30 December 2018

Review of 2018 reviews

As 2018 recedes into history, we are using this last post of the year to do what we have done since 2012 – review notable events along with reviews we didn’t previously cover.

This was a busy year for meetings, starting in January with a FragNet event in Barcelona, then moving to San Diego in April for the annual CHI FBDD meeting. Boston saw an embarrassment of riches, from the first US-based NovAliX meeting, to a symposium on FBDD at the Fall ACS meeting, followed closely by a number of relevant talks at CHI’s Discovery on Target. Finally, the tenth anniversary of the renowned FBLD meeting returned to San Diego. Look for a schedule of 2019 events later this month.

If meetings were abundant, the same can be said for reviews.

Lead optimization
Writing in J. Med. Chem., Dean Brown and Jonas Boström (AstraZeneca) asked “where do recent small molecule clinical development candidates come from?” For three quarters of the 66 molecules published in J. Med. Chem. in 2016 and 2017 the answer is from known compounds or HTS, though fragments accounted for four examples. Although average molecular weight increased during lead optimization, lipophilicity did not, suggesting the importance of this parameter.

The importance of keeping lipophilicity in check is also emphasized by Robert Young (GlaxoSmithKline) and Paul Leeson (Paul Leeson Consulting) in a massive J. Med. Chem. treatise on lead optimization. Buttressed with dozens of examples, including several from FBLD, they show that the final molecule is usually among the most efficient (in terms of LE and LLE) in a given series, even when metrics were not explicitly used by the project team. Perhaps with pedants like Dr. Saysno in mind, they also emphasize the complexity of drug discovery, and note that “seeking optimum efficiencies and physicochemical properties are guiding principles and not rules.”

Lipophilic ligand efficiency (LLE) is also the focus of a paper in Bioorg. Med. Chem. by James Scott (AstraZeneca) and Michael Waring (Newcastle University). This is based largely on personal experiences and provides lots of helpful tips. Importantly, the researchers note that calculated lipophilicity values can differ dramatically from measured values, and go so far as to say that “this variation is sufficient to render LLEs derived from calculated values meaningless.”

Turning wholly to fragments, Chris Johnson and collaborators (including yours truly) from Astex, Carmot, Vrije Universiteit Amsterdam, and Novartis have published an analysis in J. Med. Chem. of fragment-to-lead success stories from last year. This review, the third in a series, also summarizes all 85 examples published between 2015 and 2017, confirming and expanding some of the trends we mentioned last year.

Two reviews focus on specific target classes. Bas Lamoree and Rod Hubbard (University of York) cover antibiotics in SLAS Discovery. After a nice, concise review of fragment-finding methods, the researchers discuss a number of case studies, many of which will be familiar to regular readers of this blog, including an early example of whole-cell screening.

David Bailey and collaborators from IOTA and University of Cambridge discuss cyclic nucleotide phosphodiesterases (PDEs) in J. Med. Chem. The researchers provide a good overview of the field, including mining the open database ChEMBL for fragment-sized inhibitors. As they point out, the first inhibitors discovered for these cell-signaling enzymes were fragment-sized, so it is no surprise that FBLD has been fruitful – see here for an example from earlier this year. Interestingly though, although at least six fragment-sized PDE inhibitor drugs have been approved, none of these were actually discovered using FBLD.

PDEs are an example of “ligandable” targets, for which small molecule modulators are readily discovered. In Drug Discovery Today, Sinisa Vukovic and David Huggins (University of Cambridge) discuss ligandability “in terms of the balance between effort and reward.” They use a published database of protein-ligand affinities to develop a metric, LIGexp, for experimental ligandability, and also describe their computational metric, Solvaware, which is based on identifying clusters of water molecules binding weakly to a protein. Comparisons with experimental data and with other predictive metrics, such as FTMap, reveal that while the computational methods are useful, there is still room for improvement.

We have previously written about how target-guided synthesis methods such as dynamic combinatorial chemistry have – despite decades of research – yielded few truly novel, drug-like ligands. Is this because the targets chosen were simply not ligandable? In J. Med. Chem., Anna Hirsch and collaborators at the University of Groningen, the Helmholtz Institute for Pharmaceutical Research, and Saarland University review some (though by no means all) published examples and examine their computationally determined ligandability scores. There seems to be no difference between these targets and a set of traditional drug targets.

Finding fragments
Crystallography continues to be a key tool for FBLD: as we noted in the review of the 2017 literature, 21 of the 30 examples made use of a crystal structure of either the starting fragment or an analog, and only 3 projects didn’t use crystallography at all. That said, FBLD is possible without crystallography, as illustrated through multiple examples in a Cell Chem. Biol. review by Wolfgang Jahnke (Novartis), Ben Davis (Vernalis), and me (Carmot).

In the absence of a crystal structure, NMR is best suited for providing structural information, and this is the subject of a review in Molecules by Barak Akabayov and colleagues at Ben-Gurion University of the Negev. The researchers provide a nice summary of NMR screening methods and success stories within a broader history of FBLD. They also include an extensive list of fragment library providers as well as a discussion of virtual screening.

Speaking of virtual screening, three reviews cover this topic. In Methods Mol. Biol., Durai Sundar and colleagues at Indian Institute of Technology Delhi touch on a number of computational approaches for de novo ligand design, though the lack of structures sometimes makes it challenging to read. A broader, more visually appealing review is published in AAPS Journal by Yuemin Bian and Xiang-Qun Xie at University of Pittsburgh. In addition to an overview and case studies, the researchers also provide a nice table summarizing 15 different computational programs. One of these, SEED, is a main focus of a review in Eur. J. Med. Chem. by Jean-Rémy Marchand and Amedeo Caflisch (University of Zürich). The researchers describe how this docking program can be combined with X-ray crystallography (SEED2XR) to rapidly identify fragments; we highlighted an example with a bromodomain. Their ALTA protocol uses SEED to generate larger, more potent molecules, as we described for the kinase EphB4. The researchers note that together these protocols have led to about 200 protein-ligand crystal structures deposited in the PDB over the past five years.

Rounding out methods, Sten Ohlson and Minh-Dao Duong-Thi (Nanyang Technological University) provide a detailed how-to guide in Methods for performing weak affinity chromatography, and how this can be combined with mass spectrometry (WAC-MS), as we noted last year.

One drawback of some computational approaches for fragment optimization is that they do not consider synthetic accessibility. In Mol. Inform., Philippe Roche, Xavier Morelli, and collaborators at Aix-Marseille University and Institut Paoli-Calmettes focus on hit to lead approaches that do, and provide a handy table summarizing nearly a dozen computational methods. We highlighted one from the authors, DOTS, earlier this year.

DOTS is an example of using DOS, or diversity-oriented synthesis. In Front. Chem., David Spring and colleagues at University of Cambridge review recent applications of DOS for generating new fragments, some of which we recently highlighted. Only a couple examples of successfully screening these new fragments are described, but the authors note that this is likely to increase as virtual library screening continues to advance.

Perhaps the most productive fragment of all time is 7-azaindole, the origin of three fragment-derived clinical compounds. (The moiety appears in both approved FBLD-derived drugs, vemurafenib and venetoclax.) Takayuki Irie and Masaaki Sawa of Carna Biosciences devote their attention to this little bicycle in Chem. Pharm. Bull. The researchers count six clinical kinase inhibitors that contain 7-azaindole (not all from FBLD) as well as more than 100,000 disclosed compounds containing the fragment. More than 90 kinases have been targeted by molecules containing 7-azaindole, and the paper provides a list of 70 PDB structures of 37 different kinases bound to molecules containing the moiety.

Finally, in J. Med. Chem., Brian Raymer and Samit Bhattacharya (Pfizer) survey the universe of “lead-like” drugs. Among the most highly prescribed small molecule drugs, 36% have molecular weights below 300 Da. Only 28 of 174 drugs approved between 2011 and 2017 fall into this category, consistent with the increasing size of newer drugs. The researchers discuss 16 recently approved drugs, and find that 13 have very high ligand efficiencies (at least 0.4 kcal mol-1 per heavy atom). As noted above, optimization often entails adding molecular weight by growing or linking, and the researchers suggest that alternative strategies such as conformational restriction and truncation also be investigated.

And with that, Practical Fragments wishes you a happy new year. Thanks for reading some of our 686 posts over the past decade plus, and please keep the comments coming!

17 December 2018

New types of covalent fragments

As covalent drugs become more accepted, covalent fragment libraries are becoming more popular: we’ve previously written about both reversible and irreversible fragments. One potential limitation is the number of different types of covalent modifiers, or warheads. The program DOCKovalent, for example, only considers ten classes. György Keserű and collaborators at the Hungarian Academy of Sciences and the University of Ljubljana go some way towards expanding this list in a recent paper in Arch Pharm Chem Life Sci.

The researchers were interested in heterocyclic electrophiles. For heterocycles, they considered pyridines, pyrimidines, pyrazines, imidazoles, pyrazoles, oxazoles, isoxazoles, and thiazoles. For electrophiles, they considered chloride, bromide, iodide, nitrile, vinyl, and ethynyl groups, often at different positions around a given heterocycle. So for example, they chose 2, 3, and 4-chloropyridine. Not every electrophile was available or easily synthesized for every heterocycle, so in total they assembled a library of 84 different fragments.

The library was tested for aqueous stability, and all but six fragments had half-lives of at least 24 hours at pH 7.4. Next, the researchers examined the intrinsic reactivities of their molecules by reacting them with glutathione, a physiologically relevant thiol. As might be expected, the different molecules showed a wide range of different reactivities, all of which are reported in the paper. This is a useful list: ultimately one wants a warhead with low or modest reactivity for better selectivity.

Next, the researchers tested their fragments against MurA from Staphylococcus aureus and Escherichia coli; this enzyme is important for bacterial cell wall biosynthesis, and contains an active-site cysteine that has previously been shown to be sensitive to electrophiles. The reactivity patterns were similar between the two enzymes, but they did differ somewhat from glutathione reactivity, suggesting the possibility of molecular recognition. Dose response assays were performed on the most potent molecules, most of which had IC50 values in the mid to high micromolar range. These results expand on research we highlighted six years ago showing that halopyridines could covalently modify a cysteine-dependent enzyme.

The researchers also examined the mechanism of their fragments by doing time-dependence and dilution experiments. Some of the results are quite unexpected, suggesting that, for example, 4-iodopyridine is a reversible modifier, which is hard to understand mechanistically. Perhaps, like the “universal fragment” 4-bromopyrazole, the molecule does not act covalently, though the time dependence observed suggests otherwise.

This is a nice example of how to create and assess a fragment library with a particular mechanism in mind, reminiscent of the metal-chelating fragments described by Seth Cohen and colleagues. Finally, I’d like to note that the first author, Aaron Keeley, is part of the FragNet training program. He and his fellow trainees will soon be looking for the next phase in their careers, so if you’re hiring keep them in mind!

10 December 2018

Poll results: library vendors

Our latest poll has just closed, and the results are quite interesting. We asked three questions:

1) Have you bought fragments in the past few years?
2) Which of the following vendors would you RECOMMEND?
3) Which of the following vendors would you AVOID?

First, a paragraph on methodology. The poll ran from November 3 through December 7. Due to the limitations of the free version of Crowdsignal (formerly Polldaddy), I have no way of knowing how many individuals responded to questions 2 or 3 (respondents could choose multiple answers). This was the purpose of question 1; 37 people answered yes, and 12 people answered no. Assuming that only people who answered yes answered questions 2 and 3, I divided the responses to questions 2 and 3 by 37 to give percentages. So for example, 33 people would recommend Enamine, which is 89%. If some people who answered no to question 1 answered 2 and/or 3, or answered questions 2 and/or 3 but not 1, the percentages may be overestimates. This seems possible, as the total number of people who would recommend or avoid Enamine adds up to 36. So either nearly everyone who said they bought fragments did so from Enamine, or more people responded than were accounted for by answering “yes” to whether they purchased fragments.

The results are shown here.

The first thing that jumps out is the popularity of Enamine – which is recommended by nearly 90% of respondents. Life Chemicals, Maybridge, ChemBridge, and Key Organics are each recommended by more than 30%, while Vitas-M, ChemDiv, and Asinex are each recommended by 16-24% of respondents. Seven other vendors were recommended by 2 or fewer respondents.

The second observation is that, for the most part, people seem fairly happy with their vendors: each named vendor would be avoided by fewer than 10% of respondents. That said, the relative numbers vary considerably: only one respondent would avoid Life Chemicals, while 18 would recommend them. In contrast, for some of the less popular suppliers, the number of people who would avoid them was comparable to the number who would recommend them.

Finally, I was pleased to see that although a few respondents selected “other” for vendors they would recommend, these were outnumbered by the number selecting “others” they would avoid. That suggests the list provided in the poll captured most trusted vendors. That said, there is no way of knowing whether, for example, the 7 respondents who chose to recommend “other” vendors all had the same vendor in mind, or up to 7 different ones.

Of course there are caveats (and more in the methodology section above). First, the response rate is lower than most of our other polls, reflecting the fact that library generation is not something done lightly or frequently. Second, the first question was deliberately vague; people may have different definitions of “past few years,” and some vendors may have improved or deteriorated. Third, we have no way of knowing how many organizations are represented; if many people responded from a single company this could bias the results. Fourth, we are dependent on the honesty of respondents – we don’t know whether vendors recommended themselves.

Finally, please leave comments, positive or negative, especially if you would recommend vendors not included in the poll. Remember, you can comment anonymously.

03 December 2018

Fragments vs lectins - allosterically

Carbohydrates are ubiquitous in nature but largely ignored in drug discovery. This is because interactions between carbohydrates and proteins, while important, tend to be quite weak; sugar binding sites in proteins rarely have deep, ligandable binding pockets. The few case studies we’ve highlighted (here, here, and here) have resulted in weak and/or large ligands.

However, you don’t need to target the active site to inhibit a protein: one of the most advanced fragment-derived drugs in the clinic is an allosteric inhibitor. Recognizing that many proteins contain secondary (and potentially allosteric) binding sites, Marc Nazaré (Leibniz Forschungsinstitut für Molekulare Pharmakologie), Christoph Rademacher (Max Planck Institute) and collaborators at Freie Universität Berlin and Berlin Institute of Health set out to find some, as they report in a recent paper in J. Am. Chem. Soc.

The researchers were interested in the protein langerin, a C-type lectin receptor involved in pathogen recognition. They screened the extracellular domain against a total of 871 fragments using a combination of NMR methods: STD, T2-filtered, and 19F NMR. A total of 78 fragments confirmed in at least two of these assays, of which 53 also confirmed by SPR. Three of these fragments inhibited the binding interaction between langerin and the polysaccharide mannan.

Next, the researchers acquired or synthesized more than a hundred derivatives of the active fragments and tested them in their battery of assays. Throughout the process they were careful to look for and exclude compounds that showed bad behavior such as aggregation or instability.

Ultimately, the best compounds showed triple-digit micromolar affinity by SPR and double-digit micromolar inhibition in the mannan-binding assay. Interestingly, these compounds do appear to be allosteric: they reduce the affinity of langerin towards mannan but don’t appear to directly block binding. Moreover, two-dimensional (HSQC) NMR studies suggest that the compounds bind to a different binding site on the protein than the carbohydrate does.

Of course there is still a long way to go: the compounds are far too weak to be useful chemical probes at this point. Still, this is a nice tour-de-force of biophysics. And perhaps – as we’ve seen before – someone else will be able to improve the potency of these molecules.