Fragments 2024

Last week saw the first of four dedicated fragment meetings this year: Fragments 2024, the 9^th RSC-BMCS Fragment-based Drug Discovery Meeting, was held in historic Hinxton Hall, Cambridge, UK. I won’t attempt to cover the 17 talks, 40+ posters, and 20 exhibitors in detail but just try to hit on some broad themes.

 

One highlight was a talk by Chris Swain, whose Cambridge MedChem Consulting has come up several times at Practical Fragments. Chris has been systematically cataloging fragment hits reported in the literature, and his database now includes >2500 fragments from >300 papers that hit 265 targets. This has not been easy: as we’ve noted in our annual F2L reviews, papers don’t always mention fragments in the title or abstract; sometimes you need to dig deep into the experimental methods to find out the origin of the initial hits, and even then there are questions of interpretation. Chris noted that the the drug aprepitat originated from a fragment-like pharamacophore extracted from a more complex literature compound. That story was published in 1998, predating the term “fragment-based drug discovery,” but perhaps it would be considered FBDD today.

 

The fragments themselves are a diverse bunch, with an average Tanimoto similarity of just 0.09, but there are small clusters. Looking at them in more detail, the ten most common scaffolds are aromatic (benzene, indole), which is a departure from approved drugs. There is also a significant fraction of charged molecules, including 298 acids and 348 basic groups. About 10% of the fragments hit more than one target, exactly what you would expect from the theory of molecular complexity.

 

Chris’s talk was followed by a wide-ranging panel discussion that expanded on some of these themes. Solubility was recognized as important, though with different techniques being more persnickety: Justin Dietrich (AbbVie) noted that pre-screening is critical for SPR, but for protein-detected NMR the protein is present at high enough concentrations to act as a “phase transfer reagent.”

 

The topic of thermodynamics also came up, with Chris Murray noting that Astex collects lots of ITC data but uses it for assessing free energy (ΔG) values rather than enthalpic energy (ΔH) values. Helena Danielson (Uppsala University) noted that the early correlation between compound quality and enthalpy found with HIV protease inhibitors did not seem to apply to other targets despite significant investment in collecting data at multiple companies, as also noted by Chris Smith (Mirati) and Mike Hann (GSK). Rod Hubbard (Vernalis) puckishly suggested that the study of ΔH had produced “more heat than light.”

 

The topic of MiniFrags also came up during the panel discussion. Chris Murray noted that they had been tried on quite a few targets but, as Rod Hubbard confirmed, were more helpful in identifying binding sites than providing starting points. But Chris Smith pronounced himself a “complete convert” after a MiniFrag identified an induced pocket on a previously intractable target where fragments (and other techniques) had failed.

 

Covalent fragments also made several appearances, with Jonathan Pettinger describing a phenotypic screen at GSK looking for compounds that block the pro-inflammatory M1 polarization of macrophages. After screening some 2000 covalent fragments they used chemoproteomics to determine that one of the best compounds acted by modifying cysteine 817 of the kinase JAK1. Interestingly, this is the same cysteine identified independently by researchers from Vividion, which could speak to the centrality of this target, the reactivity of this particular cysteine, or both.

 

Pursuing residues other than cysteine is seen as difficult, with Mike Hann noting in the panel discussion that these may require more extensive non-covalent interactions and Chris Murray noting that the warheads themselves were less attractive. But these challenges have not dissuaded Peter Cossar (Eindoven University of Technology), who has introduced cysteine-reactive disulfide and lysine-reactive aldehyde moieties into the same fragment to crosslink a 14-3-3 protein to substrate ERRγ.

 

Another theme was screening crude reaction mixtures in a “direct to biology” approach. Vernalis was an early adopter with their off-rate screening, and a talk by Lucie Guetzoyan confirmed that they are continuing to invest here not just with SPR but also with affinity-selection mass spectrometry and X-ray crystallography. Lucie also described using flow chemistry to enable sensitive organometallic chemistries such as Grignard and Negishi couplings. John Spencer (University of Sussex) is also using crude reaction screening by crystallography and thought the approach can compress ten years worth of work into a few months.

 

As with most conferences these days there were plenty of success stories. Martina Schaefer (Nuvisan) described the discovery of the Bayer SOS1 inhibitor BAY-293, which we wrote about here. Anna Vulpetti (Novartis) described the discovery of IL-1β inhibitors, which we wrote about here. Nicola Wilsher (Astex) described the discovery of potent SHP2 inhibitors; I’ll write more about these later. And Matthew Calabrese described the discovery of allosteric activators selective for the γ3 subunit of AMPK, which could avoid the cardiotoxicity seen with less selective molecules. Three HTS screens had failed but fragments ultimately led to a potent tool molecule. Interestingly, some of the HTS compounds were later found to be hits but had been overlooked because they were so weak that they did not rise above the noise of the assay.

 

Finally, Justin Dietrich described several success stories, including against TNFα (which we wrote about here) as well as CD40 ligand. Justin noted that FBLD is used alongside HTS and DEL at AbbVie, and that the techniques can be complementary – a theme noted by several others.

 

Despite being so intimately integrated with other discovery approaches, FBLD continues to innovate and evolve and remain sufficiently quirky that stand-alone meetings are still valuable and rewarding. I’m looking forward to seeing what the next several meetings reveal.

Review of 2022 reviews

The winter solstice is behind us in the Northern Hemisphere, which means 2022 is rapidly drawing to a close. As we have done for the past decade, Practical Fragments will spend this last post of the year summarizing conferences and reviews.

 

The remarkable progress in vaccines against SARS-CoV-2 allowed the full return of in-person conferences, and it was nice to see folks at CHI’s Discovery on Target in Boston and Drug Discovery Chemistry in San Diego. Nearly twenty reviews of interest to this readership were published, and these are covered thematically.

 

Targets

Several reviews cover the use of FBLD to target antiviral and antibacterial targets. Sangeeta Tiwari and colleagues at University of Texas El Paso cover both in an open access Pharmaceuticals review, focusing on tuberculosis and HIV, which often afflict the same individuals, leading to worse outcomes. The paper includes several tables with chemical structures, though the fragment origins of some molecules are not apparent.

 

Tuberculosis is caused by Mycobacterium tuberculosis, but there are more than 170 known members of the Mycobacteriaceae family. In an open access Int J. Mol. Sci. paper, the Tiwari group describes fragment-based approaches against these bugs. In addition to multiple examples, the review provides summaries of fragment finding methods and some of the challenges the field faces.

 

Another organism, Pseudomonas aeruginosa, infects the lungs of people with cystic fibrosis. In an open access Front. Mol. Biosci. paper, Tom Blundell and collaborators at University of Cambridge summarize fragment-based campaigns against this organism and its enzymes. The authors focus on structure-guided methods and note that the work is “at an early stage” but encouraging.

 

Switching to mammalian targets, Katrin Rittinger and colleagues at The Francis Crick Institute review (open access) applications of FBLD for targeting the ubiquitin system in Front. Mol. Biosci. The paper includes a nice table summarizing 15 examples that includes target, enzyme class, fragment binding mode, detection methods, and chemical structures of the fragment hit and optimized compound where applicable. Many of these are covalent modifiers; more on that topic below.

 

Finally, Tarun Jha, Shovanlal Gayen, and collaborators at Jadavpur University discuss “recent trends in fragment-based anticancer drug design strategies” in Biochem. Pharm. In addition to case studies (with chemical structures) of FBLD approaches against 18 oncology targets, the review covers fragment libraries, screening methods, optimization, and challenges.

 

Methods

Many of the targets above are challenging, and it’s always nice to be able to assess how challenging a project might be at the outset. In Curr. Opin. Struct. Biol., Sandor Vajda and collaborators at Boston University and Stony Brook University discuss (open access) “mapping the binding sites of challenging drug targets.” This is a brief, readable account of computational methods to identify hot spots, including allosteric ones. The authors examine the various small-molecule binding sites on KRAS and conclude that, due to “limited druggability,” the “other G12 oncogenic mutants will be very challenging.” Perhaps, but not impossible, as researchers at Mirati demonstrated earlier this year with the (open access) publication of a low (or sub) nanomolar KRAS^G12D inhibitor.

 

Among experimental methods used in FBDD, NMR is a mainstay, as demonstrated by Luca Mureddu and Geerten Vuister (University of Leicester) in Front. Mol. Biosci. (open access). The paper covers methods, successes, and challenges, focusing on three compounds that reached the clinic: AZD3839, venetoclax, and S64315.

 

In contrast to NMR, dynamic combinatorial chemistry (DCC) and DNA-encoded libraries (DEL) are used less frequently in FBLD. In RSC Chem. Biol., Xiaoyu Li and collaborators at University of Hong Kong and Jining Medical University discuss “recent advances in DNA-encoded dynamic libraries.” This concise paper covers lots of ground and does not understate the challenges.

 

Libraries

“The importance of high-quality molecule libraries” is emphasized by Justin Bower and colleagues at the Beatson Institute in Mol. Oncol. This highly readable and wide-ranging open access review covers all aspects of library design and use and includes comparisons of some of the major commercial vendors. An important point is that the “hit rate does not define the success of a library as it is more important to identify ligand-efficient and chemically tractable start points.”

 

Thus, even though shapely fragments may have lower hit rates than more planar aromatic fragments, they may still be worth including – if you can make them. In Drug Discov. Today (open access), Peter O’Brien and collaborators at University of York and Vrije Universiteit Amsterdam review synthetic strategies behind 25 “3D” fragment libraries. The tabular summary showing all the scaffolds emphasizes that most of these libraries are modest in size, with the largest being 102 members. Chemists will particularly enjoy the multiple synthetic schemes. The authors note the importance of “fragment sociability” to facilitate SAR and elaboration.

 

Covalent fragments

Special libraries are required for covalent fragment-based drug discovery, the most notable feature being the “warhead” that reacts with the protein target. These are the focus of a chapter in Adv. Chem. Prot. by Péter Ábrányi-Balogh and György Keserű of the Hungarian Research Centre for Natural Sciences. The review includes a table containing more than 100 warheads with associated mechanisms and amino acid selectivity.

 

The “reactivity of covalent fragments and their role in fragment-based drug design” is the focus in an (open access) Pharmaceuticals review by Kirsten McAulay and colleagues at the Beatson Institute. This is a nice overview of the field and contains several case studies. The authors conclude that “striking a balance between reactivity, potency and selectivity is key to identifying potential candidates.”

 

“Advances in covalent drug discovery” are reviewed (open access) by Dan Nomura and colleagues at University of California Berkeley in Nat. Rev. Drug Disc. This is a highly readable and comprehensive overview of the field. The authors differentiate between “ligand-first” approaches, in which a covalent warhead is appended to a known binder (such as here) and “electrophile-first,” in which “the initial discovery process is rooted in finding a covalent ligand from the outset,” such as for KRAS^G12C inhibitors.

 

Another broad overview of covalent inhibitors is provided by Juswinder Singh (Ankaa Therapeutics) in J. Med. Chem. Jus is a pioneer in the field, having published the first targeted covalent inhibitor in 1997. Of 1673 small molecules approved as drugs by the US FDA, only about 7% are covalent, and it wasn’t until recently that these have been intensively pursued. Part of the reluctance has been concerns over toxicity, but the paper suggests that – at least among kinase inhibitors – covalent drugs may actually be safer, perhaps due to conjugation of glutathione to the warhead and rapid clearance rather than formation of reactive metabolites.

 

Other

Whether covalent or not, thermodynamics plays a fundamental role in protein-ligand interactions, and this is the topic of an (open access) review in Life by Conceição Minetti and David Remeta of the State University of New Jersey. The paper covers a lot of ground, including drug discovery approaches, metrics (such as LE, LLE, etc.), isothermal titration calorimetry, case studies, and more. Importantly, the authors acknowledge the many challenges of applying thermodynamics to drug discovery, some of which we highlighted here.

 

Thermodynamics explains the potency increases longed for when doing fragment-linking, the subject of two reviews. In Chem. Biol. Drug Des. Anthony Coyne and colleagues at University of Cambridge provide a broad overview, starting with the historical theoretical background and newer developments. The bulk of the paper surveys published examples of fragment linking, with structure-based methods (whether X-ray, NMR, or computational) separated from target-guided methods such as DCC.

 

The second review, published in Bioorg. Chem. by Junmei Peng and colleagues at University of South China, is broader in scope, encompassing not just FBLD but also linkers used in PROTACs and even antibody-drug conjugates. The paper is organized by chemical structure of the linker.

 

Finally, in J. Med. Chem., Peter Dragovich, Wolfgang Happ, and colleagues at Genentech and Roche examine “small-molecule lead-finding trends” at their organizations between 2009 and 2020. (Although Genentech is fully owned by Roche, its research organization operates independently.) Fragment-based approaches led to only a small fraction of chemical series at Genentech and none at Roche. The authors note that leads derived from public sources such as patent applications were often found and pursued earlier, and that “purposeful dedication” of resources to fragment approaches may be necessary. Another major source of leads at Genentech is in-licensing, and some of these are fragment-derived.

 

And that’s it for 2022, year three of COVID-19. Thanks for reading and special thanks for commenting. May the coming year bring health, peace, and significant scientific progress.

Fragments vs a Pseudomonas aeruginosa virulence factor

The world is understandably focused on SARS-CoV-2; see for example last week’s post. But there are many other threats out there, including infectious Pseudomonas aeruginosa, which is particularly problematic for immunocompromised people. A recent (open access!) ChemMedChem paper by Martin Empting and collaborators at the Helmholtz Centre for Infection Research and elsewhere describes a clever approach to tackle this pathogen.

An age-old problem for antibiotics is that they provoke resistance: nothing like death to kick evolution into high gear. One way to sidestep this is to develop drugs that target virulence rather than essential microbial pathways. The protein PqsR is part of the Pseudomonas Quinolone Signal Quorum Sensing system, and is important for pathogenicity.

A previously published screen of 720 fragments by SPR yielded about 40 hits, including compound 3. Not only does this compound have impressive ligand efficiency, it also has high enthalpic efficiency; the binding is largely enthalpy-driven. Although the utility of thermodynamics for lead optimization is questionable, the researchers were cognizant of the hydrophobic nature of the ligand binding site for PqsR, and sought molecules that would make polar interactions from the start rather than having to engineer them; a similar strategy proved successful for Astex.

Crystallography with compound 3 was unsuccessful, but SAR by catalog led to compound 7, which has higher affinity for PqsR as assessed by isothermal titration calorimetry (ITC) and also shows activity in a reporter gene assay. Fragment growing led to compound 11, which the researchers were able to characterize crystallographically. The two aromatic rings are at a sharp angle to one another, and attempts at rigidifying the linker proved unsuccessful. But further growing led to compound 20, with submicromolar activity in the reporter assay. This molecule also reduced release of a toxic virulence factor from a clinical isolate of P. aeruginosa.

Interestingly, despite the increased activity of compound 20 over compound 11 in the reporter assay, it seems to have lower affinity for PqsR by ITC. The researchers suggest that the full protein in cells likely behaves differently than the truncated version studied in the biophysical assays.

The researchers also emphasize that flexible linkers were more successful than rigid linkers in improving potency – a phenomenon we’ve previously highlighted here and here. Intuitively a more flexible linker is likely to be more forgiving, as a fraction of an ångström can make the difference between binding or not.

There is still much to do: in particular, activity will need to be improved further, and no pharmacokinetic or other animal data are provided. Moreover, a clinical trial with an anti-virulence strategy would be difficult to design. Still, this is an interesting approach, and I hope the authors or others will follow up on it.

Review of 2019 reviews

The year ends, and with it the awkward teenage phase of the twenty-first century. As we have done since 2012, we're using this last post of the year to highlight conferences and reviews over the previous twelve months.

There were some good events, including CHI’s Fourteenth Annual Fragment-based Drug Discovery meeting in San Diego in April, their Discovery on Target meeting in Boston in September, and the third Fragment-based Drug Design Down Under 2019 in Melbourne in November, which also saw the launch of the Centre for Fragment-Based Design. Our updated schedule of 2020 events will publish next week.

Turning to FBLD reviews, Martin Empting (Helmholtz-Institute for Pharmaceutical Research Saarland) and collaborators published a general overview in Molecules. This is a nice up-to-date summary, covering library design, methods to find, confirm, and rank fragments, and optimization approaches. It’s also open access so you can read it anywhere.

Targets

Protein-protein interactions can be particularly challenging drug targets, and these are covered in a Eur. J. Med. Chem. review by Dimitrios Tzalis (Taros Chemicals), Christian Ottmann (Technische Universiteit Eindhoven) and colleagues. The focus is on clinical compounds, and several of these – including venetoclax, ASTX660, mivebresib, onalespib – are discussed in detail. The article is particularly useful in discussing late-stage optimization of pharmacokinetic and pharmacodynamic properties. It also provides a nice summary of physicochemical properties for fragment hits and derived candidates.

Target selectivity is always important, and this is the focus of a review in Exp. Opin. Drug Disc. by Rainer Riedl and collaborators at the Zurich University of Applied Sciences and the Università degli Studi dell’Insubria. Although the broader topic is de novo drug design, fragment-based methods are prominent, and include case studies we’ve discussed on nNOS, pantothenate synthetase, and MMP-13.

In terms of specific targets, Fubao Huang, Kai Wang, and Jianhua Shen at the Shanghai Institute of Materia Medica provide an extensive review of lipoprotein-associated phospholipase A2 (Lp-PLA₂) in Med. Res. Rev. This serine hydrolase has been studied for four decades but – as the researchers note – “divergence seems to be ubiquitous among Lp-PLA₂ studies.” At least this is not for lack of good chemical tools, fragment-derived (see here, here, and here) and otherwise.

Methods

Although NMR has fallen behind crystallography in our latest poll, that is certainly not reflected in terms of reviews. In particular, ¹⁹F NMR is covered in three papers. CongBao Kang (A*STAR) manages to pack a lot (including 261 references!) into a concise review in Curr. Med. Chem. Topics include protein-observed ¹⁹F NMR, in which one or more fluorine atoms are introduced into a protein genetically, enzymatically, or chemically, as well as ligand-observed methods, in which fluorine-containing small molecules are directly observed or used as probes that are displaced by non-fluorine-containing molecules.

Protein-observed ¹⁹F NMR (PrOF NMR) is covered in Acc. Chem. Res. by William Pomerantz and colleagues at the University of Minnesota. Although the first example was published 45 years ago, only in the past few years has the technique been used for studying protein-ligand interactions. The researchers note that introducing fluorines into aromatic residues is ideal because they are relatively rare, simplifying interpretation, and overrepresented at protein-protein interactions, maximizing utility. Several case studies are described, and even proteins as large as 180 kDa are amenable to the technique.

Ligand-based fluorine NMR screening is simpler and more common than techniques that focus on proteins, and this topic is thoroughly reviewed by Claudio Dalvit (Lavis) and Anna Vulpetti (Novartis) in J. Med. Chem. After a section on theory, the researchers discuss library design, including a long section on quality control (which involves assessing solubility, purity, and aggregation of the molecule in a SPAM filter). Direct and competition-based screening approaches are covered in detail; for the latter, a new method for determining binding constants is provided. The paper concludes with more than a dozen case studies. Clearly much has changed in the ten years since I wondered “why fluorine-labeled fragments are not used more widely.” This perspective is a definitive guide to the topic.

Moving to less common methods for characterizing fragments, György Ferenczy and György Keserű (Research Center for Natural Sciences, Budapest) cover thermodynamic profiling in Expert Opin. Drug Disc. After discussing several case studies, they conclude that “thermodynamic quantities are not suitable endpoints for medicinal chemistry optimizations” due to the complexity of contributing factors. This is consistent with another recent paper on the subject (see here), though the information provided is still interesting for understanding molecular interactions.

And although you might have thought the 2017 VAPID publication was the last word on the limitations of ligand efficiency (LE), Pete Kenny has published a splenetic jeremiad on the topic in J. Cheminform. (see also his blog post on the topic, which includes a sea serpent). This is largely a retread of a 2014 article on the same topic (reviewed by Teddy in his inimitable manner here). Pete also describes a more complicated alternative to LE involving residuals, though unfortunately he provides no evidence that it provides more useful information. Pete is of course correct to remind us that metrics have limitations, but assertions that LE “should not even be considered to be a metric” are overwrought.

Chemistry

Two articles discuss virtual chemical libraries. In J. Med. Chem., W. Patrick Walters (Relay Therapeutics) describes efforts to measure, enumerate, and explore chemical space. He notes that false positives could quickly overwhelm a virtual screen of a hundred million molecules, but as we saw earlier this year, progress is being made. Indeed, Torsten Hoffmann (Taros Chemicals) and Marcus Gastreich (BioSolveIT) focus on navigating the vastness of chemical space in Drug Disc. Today. They note that the Enamine REAL Space is up to 3.8 billion commercially accessible compounds, more than double the number of stars in the Milky Way. But this pales in comparison to the 10²⁰ potential compounds in Merck’s MASSIV space. Just storing the chemical structures of these in compressed format would require 200,000 terabytes – and searching them exhaustively is beyond current technology.

Ratmir Derda and Simon Ng (University of Alberta) discuss “genetically encoded fragment-based discovery” in Curr. Opin. Chem. Biol. This involves starting with a known fragment that is then coupled to a library of peptides and screened to find tighter binders. The researchers provide a number of case studies, though adding even a small peptide to a fragment will generally have deleterious effects on ligand efficiency. And – Rybelsus not withstanding – oral delivery of peptides is challenging.

Finally, Vasanthanathan Poongavanam, Xinyong Liu, and Peng Zhang, and collaborators at Shandong University, University of Bonn, University of Southern Denmark, and K.U. Leuven review “recent strategic advances in medicinal chemistry” in J. Med. Chem. Among a wide range of topics from drug repurposing to antibody-recruiting molecules is a nice, up-to-date section on target-guided synthesis. As I opined a couple years ago, I still doubt whether this will ever be generally practical, but from an intellectual standpoint I’m happy to see work continue on the approach.

And with that, Practical Fragments says goodbye to the teens and wishes you all a happy new year. Thanks for reading and commenting. May 2020 bring wisdom, and progress.

Is thermodynamic data useful for drug discovery?

Just over a decade ago Ernesto Freire suggested that small molecules whose binding energy is dominated by the enthalpic – rather than the entropic – term make superior drugs. He also suggested that such molecules may be more selective for their target. But the backlash came quickly, and a couple years ago we wrote that focusing on thermodynamics probably isn’t particularly practical. A new perspective in Drug Disc. Today by Gerhard Klebe (Philipps-University Marburg) revisits this topic.

Klebe suggests that enthalpy was initially embraced “because readily accessible and easily recordable parameters are much sought after for the support of the nontrivial decision over which molecules to take to the next level of development.” (I would be interested to know whether sales of isothermal titration calorimetry (ITC) instruments spiked around 2010.) Unfortunately, both theoretical and practical reasons make thermodynamic measurements less useful than hoped.

First, and as we noted previously, “in an ITC experiment… the balance sheet of the entire process is measured.” In particular, water molecules – which make up the bulk of the solution – can affect both enthalpic and entropic terms. Klebe describes an example in which the most flexible of a series of ligands binds with the most favorable entropy to the target protein; this is counterintuitive because the ligand adopts a more ordered state once bound to the protein. It turned out that in solution the ligand traps a water molecule that is released when the ligand binds to the protein, thus accounting for the favorable entropy.

Indeed, water turns out to be a major confounding factor. We’ve previously written about “high-energy” water; Klebe notes that an individual water molecule can easily contribute more than 2 kcal/mol to the overall thermodynamic signature. And of course, proteins in solution are literally bathed in water. The structure of this water network, which may change upon ligand binding, is rarely known experimentally, but optimizing for it can improve affinity of a ligand by as much as 50-fold. Conversely, attaching a polar substituent to a solvent-exposed portion of a molecule to improve solubility sometimes causes a loss in affinity, and Klebe suggests this can be due to disruption of the water sheath.

Beyond these theoretical considerations, experimental problems abound. We’ve previously discussed how spurious results can be obtained when testing mixtures of ligands in an ITC experiment, but even with single protein-ligand complexes things can get complicated. Klebe shows examples where the relative enthalpic and entropic components to free energy change dramatically simply because of changes in buffer or temperature. This means that the growing body of published thermodynamic data needs to be treated cautiously.

So what is to be done? First, thermodynamic data should always be treated relatively: “we should avoid classifying ligands as enthalpy- or entropy-driven binders; in fact, we can only differentiate them as enthalpically or entropically more favored binders relative to one another.”

Klebe argues that collecting data on a variety of ligands for a given target under carefully controlled conditions will be useful for developing computational binding models. This is important, but not the kind of work for which people usually win grants, let alone venture funding.

He also suggests that, by collecting thermodynamic data across a series of ligands, unexpected changes in thermodynamic profiles might reveal “changes in binding modes, protonation states, or water-mediated interactions.” Maybe. But it takes serious effort to collect high-quality ITC data. Are there examples where you’ve found it to be worthwhile?

Fragment growing and merging: an inverse agonist of RORγt2

The nuclear receptor transcription factor RORγt2 is involved in the differentiation of Th17 cells, and is thus a target for inflammatory diseases. The protein contains a large, hydrophobic ligand binding site, and as a result most known inverse agonists have less than ideal physicochemical properties. In a paper recently published in J. Med. Chem., Samuel Hintermann and colleagues at Novartis have taken a fragment-based approach.

The researchers screened a library of 1408 fragments using a “differential static light scattering (DSLS)” assay, which is a type of thermal shift assay that measures denaturation and aggregation of the protein. A few dozen molecules that stabilized RORγt2 were tested in dose-response curves prior to crystallization trials, ultimately yielding 13 structures. Compound 1 was particularly interesting because it binds in the center of the cavity, providing growth vectors in two directions. It also makes a couple hydrogen bonds with the protein, as opposed to purely hydrophobic interactions.

Growing from the ethoxy position quickly led to improvements in affinity. To avoid the possibility of toxic iminoquinone metabolites, the researchers replaced the central phenyl ring with a pyridine, resulting in the low micromolar inverse agonist compound 8.

To further improve affinity, the researchers merged an element from a previously reported GlaxoSmithKline molecule (compound 2) onto compound 8, resulting in the potent compound 9, which was characterized in a battery of assays.

The crystal structure of compound 9 bound to the protein revealed that the core fragment moiety binds in the same manner as the original compound 1, though the added benzyl ether binds in a subpocket that had not previously been observed to bind ligands.

Kinetic studies using a reporter displacement assay revealed that compound 9 has both a slow on-rate as well as a slow off-rate, consistent with the fact that it is fully enclosed by the protein. The researchers performed molecular dynamics simulations to try to determine how the ligand could enter or leave, which suggested large conformational changes in a flexible region of the protein. Isothermal titration calorimetry (ITC) showed that the binding of compound 9 is enthalpically driven, with an unfavorable entropy. Although interpreting thermodynamics is fraught, this result makes intuitive sense given the hydrogen bonds formed and the fact that the molecule seems to rigidify the protein.

Biophysics is interesting, but of course biology is what was driving the program. Compound 9 is potent in a variety of cell assays and is also selective for RORγt2 over other nuclear hormone receptors. However, it is also mostly insoluble, and although it did show efficacy in a rodent inflammation model, plasma concentrations of compound 9 were highly variable between individual rats, which the authors attribute to poor physicochemical properties.

This is a nice application of fragment growing and merging that demonstrates how difficult it is to find useful leads for lipophilic sites: even with favorable biochemistry and biophysics, the pharmacokinetics are a slog. That said, others have made progress against similarly hydrophobic targets, so it will be fun to watch this story progress.

Enthalpy revisited – and retired

The relative importance of enthalpy versus entropy for protein-ligand interactions has been a subject of considerable attention. In a 2009 post we suggested that it might be worthwhile to focus on fragments that bind predominantly enthalpically, and in 2011 we highlighted a paper suggesting that enthalpic binders may be more selective than entropic binders. But the universe has a way of confounding pet models – as we acknowledged in 2012 (twice). The best way forward is often with lots of data, which is exactly what we have in a new paper in Drug Disc. Today by György Keserű and collaborators at the Hungarian Academy of Sciences, Astex, and AstraZeneca.

The data in this case are sets of 284 protein-ligand interactions with thermodynamic binding data from the literature, 782 from Astex, and about 230 from AstraZeneca. Commendably, these data are provided in 103 pages of supporting information.

In order to analyze the data, the researchers developed a new metric, the Enthalpy-Entropy Index:

I_E-E = (ΔH+TΔS)/ΔG

If I_E-E = 0, it means that enthalpy and entropy both contribute equally to the free energy of binding; if I_E-E > 0 it means that enthalpy dominates, and if I_E-E > 1 it means that enthalpy needs to overcome an unfavorable entropy. Similarly, negative values mean that entropy dominates – completely so when I_E-E < -1. (Note that, unlike enthalpy efficiency, this is a dimensionless ratio, which should please our friends over at Molecular Design.)

As it turns out, the vast majority of fragments bind to their targets with favorable enthalpy, and almost all of those that don’t are charged compounds in which desolvation of the charged bit could entail an enthalpic cost. The researchers also examined a set of 94 neutral fragment-sized and 44 larger molecules binding to 17 targets and found that, statistically speaking, enthalpy plays a more important role in the free energy of binding for fragments than for larger molecules. But things can change quickly: in one case, adding just two non-hydrogen atoms to a molecule improves the affinity by more than 4000-fold and changes the I_E-E from -1.5 to +0.5.

The paper does an excellent job describing the challenges of collecting high-quality isothermal titration calorimetry (ITC) data. In a typical experiment, the heat measured with each injection is the same as “would fall on an A4 sheet of paper in 1 second when illuminated by a 40 Watt bulb placed nearly 5 kilometers away.” Errors can be caused by inaccurate concentrations, heat of dilution, and changes in buffer concentration or protonation state. An analysis of replicate measurements at Astex found that, while most of the replications were within 1 kcal/mol of each other, some were off by nearly 3 kcal/mol. However, these larger values were all associated with different forms of the protein, and so may not be considered true replicates, though they do indicate how changes in the protein far from the active site can have an effect on what is often considered (erroneously) a local interaction.

This also emphasizes the fact that, as the researchers note, “the measured binding enthalpy is a net value and the dissection of the individual contributions might be ambiguous.” Or, as Pete has previously stated, “the contribution of an individual protein-ligand contact is not strictly an experimental observable”.

From a molecular recognition standpoint I find all this quite interesting and even intuitive in a hand-wavy sort of way. As the researchers suggest, fragments, being small, have minimal surface area with which to make (often but not always entropically-driven) hydrophobic interactions. Instead, much of the binding energy comes from hydrogen-bond interactions, which are (again often but not always) predominantly enthalpic. Moreover, since the entropic cost of locking down any ligand onto a protein is on the order of 3-5 kcal/mol, fragments are already fighting against entropy, and this is exacerbated by low affinity.

But from a practical perspective, my earlier suggestion to focus on enthalpic fragments may have been simplistic: if you’ve found a fragment, its enthalpy of binding is almost certainly favorable, and even if it’s not, this could change with the slightest tweak. So unless we see something truly new, don’t expect many new posts on this topic.

Eleventh Annual Fragment-based Drug Discovery Meeting

The first major fragment event of 2016, CHI’s Drug Discovery Chemistry, was held last week in San Diego. FBDD was the main focus of one track, and fragments played starring roles in several of the others as well, including inflammation, protein-protein interactions, and epigenetics. Also, for the first time this year the event included a one-day symposium on biophysical approaches, which also included plenty of fragments.

In agreement with our polls, surface plasmon resonance (SPR) received at least a mention in most of the talks. John Quinn (Genentech) gave an excellent overview of the technique, packed with lots of practical advice. At Genentech fragments are screened at 0.5 mM in 1% DMSO at 10°C using gradient injection, which permits calculation of affinities and ligand efficiencies directly from the primary screen. Confirmation of SPR hits in NMR is an impressive 80%. A key source of potential error in calculating affinities is rebinding, in which a fragment dissociates from one receptor and rebinds to another. That problem can be reduced by increasing the flow rate and minimizing the amount of protein immobilized to the surface. Doing so also lowers the signal and necessitates greater sensitivity, but happily the baseline noise has decreased by 10-fold in the past decade.

Some talks focused on using SPR for less conventional applications. Paul Belcher (GE) described using the Biacore S200 to measure fragments binding to wild-type GPCRs. In some cases this provided different hits than those detected against thermally stabilized GPCRs. And Phillip Schwartz (Takeda) described using SPR to characterize extremely potent covalent inhibitors for which standard enzymatic assays can produce misleading results. These screens require exotic conditions to regenerate the chip, so it helps that the SensiQ instrument has particularly durable plumbing.

In theory, SPR can be used to measure the thermodynamics of binding by running samples at different temperatures, but John Quinn pointed out that enthalpic interactions dominate for most fragments, so the extra effort may not be worthwhile. Several years ago many researchers felt that enthalpically driven binders might be more selective or generally superior. Today more people are realizing that thermodynamics is not quite so simple, and Ben Davis (Vernalis) may have put the nail in the coffin by showing that, for a set of 22 compounds, enthalpy and entropy of binding could vary wildly simply by changing the buffer from HEPES to PBS! (Free energy of binding remained the same with either buffer.)

Thermal shift assays (TSA or DSF) continued to be controversial, with Ben finding lack of agreement between the magnitude of the shift and affinity, though there was a correlation with success in crystal trials. In contrast, Mary Harner (BMS) reported good agreement between thermal shift and affinity. She also found that it seemed to work better when the fragments bound in deep pockets than when they bound closer to the surface. However, Rumin Zhang (Merck), who has tested more than 200 proteins using TSA, mentioned that some HCV protease inhibitors could be detected despite the shallow active site. Rumin also pointed out that a low response could indicate poor quality protein – if most of the protein is unfolded it might be fine for biochemical assays but not for TSA. Negative thermal shifts are common and, according to Rumin, sometimes lead to structures, though others found this to be the case less often.

What to do when assays don’t agree was the subject of lively discussion. Mary Harner noted that out of 19 targets screened in the past two years at BMS using NMR, SPR, and TSA, 45% of the BMS library hit in at least 1 assay. However, 68% of hits showed up in only a single assay. Retesting these did lead to more agreement, but even many of the hits that didn’t confirm in other assays ultimately led to leads. All techniques are subject to false negatives and false positives, so lack of agreement shouldn’t necessarily be cause for alarm. Indeed, Ben noted that multiple different soaking conditions often need to be attempted to obtain crystal structures of bound fragments.

Crystallography in general is benefiting from dramatic advances in automation. Jose Marquez described the fully automated system at the EMBL Grenoble Outstation, which is open to academic collaborators. And Radek Nowak (Structural Genomics Consortium, Oxford) discussed the automated crystal harvesting at the Diamond Light Source, which is capable of handling 200 crystals per hour. He also revealed a program called PANDAA (to be released soon) that speeds up the analysis of crystallographic data.

Crystallography was used as a primary screen against KEAP1, as discussed by Tom Davies (Astex). A subset of 330 of the most soluble fragments was tested in pools of four, which revealed several hot spots on the protein. Interestingly, an in-house computational screen had not identified all of these hot spots, though Adrian Whitty (Boston University) noted that they could be detected with FTMap. The fragments themselves bound exceptionally weakly, but intensive optimization led to a low nanomolar inhibitor.

Another case in which extremely weak fragments turned out to be useful was described by Matthias Frech (EMD Serono). A full HTS failed to find any confirmed hits against cyclophilin D, but screening by SPR produced 168 fragments, of which six were characterized crystallographically. Although these were all mM, with unimpressive ligand efficiencies, they could be linked or merged with known ligands to produce multiple leads – a process which took roughly one year from the beginning of the screen. Matthias noted that sometimes fragment efforts are started too late to make a difference, and that it is essential to not be dogmatic.

Huifen Chen discussed Genentech's MAP4K4 program. Of 2361 fragments screened by SPR, 225 had affinities better than 2 mM. Crystallography was tough, so docking was used instead, with 17 fragments pursued intensively for six months, ultimately leading to two lead series (see here and here), though one required bold changes to the core. This program is a nice reminder of why having multiple fragment hits can be useful, as the other 15 fragments didn’t pan out.

Finally, George Doherty (AbbVie) gave a good overview of the program behind recently approved venetoclax, which involved hundreds of scientists over two decades. He also described intensive medicinal chemistry which led to a second generation compound, ABT-731, with improved solubility and oral bioavailability.

We missed Teddy at this meeting, and there is plenty more to discuss, so please add your comments. If you did not attend, several excellent events are still coming up this year. And mark your calendar for 2017, when CHI returns to San Diego April 24-26.

More Notes from DDC 2015

Dan and I both gave our thoughts on the conference last week.  But there was more than just the talks.  There were roundtables.  I chaired one on using kinetics and thermodynamics to drive medchem for the PPI track.  It was a lively discussion.  It was agreed that dyed in the wool enzymologists are priceless.  Kinetics is useless if clearance is the driving force, so this becomes a PK/PD issue.  But does it always have to be?  Paul Belcher from GE shared the On/off rate map (Figure 1) that shows what realm of binding you are in depending on your reates.  Paul also mentioned that Tony Gianetti, formerly of Genentech, used HSA and SPR to assess a more realistic picture of how compounds interact in plasma.  In terms of earlier phase uses, one of the round table attendees mentioned that she had seen talks of people using kinetic data to drive medchem.  She couldn't recollect who, so if any of our astute readers have references please share.  We also discussed using kinetic data to rank compounds with similar IC50.  A question was raised whether or not kinetics can be a good surrogate for receptor occupancy? 

Figure 1.  On/off Rate Map: A = affinity limited efficacy, B= on rate limited efficacy, C= rapid off rate limited, D= slow off protected efficacy

So, what about thermodynamics?  By and large, this was viewed as retrospective only.  Paul from GE did share that they have an app note of using SPR to generate thermodynamic data (I can't figure out how to link it, so if you want it contact me (or Paul) and we can send it). 

The main thrust was that neither kinetics nor thermodynamics are used to make prospective medchem decisions, rather they are used to justify in retrospection. Specifically for PPIs, the consensus was that the focus should be on on rate because you have to the compound in there when you can (i.e. when the complex is "open" enough). 

Derek Cole of Takeda led one of the FBDD round tables: Practical Aspects of Fragment Screening. Here is a picture, courtesy of Bjorn Walse of Saromics.  

His notes are replicated below:

Round table became figure 8 with two tables, with 2-3 deep seats and 40 -50 participants. FBDD expertise from novice to experts, including Teddy Zartler, Dan Erlanson, Gregg Siegal, and Andrew Petros. Large attendance highlights the number of newcomers to FBDD, confirmed by Dan Erlanson during opening when 2/3 of attendees indicated this was their first CHI FBDD meeting. Very lively debate/discussion covering 4 primary targets.

1. Designing and building and storing libraries. Discussed size of library i.e. 1000 or 40K. Agreed that a good library of 1000 should yield lots of high quality hits. Best to keep HA low, 10 - 16 (majority in 12 - 14 range). Discussed 3D vs. flat fragments. Flat give higher hit rate and should be major part of library. 3D likely give lower hit rate but may yield very exciting hits. Discussed complexity and the need for fragments to have enough complexity, but not two pharmacophores. (ref. Astex work). IF just starting out, best to buy a vendor library, e.g. Maybridge or others, which are fully characterized.

2. Screening techniques. NMR and SPR most common. Both very good. Tm - fast, inexpensive and can correlate with x-ray. What to do if no biochemical activity. Might be fine if below sensitivity of biochemical assay, i.e. very small fragment, however if larger fragment, need to understand why not being detected.

3. Potential pitfalls. Make sure library is soluble above assay conditions, i.e. > 1 mM in aqueous buffer (1 - 2% DMSO). Check for aggregation. Run SPR clean screen.

4. Fragment hit follow up. Think of fragments as seeds to identify protein compatible pharmacophore. SAR by catalog of similar fragments or fragments which present a similar pharmacophore is of great value. May find fragments which are much more potent, efficient, or which crystallize (if original was unsuccessful). Good to design diverse library, but similarity in fragments is different than similarity in large molecules, small 1-atom changes can have profound effect on binding mode, potency, etc.

If I missed any other highlights, please add them in the comments, or email me and I can add it in.  

Fast, competitive thermodynamic data

The importance of thermodynamics in drug discovery is often debated, with advocates arguing that ligands binding primarily through enthalpic interactions may be superior to those whose binding is driven by entropy. Some publications support these claims, though the data are rather sparse. This is at least partly because thermodynamic measurements are typically done using isothermal titration calorimetry (ITC), which consumes sizable amounts of protein and is not exactly high throughput. In a recent issue of J. Med. Chem., Jose Caaveiro, Kouhei Tsumoto, and their colleagues at the University of Tokyo and GE Healthcare Japan describe a new screening method that could speed things up.

The approach, which is essentially a competition screen, is called single-injection thermal extinction, or SITE. In a conventional calorimetric assay, a ligand is added to the protein in a calorimeter, and the measured heat change upon binding is used to calculate enthalpy. In SITE, a protein is first incubated with the fragment to be tested in the calorimeter, and a known positive control binder is then added. If the fragment binds at the same site as the known binder, addition of the positive control will cause a smaller change in temperature, and this difference should reflect the enthalpy of binding of the fragment compared to the positive control.

To validate the system, the researchers tested the steroid-processing enzyme ketosteroid isomerase (KSI). They first ran an SPR screen of 2000 fragments at 0.2 mM. To weed out false positives, they used two different types of SPR chips, and looked closely at the binding curves; the paper has a nice summary of some of the pathologies that can occur. A total of 129 hits were identified, of which 44 were then tested in SITE and characterized more fully with SPR.

Interestingly, most of the most potent compounds – as assessed by SPR – also gave the strongest signals in SITE, suggesting that these compounds are binding largely through enthalpic interactions. A few of the best compounds were further characterized by conventional ITC, and these did in fact have better enthalpic efficiencies than the positive control (they had better ligand efficiencies too).

It would be interesting to know how SITE behaves with allosteric inhibitors or ligands that bind to different sites on the protein. And of course, the jury is still out on whether enthalpic binders really do make superior leads, and even whether it is possible to use thermodynamics prospectively in lead optimization. But with a 9-fold drop in protein consumption and an increase in speed, this technique may make it easier to get the data to answer these questions.

Entropy-enthalpy transduction: time to throw up our hands?

Thermodynamics has come up several times on Practical Fragments. The binding of a ligand to a protein can be dissected into enthalpic and entropic components. Very simplistically, enthalpy underpins directed, often polar interactions, while entropy plays the dominant role in non-directed, hydrophobic interactions. Ligands that bind primarily through enthalpic interactions (such as hydrogen bonds) have been suggested to be more selective and “best in class”. Historically, a key theoretical advantage of FBLD is the notion that linking two fragments can provide an entropic advantage to the combined molecule compared with the isolated fragments. However, as discussed recently, reality sometimes cocks a snook at theory.

One stumbling block in trying to apply thermodynamics rationally is enthalpy-entropy compensation, a perverse trick of the universe in which, when you improve the enthalpy of an interaction, you may worsen entropy, and vice versa. For example, if you introduce a hydrogen bond into a protein-ligand interaction, the precise positioning required may cause increased rigidity, at an entropic cost.

Now a new paper in Proc. Nat. Acad. Sci. USA from Michael Gilson and colleagues at UCSD suggests that things may be even more complicated. They analyze a previously published 1 millisecond molecular dynamics simulation of the small (58 residue) protein BPTI. There are three main conformational states (or clusters), each with similar overall energies. However, the researchers find that the different conformational states have very different global enthalpies and entropies. Worse, very tiny perturbations, such as the distance between two side chain atoms, can cause one state to shift to another, in turn dramatically changing the overall thermodynamic signature.

In practice, this means that when you measure the thermodynamics of a ligand binding to a protein, the enthalpic and entropic changes observed could have more to do with subtle changes in the global conformation of the protein, or even changes in solvent binding, than to the ligand-protein interaction itself.

The researchers call this phenomenon entropy-enthalpy transduction (EET):

The thermodynamic character of a local perturbation, such as enthalpic binding of a small molecule, is camouflaged by the thermodynamics of a global conformational change induced by the perturbation, such as a switch into a high-entropy conformational state.

The researchers argue that EET could occur in many protein systems, so experimentally determined values of entropy and enthalpy for ligand binding are actually unreliable indicators of the local thermodynamic driving forces we normally try to influence.

Although the researchers develop a sophisticated mathematical framework to describe EET, at the end of the article I’m left wondering, is there any hope of using thermodynamics for practical drug discovery?

ACS Fall Meeting 2012

I recently returned from Philadelphia, where the American Chemical Society held its 244^th national fall meeting. As always this was a massive affair, but fragments were well-represented, particularly in a nice session organized by Percy Carter, Debbie Loughney, and Romyr Dominique.

I opened the session by giving an introduction to fragment-screening, as well as an overview of some of the work we’re doing at Carmot. Andrew Good had perhaps the best title (“Fragment fat wobbles too”), and discussed some of the work done at Genzyme on Pim-1 kinase. Eric Manas next described some of the computational tools being used at GlaxoSmithKline, in particular strategies to deal with water. He also discussed the utility of looking for fragment analogs early in a project. In the last talk before the intermission, Chris Abell from the University of Cambridge described a number of projects from his group, starting with antimicrobial targets (such as this one); we’ll cover another in a separate post. Chris is unabashedly going after difficult targets, not just protein-protein interactions, but oligonucleotides – specifically riboswitches. There is only limited precedent for targeting RNA with fragments, so it will be fun to see how this progresses.

Francisco Talamas next described a nice example from Roche using FBLD to discover hepatitis C NS5B Palm I allosteric inhibitors. An HTS campaign of around 900,000 molecules yielded just 3 hits, none of which were advanced. A fragment screen of about 2700 fragments gave a better hit rate (5.9%), but of the 29 co-crystal structures attempted only a single structure was obtained. However, by combining the information from this crystal structure with information from other crystal structures, both proprietary and public, the researchers put together a set of rules to design a de novo fragment library tailored to this protein. This effort ultimately yielded compounds that were optimized to a clinical candidate.

Next, Nick Wurtz from Bristol-Myers Squibb described his company’s approach to discover neutral Factor VIIa inhibitors. The researchers used a combination of computational, functional, and biophysical approaches to find uncharged fragments that would bind in the P1 pocket, leading to a couple dozen crystal structures. Despite the low affinities of these fragments (typically mM), many of them could successfully be merged onto an existing series, replacing a positively charged moiety to yield potent molecules with better permeability. This is the first time I’ve seen a fragment story out of BMS, so I'm glad to see that they’re active in this area. This is also a prime example of what has been described as fragment-assisted drug discovery.

Finally, Prabha Ibrahim of Plexxikon gave a lovely overview of the discovery and development of vemurafenib, including a more detailed description of the SAR than has been presented in their earlier papers.

In addition to this dedicated session, there was a scattering of other talks and posters, including a notable poster from Timothy Rooney at the University of Oxford using fragment-based approaches to discover bromodomain inhibitors, a target class we’ve previously discussed.

A session entitled “A medicinal chemist’s toolbox” ranged over several topics of interest. Ernesto Freire of Johns Hopkins gave a great overview of thermodynamics in drug discovery, a topic we’ve previously covered. Most readers are probably familiar with the concept of enthalpy-entropy compensation, in which (for example) an added hydrogen bond fails to achieve the desired boost in potency due to unfavorable entropy. Recognizing this, he suggested that one should target groups in proteins that are already well-structured, so you don’t have to pay the cost of structuring a disordered part of the protein. He also suggested that if you introduce one hydrogen bond, you might be better off introducing a second one too, as the incremental entropic cost is likely to be low.

György Keserű of Gedeon Richter discussed the importance of avoiding lipophilicity by using tools such as LELP, which we’ve covered here and here. Continuing this theme, Kevin Freeman-Cook of Pfizer described two examples of using LLE in lead discovery programs, in particular calculating LLE values before making compounds. Although this may seem obvious, what was quite striking was the dramatic effect subtle changes in structure could make to ClogP values.

Of course, these are just a few of thousands of presentations. Please feel free to point out any that caught your eye, or expand on some of those mentioned above. And just a reminder, it’s only 4 weeks to FBLD 2012 in San Francisco – the biggest fragment event of the year!

Slow-off, albeit tight, fragments

Practical Fragments recently discussed binding kinetics, and that got me wondering whether any fragments have slow off-rates. Turns out some do: a January 2012 review of protein-ligand energetics and kinetics in Drug Discovery Today by Sara Núñez and colleagues at Abbott summarized a paper published last October in Eur. J. Med. Chem. by Jos Lange et al. In it, Lange and colleagues extensively characterize six inhibitors of the enzyme D-amino acid oxidase (DAAO), a potential target for schizophrenia.

The researchers use biochemical assays, surface plasmon resonance (SPR), and isothermal titration calorimetry (ITC) to characterize the thermodynamics and kinetics of their inhibitors binding to DAAO. Although all six molecules are fragment-sized, these are not your typical fragments: the weakest has a Kd better than 1 micromolar, and all have ligand efficiencies of 0.79 kcal/mol/atom or better! Three of them are shown below, along with their dissociation constants (determined by ITC) and their dissociation rate constants (determined by SPR).

One interesting aspect of the kinetics is that compound 6 dissociates from the enzyme roughly 50-fold more slowly than compound 3, even though it binds only about 3-fold more tightly. As an interesting aside, compound 1 has a slower on-rate than any of the other molecules, a phenomenon the researchers attribute to tautomerization around the pyrazole.

The researchers go on to measure a number of other properties of these molecules, including Log P, pKa, thermodynamic and kinetic solubility, cell membrane permeability, and in vivo pharmacokinetics. There is a tremendous amount of data here, and it’s a lot of fun to dig into.

With a predicted half-life of more than 2 hours, compound 6 certainly classifies as a slow-off fragment. So is it a better drug? Well, it’s not orally bioavailable, in contrast to some of the other compounds, and it has faster clearance in rodents. Unfortunately the researchers do not report in vivo target modulation, but one has to assume that a schizophrenia drug would need to be oral. Chemists can optimize affinity, thermodynamics, kinetics, and drug-like properties all we want, but the body still has the final say.

Fragment linking: flexible rules

Linking two fragments together to achieve a boost in potency has been done a number of times (see here, here, here, and here), though it often doesn’t work as well as might be hoped (see here). To better understand the energetics of fragment-linking, Marc Nazaré, Hans Matter, and colleagues at Sanofi-Aventis Deutschland have analyzed ligands for the blood coagulation enzyme factor Xa (fXa) and published their results in a recent issue of Angew. Chem. Int. Ed.

The researchers “deconstructed” potent fXa inhibitors into component fragments, measured their inhibition constants (and thereby inferred their binding energies), and compared these binding energies with those of the original linked molecules. One of the first observations was that many of the component fragments bound so weakly as to show no measurable activity, a phenomenon that has been observed previously.

In an exemplary case, cleaving a single bond connecting the two component fragments of a 2 nM ligand (1a, below) yielded one fragment (1g) with 58 micromolar activity and another (1d) whose activity was worse than 10 millimolar. Because the second fragment has such low affinity, the binding energy of linking is really just a lower estimate, but it seems to be at least 3.3 kcal/mol, which is greater than the binding energy of fragment 1d itself. In other words, the affinity brought about by linking is greater than the affinity of the weakly binding fragment. The superadditivity provided by the linker in this case is about 300-fold, a similar value to that observed in the unrelated MMP-12 system. This is perhaps all the more remarkable given the fact that the fragments are connected by a linker containing several rotatable bonds, the entropy of which should partially counter the advantages of linking.

In fact, a common strategy to improve the potency of two linked fragments is to rigidify the linker. Often this doesn’t work: in a second case, the Sanofi-Aventis researchers cleaved one bond of a 3 nM ligand (2a, below) to yield two fragments with roughly equal potency. However, even though the linker is more rigid than in the previous example, the binding energy due to linking is less – just 2.0 kcal/mol, representing a boost of about 30-fold.

As the authors note:

The introduction of rigid aromatic moieties as a common approach to increase affinity does not necessarily maximize the benefit from the linker effect as detrimental affinity contributions might originate from suboptimal orientation and accommodation of specific binding elements.

There are many more examples in this paper than can be covered in a blog post; the authors dissect compounds 1a and 2a at a number of different points, and while the component fragments typically bind less tightly than simple additivity would suggest, there are lots of interesting details.

Finally, it is interesting to note that ligands 1a and 2a consist of a relatively hydrophobic fragment (1g or 2g) connected to a more polar fragment (1d or 2h). The fact that these show superadditivity is consistent with Mark Whittaker and colleagues' proposal last year that linking such fragments is likely to maximize additivity, although given the precise interactions made by both parts of the molecules the details get a bit messy. We’re not yet at the point where the universe of molecular interactions can be distilled to rigid rules.