containing fragments and treated cell lysates with these, followed by treatment with probe P11, click chemistry to introduce a fluorescent dye, and gel electrophoresis. Hydrazine-containing fragments that inhibited the binding of P11 were found for SCRN2, SCRN3, and the protein AMD1. Some of these fragments showed EC50 values less than 1 µM and were up to 25-fold selective for SCRN3 over SCRN2 despite the 54% sequence identity shared between the two proteins.
 
An orthodox medicinal chemist might sniff at the hydrazine moiety in these molecules, but it is worth noting that P12, P13, and P17 are all derived from approved drugs (carbidopa, hydralazine, and phenelzine; substructures colored blue).
 
The functional roles of Pyvl and Glox modifications in proteins are poorly understood, and whether modulating them will prove useful in treating diseases remains uncertain. But the best way to answer this question will be by inventing suitable chemical probes. This paper suggests that nucleophilic fragments may prove useful.

14 March 2022

Higher hit rates with heavier halogens

Halogen bonding is an esoteric type of molecular interaction. Any first-year chemistry student can tell you that halogens are electronegative. More advanced students learn that the electron density on a halogen attached to a carbon is not evenly distributed. Rather, an electron deficient region appears directly opposite the carbon bond on chlorine, bromine, and iodine atoms. This “σ-hole” can form attractive interactions with electron-rich moieties, such as backbone carbonyl atoms. These highly directional interactions can be useful alternatives to hydrogen bonds, especially since they allow a reduction in the number of hydrogen bond donors. But how to find them? This is the topic of a recent open-access paper in Frontiers in Chemistry by Frank Boeckler and collaborators at Eberhard Karls Universität Tübingen.
 
The researchers constructed a library of 191 commercially available halogen-enriched fragments (called HEFLibs), which we wrote about in 2019. Most fragments have a single halogen atom, though 15 have two of the same type (two chlorine atoms, for example). The initial publication had no screening data, but the new paper describes screening the library against four diverse proteins: the methyltransferase DOT1L, the oxygenase IDO1, and the kinases AAK1 and CAMK1G.
 
Ligand-detected STD NMR was used as the primary screen, with proteins present at 20 µM and fragments at 1 mM each in mixtures of two. Between 9 and 57 hits were found for each target, with unique hits for all the targets except DOT1L. Some fragments hit all four targets, including one similar to the "universal fragment" we highlighted here.
 
Interestingly, iodine-containing fragments gave higher hit rates than bromine-containing fragments, which in turn gave higher hit rates than chlorine-containing fragments. Specifically, 9 of 14 (64%) iodine-containing fragments hit at least one target, vs 51% and 35% for bromine- and chlorine-containing fragments.
 
To assess whether halogen bonding played a role, the researchers calculated maximum electrostatic potential (Vmax) for each fragment; this is a measure of the size of the σ-hole. Fragment hits tended to have higher Vmax values than non-hits.
 
One possible confounding influence is that aryl halides can react with cysteine residues in proteins, and indeed the researchers did find that some of their fragments are unstable in the presence of the cellular reducing agent glutathione.
 
To confirm the STD-NMR results with an orthogonal method, the researchers turned to isothermal titration calorimetry (ITC). Of 57 fragment-protein pairs tested, only ten gave KD values less than 1 mM, and nine were against the kinases; there were even a couple single-digit micromolar binders for AAK1. ITC is less sensitive than NMR, so some of the other fragments may bind too weakly to fully characterize.
 
Unfortunately, crystallography has been unsuccessful so far, so it remains unclear whether any of the hits are actually making halogen bonding interactions with the proteins. Halogens are good at filling lipophilic pockets, so it is perhaps likely that less specific van der Waals interactions are the key affinity drivers. But the Boeckler group has been pursuing halogen bonding for more than a decade, so I look forward to seeing more on this topic.
 
And in the meantime, happy Pi Day!

07 March 2022

Virtual screening succeeds against the SARS-CoV-2 main protease

Today marks exactly two years since Practical Fragments first mentioned SARS-CoV-2. Since then, COVID-19 has killed more than 6 million people worldwide. Multiple effective vaccines have been developed and approved, along with a couple small-molecule drugs, but the virus is here to stay, and more drugs will be needed. This brings us to an open-access paper published in J. Am. Chem. Soc. by Jens Carlsson (Uppsala University) and a large group of international collaborators.
 
The so-called main protease (Mpro, or 3CLp) has been an antiviral target since the earliest days of the pandemic; the work we highlighted two years ago focused on a crystallographic screen against this enzyme. The new paper describes two virtual screening approaches.
 
The first started with a library of 235 million virtual compounds, mostly from Enamine’s “readily available for synthesis” (REAL) collection. Each compound was docked in thousands of different orientations against the active site of Mpro using DOCK3.7. Despite the staggering numbers (more than 223 trillion complexes!), the screen took just a day on 3500 CPU cores. The top 300,000 compounds were clustered based on similarity, and 100 molecules were synthesized. Nineteen of these showed binding by SPR, and three also inhibited the enzyme. Crystal structures were obtained for two of these, and both bound similarly to the predicted binding modes.
 
Compounds 1 and 3 each contain a hydantoin moiety that makes multiple hydrogen bonds to the protein, and merging elements led to low micromolar compounds such as compound 15. Further optimization ultimately delivered compound 19.
 

Compound 19 was potent in SPR and biochemical assays. Though it binds noncovalently, it had comparable cellular activity to nirmatrelvir, the recently approved covalent inhibitor of Mpro. Compound 19 showed nanomolar cell potency against SARS-CoV-1 and MERS-CoV and good selectivity against ten human proteases. The in vitro stability and permeability of compound 19 are also promising.
 
In addition to this de novo virtual screen, the researchers performed a second screen starting from one of the fragments identified crystallographically at Diamond Light Source. Of 93 molecules purchased and experimentally tested, 21 showed binding by SPR and 5 of these also inhibited the enzyme, with the most potent compound showing low micromolar activity.
 
There are several lessons from this paper. First, despite searching hundreds of millions of compounds, the best hits had only modest activity. This is perhaps surprising given the high fragment hit rates observed against Mpro in crystallographic and NMR screens, though it is worth noting that those fragments were even weaker binders.
 
Second, the hit rate from the naïve virtual screen was similar to that from the experimentally derived fragment screen. The researchers suggest that perhaps docking “may be more proficient in ranking diverse chemotypes rather than differentiating between closely related elaborations of the same scaffold.” In other words, virtual screens seem better at evaluating diverse starting points rather many similar molecules.
 
Third, despite the fact that the de novo virtual screen was not explicitly fragment-based, compound 1 does actually adhere to the rule of three. From there, addition of just six atoms improved affinity by >600-fold while also improving ligand efficiency.
 
Finally, this work is a testament to the utility of combining massive virtual screening with readily synthesizable compounds: the researchers note that it took less than four months to progress from compound 1 to nanomolar inhibitors.
 
This work relied heavily on rapid chemical synthesis done in Ukraine. Indeed, the two most popular fragment suppliers are both largely based in that country. Over the years many of us have come to know Ukrainian scientists not just as trusted colleagues but also as friends. I wish them and their families safety, and strength.

28 February 2022

Photoaffinity fragment PhABits, faster

Practical Fragments has written previously about PhotoAffinity Bits, or PhABits, which are fragments designed to reveal binding (as opposed to inhibition). These fragments contain a photoreactive moiety such as a diazirine. When incubated with a protein target and irradiated by ultraviolet light, the diazirine transforms into reactive species that can react irreversibly with anything nearby. Intact protein mass spectrometry can identify whether a reaction has occurred, and further proteomics experiments can identify more precisely where the PhABits reacted.
 
One challenge with this approach is obtaining a library of PhABits; few are commercially available (though AstraZeneca is sharing a set). In a recent open-access Chem. Sci. paper, Jacob Bush and collaborators at GlaxoSmithKline and University of Strathclyde describe speeding up the process.
 
The approach is called direct-to-biology high-throughput chemistry (D2B-HTC). Recognizing that purification is often the rate-limiting step in library synthesis, the researchers synthesized PhABits in 384-well plates and used the crude reaction mixtures directly. In short, a diazirine moiety linked to an activated ester was reacted for 24 hours with 1073 diverse alkylamines chosen from the GlaxoSmithKline internal collection. Interestingly, 54 of the amines themselves were not pure as judged by LC-MS – a useful reminder of the importance of quality control. Ultimately, 853 of the reactions were deemed successful, with >80% purity. Residual activated ester was quenched with hydroxylamine, and the reactions were performed in biologically compatible DMSO so that they could be used directly.
 
Next, each member of the library was screened at 100 µM against human carbonic anhydrase I (CAI, at 1 µM), a well-characterized model protein. After UV light illumination (302 nm for 10 minutes) the reactions were analyzed by mass spectrometry, resulting in seven hits, defined as > 1.5% covalent adduct. Five of these contained a primary sulfonamide, a privileged pharmacophore for carbonic anhydrases. Dose response experiments gave similar results on both the crude mixtures as well as resynthesized, pure compounds, with the best molecule showing high nanomolar activity. All seven PhABits could be competed with the known ligand ethoxzolamide, suggesting that they bind in the active site of the enzyme.
 
The seven hits gave even higher levels of modification with carbonic anhydrase II (CAII), and four of the sulfonamide-containing hits were further characterized by proteolyzing the modified enzyme and using LC-MS/MS to determine the sites of modification. This revealed that the PhABits were reacting with either a glutamic acid or histidine residue at the entrance of the active site. As we discussed last year, the precise nature of the diazirine probe can affect which amino acid residues are likely to react.
 
Based on the SAR from the primary screen, a second 100-member library was constructed and screened without purification. This provided a much higher hit rate, with all 52 hits containing a primary sulfonamide.
 
I do wish the researchers had used an orthogonal method to assess the affinities of their molecules. One drawback of the approach, which they note, is that “the absolute value of the crosslinking yield is not indicative of binding affinity,” but it would be interesting to know whether there is any correlation at all. It would also be nice to get a sense of how often false negatives occur.
 
Still, D2B-HTC adds to the growing list of methods that screen crude reaction mixtures, alongside related approaches such as off-rate screening, Chemotype Evolution, and REFiLx. The future may be a bit dirty, but perhaps we can get to our destination faster.

21 February 2022

Ensembles of fragment structures guide selectivity

Scientists generally want structural information when a project begins, and ideally that structural information comes from crystallography. Most of us who have been doing drug discovery for a while can remember seeing the first structure of a favorite molecule bound to a target protein and being inspired, reassured, or sometimes confused. But as crystallography becomes increasingly high throughput, it is now not uncommon to obtain dozens or even hundreds of structures. What to do with all this bounty? In a recent open-access J. Chem. Inf. Model. paper, Mihaela Smilova, Brian Marsden, and collaborators at University of Oxford, the Cambridge Crystallographic Data Centre, and Exscientia describe one application.
 
Back in 2016 we wrote about a computational approach called hotspot mapping, which uses three small fragment probes (aniline, cyclohexa-2,5-dien-1-one, and toluene) to virtually explore potential binding sites and map hydrogen bond acceptors, donors, and apolar interactions. The idea was to predict binding sites and the key interactions likely to drive affinity. The new paper focuses not just on affinity, but on selectivity.
 
The approach starts by taking multiple structures of the same protein bound to various ligands, especially fragments. Ligands and water molecules are then removed, and hotspot mapping is conducted for each structure. Then, all the hotspot maps are combined to generate an “ensemble” hotspot map, which in theory should give a more complete picture of potential attractive and repulsive interactions than a single structure.
 
To assess selectivity, the ensemble hotspot map of one protein is “subtracted” from that of another. If the proteins are very closely related, this “selectivity map” might be empty: all the interactions for one protein would be present in the other. But if there are differences, they become very apparent.
 
Several retrospective case studies are provided. In the first, ensemble hotspot maps were generated from the closely related bromodomains BRD1 and BRPF1, using 23 and 26 fragment-bound structures, respectively. The selectivity map clearly shows the potential for a hydrogen bond donor on a ligand to bind to the backbone amide of a serine in BRD1; the corresponding residue in BRPF1 is a proline, incapable of making this interaction. And indeed, an examination of the literature revealed that this interaction had previously been used to generate inhibitors of BRD1 that were 15-fold selective over BRPF1.
 
The kinases p38α and ERK2 are also closely related, but selectivity maps generated from five p38α structures and 17 ERK2 structures revealed a hydrophobic pocket in the former but not in the latter. This pocket had previously been used to generate selective inhibitors of p38α. Similarly, 28 structures of CK2α and 32 structures of PIM1 were used to generate a selectivity map that also revealed a hydrophobic pocket that can form in the former protein and had been used to generate selective inhibitors.
 
Generally, the more structures available, the more informative the selectivity maps are. The researchers note that though they only used five p38α structures, the fragments were chosen to be diverse (and interestingly all of them made interactions in the hydrophobic pocket). Also, while some protein flexibility can improve the maps, too much is a problem. (For the kinases, only DFG-in structures were used, for example.)
 
This method is a nice synthesis of experimental and computational techniques. A skeptic might argue that it doesn’t provide fundamentally new information: in the examples provided, the selectivity features had already been found and exploited by medicinal chemists. But the automated process and the clear output may speed things up, especially for newer targets, and indeed the researchers note that it is being applied in-house at Exscientia.
 
Perhaps most importantly, if you’d like to try it yourself, the code is freely available here. Happy mapping!