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.

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.

On Par with the Pyramids... a New Book on Drug Discovery!

There are many great testaments to humanity's perseverance.   The Pyramids at Giza, the Cathedral of Notre Dame , the Great Wall of China, and the most recent Applied Biophysics for Drug Discovery .   This blog typically reviews the content of the book, but I thought it would be interesting to describe how the book came together.

It is said that if you see inside a hotdog factory you'd never eat a hotdog again.  So, how did this hotdog get made?  Flash back 3 years, and Don Huddler (at that time at GSK) reaches out to me and says, "Hey do you have a contact at Wiley.  I have a great idea for a book." "Sure Don, here you go."
A week or so later, Don invites me to lunch so we go to greatest restaurant ever!!!  Over lunch , and maybe my second beer, Don says, lets write this together.  After almost choking on my Cajun Meatloaf GC, I said NO WAY!!!  There may have been at least one more beer involved but I agreed after Don said he would do all the heavy lifting.

Flash forward a few weeks, and Wiley accepted our book proposal, with 30 listed chapters, with 5 sections.  Part of the fun part is that they send your proposal out for review, so just like a paper, you get reviewer comments.   You then sign a contract with the Publisher that says you will deliver so many pages: 556 in our case by 31Jan2016 (14 months after the contract was signed).  Don had already defined many of the authors who he had thought would be appropriate.  So, at this point, you send out letters to authors and ask them to contribute.  So, "You would be perfect to write a chapter for our upcoming book on [insert what you want them to write on]."  Then you wait and hope that they actually respond.  Many authors responded right away, and it is not personal when they say no.  It is a pretty significant amount of work to contribute to a chapter.  Then you work with the authors to define the time frame of when drafts are due, and so forth.

You then wait and hope the authors deliver on time.  Some do, may don't.  So then you become Nagger-in-Chief.  "Where's the chapter draft?  Is it coming soon?"  As someone famous said, life is what happens while you are making other plans.  During the summer of 2015, GSK was re-orging, and Don decided to go to Law School full time.  So, here we are trying to get drafts done, edited and returned to authors and one editor makes a major career change.  Two months after that, I followed Don in changing careers, leaving the glamorous consulting life to join Pfizer.  As hard as we tried, our new careers required our focus and the book got short shrift.  

For some authors who had delivered on time, this was frustrating.  We had a given deadline and they delivered.  We dropped the ball for them.  For other authors who were less than timely in their contributions, they did not get nagged sufficiently, causing further delays.  2016 was by and large a horrible year if you were an author with a delivered chapter, and a fantastic year if you hadn't delivered a chapter yet.  And of course, as time drags on, other career changes happen.  One primary author retired, one changed jobs and stopped responding to emails, and so on.  So, our initial 20 chapters (from the 30 we wanted) was whittled down to 15 chapters.  

Its now 2017, and the book is a year late, and Don and I are still trying the best we can to manage new careers and editing the book.  Authors are angry with the delay and I didn't blame them.  We were actually able to finally get all the chapters together and to the publisher.  Phew, most of our work is done.  STOP!  One chapter got completely left out of the final submission.  So, the scramble was on to make sure that it was included.  You can see which one when you try to figure out the order of chapters.   

So, what is the role of the Publisher during this whole thing you ask?  I don't know.  My experience with the publisher on this book was VERY different from the first one.  I got the feeling that this book was a low priority for them.  Our emails took weeks sometimes to be responded to.  It was frustrating; but something we did not want to share this with the authors.  So, after this it is mostly on the publisher, but we had to design the cover.  To explain it, everything on the cover is from a chapter in the book: the structure and equations.  We get to galley proof stage and final publication, and Wiley tells us we need to index the book. This is a change from the first time.  Don and I take the option to have them do it for us and take it out of royalties (which is something on the order of 50$ a year).  So, finally in July of this year, it was finalized and given a publication date.  Project done.  So,  let me say to all the authors, thank you so much for being a part of this book.

So, what did I learn co-editing this book?  No matter how many beers I get fed, I will never EVER edit a book again.  There is actually a word ambit. I have a reputation for being "provocative" (from a reviewer); this probably didn't help.  The quality of the contact at the publisher makes a huge difference.  I hope our contact at Wiley was new and inexperienced because this experience was far worse than the first time I did the book.

So, what is inside the book?  291 pages (out of a promised 556).   There are 14 chapters of awesomeness, featuring people featured on this site previously.  This book is focused on biophysical methods and how they are used to triage and advance leads.  Many of these topics have been covered in depth on this site: thermodynamics, protein-protein interactions, HDX, MST, SPR, WAC, 1D NMR, Protein NMR, and how to use them in terms of residence time.  There are two case studies, one from Pfizer and one from FOB (Friend of the Blog) Michelle Arkin.  Lastly, and you can figure this out, there is a chapter from Martin Scanlon on fragment libraries.  I won't go into actually reviewing the book; that would be a major conflict of interest (I do have a financial interest in it and Don and I need to pay for that indexing!).

I would appreciate comments on it here, and of course any other questions I would be happy to answer.

Twelfth Annual Fragment-based Drug Discovery Meeting

CHI’s Drug Discovery Chemistry meeting took place over four days last week in San Diego. This was easily the largest one yet, with eight tracks, two one-day symposia, and nearly 700 attendees; the fragment track alone had around 140 registrants. On the plus side, there was always at least one talk of interest at any time. On the minus side, there were often two or more going simultaneously, necessitating tough choices. As in previous years I won’t attempt to be comprehensive but will instead cover some broad themes in the order they might be encountered in a drug discovery program.

You need good chemical matter to start a fragment screen, and there were several nice talks on library design. Jonathan Baell (Monash University) gave a plenary keynote on the always entertaining topic of PAINS. Although there are some 480 PAINS subtypes, 16 of these accounted for 58% of the hits in the original paper, suggesting that these are the ones to particularly avoid. But it is always important to be evidenced-based: some of the rarer PAINS filters may tag innocent compounds, while other bad actors won’t be picked up. As Jonathan wrote at the top of several slides, “don’t turn your brain off.”

Ashley Adams described the reconstruction of AbbVie's fragment libraries. AbbVie was early to the field, and Ashley described how they incorporated lessons learned over the past two decades. This included adding more compounds with mid-range Fsp³ values, which, perhaps surprisingly, seemed to give more potent compounds. A 1000-member library of very small (MW < 200) compounds was also constructed for more sensitive but lower throughput biophysical screens. One interesting design factor was to consider whether fragments had potential sites for selective C-H activation to facilitate fragment-to-lead chemistry.

Tim Schuhmann (Novartis) described an even more “three-dimensional” library based on natural products and fragments. Thus far the library is just 330 compounds and has produced a very low hit rate – just 12 hits across 9 targets – but even a single good hit can be enough to start a program.

Many talks focused on fragment-finding methods, old and new. We’ve written previously about the increasingly popular technique of microscale thermophoresis (MST), and Tom Mander (Domainex) described a success story on the lysine methyltransferase G9a. When pressed, however, he said it did not work as well on other targets, and several attendees said they had success in only a quarter to a third of targets. MST appears to be very sensitive to protein quality and post-translational modifications, but it can rapidly weed out aggregators. (On the subject of aggregators, Jon Blevitt (Janssen) described a molecule that formed aggregates even in the presence of 0.01% Triton X-100.)

Another controversial fragment-finding technique is the thermal shift assay, but Mary Harner gave a robust defense of the method and said that it is routinely used at BMS. She has seen a good correlation between thermal shift and biochemical assays, and indeed sometimes outliers were traced to problems with the biochemical assay. The method was even used in a mechanistic study to characterize a compound that could bind to a protein in the presence of substrate but not in the presence of a substrate analog found in a disease state. Compounds that stabilized a protein could often be crystallized, while destabilizers usually could not, and in one project several strongly destabilizing compounds turned out to be contaminated with zinc.

Crystallography continues to advance, due in part to improvements in automation described by Anthony Bradley (Diamond Light Source and the University of Oxford): their high-throughput crystallography platform has generated about 1000 fragment hits on more than 30 targets. Very high concentrations of fragments are useful; Diamond routinely uses 500 mM with up to 50% DMSO, though this obviously requires robust crystals.

Among newer methods, Chris Parker (Scripps) discussed fragment screening in cells, while Joshua Wand (U. Penn) described nanoscale encapsulated proteins, in which single protein molecules could be captured in reverse micelles, thereby increasing the sensitivity in NMR assays and allowing normally aggregation-prone proteins to be studied. And Jaime Arenas (Nanotech Biomachines) described a graphene-based electronic sensor to detect ligand interactions with unlabeled GPCRs in native cell membranes. Unlike SPR the technique is mass-independent, and although current throughput is low, it will be fun to watch this develop.

We recently discussed the impracticality of using enthalpy measurements in drug discovery, and this was driven home by Ying Wang (AbbVie). Isothermal titration calorimetry (ITC) measurements suggested low micromolar binding affinity for a mixture of four diastereomers that, when tested in a displacement (TR-FRET) assay, showed low nanomolar activity. Once the mixture was resolved into pure compounds the values agreed, highlighting how sensitive ITC is to sample purity.

If thermodynamics is proving to be less useful for lead optimization, kinetics appears to be more so. Pelin Ayaz (D.E. Shaw) described two Bayer CDK kinase inhibitors having either a bromine or trifluoromethyl substitution. They had similar biochemical affinities and the bromine-containing molecule had better pharmacokinetics, yet the trifluoromethyl-containing molecule performed better in xenograft studies. This was ultimately traced to a slower off-rate for the triflouromethyl-substituted compound.

The conference was not lacking for success stories, including MetAP2 and MKK3 (both described by Derek Cole, Takeda), LigA (Dominic Tisi, Astex), RNA-dependent RNA polymerase from influenza (Seth Cohen, UCSD), and KDM4C (Magdalena Korczynska, UCSF). Several new disclosures will be covered at Practical Fragments once they are published.

But these successes should not breed complacency: at a round table chaired by Rod Hubbard (Vernalis and University of York) the topic turned to remaining challenges (or opportunities). Chief among these was advancing fragments in the absence of structure. Multiprotein complexes came up, as did costs in terms of time and resources that can be required even for conventional targets. Results from different screening methods often conflict, and choosing the best fragments both in a library and among hits is not always obvious. Finally, chemically modifying fragments can be surprisingly difficult, despite their small size.

I could go on much longer but in the interest of space I’ll stop here. Please add your thoughts, and mark your calendars for next year, when DDC returns to San Diego from April 2-6!

Dynamic undocking for better predictions

Computational screening continues to improve, due in part to a better understanding of the energetics of protein-ligand interactions. But for low affinity fragments, differentiating binders from nonbinders is still challenging. In a recent paper in Nature Chemistry, Xavier Barril and collaborators at the Universitat de Barcelona, Discngine, Vernalis, and the University of York describe a new approach that sidesteps thermodynamics.

The researchers started with the notion that, in many cases, a single hydrogen bond is critical for the stability of a protein-ligand complex. Rather than trying to calculate the binding energy of the complex, they instead ran “dynamic undocking” (DUck) experiments. This involved “steered molecular dynamics” simulations in which the researchers calculated how much work (W_QB) is required to move the ligand from the bound state to a quasi-bound state in which the key hydrogen bond is broken. The calculations do not consider what happens under equilibrium conditions (ie, unbinding and rebinding), so W_QB should not necessarily correlate with binding affinity. Still, one might expect ligands that require a particularly high energy to dissociate (for example, W_QB > 6 kcal/mol) to have higher affinities. This turned out to be the case for ligands targeting several different proteins: the kinase CDK2, the GPCR adenosine A2A receptor, and the protease trypsin. Indeed, receiver operating characteristic curves (an analysis comparing known binders and decoys) showed a significant enrichment of true binders.

Next, the researchers compared DUck with several commonly used computational docking approaches. Again, and not surprisingly, there was essentially no correlation. However, the researchers argue that this is a feature, not a bug, since the very orthogonality of the approaches should provide better predictions: a molecule that docks favorably and has a high W_QB is more likely to be a real hit.

This is a nice idea, but does it work in practice? To find out, the researchers turned to the old work-horse protein HSP90 and performed docking experiments on 280,000 fragments. Of the top 450 hits, 139 diverse molecules were chosen for DUck. Several dozen of these were then tested for binding using three different ligand-observed NMR experiments.

Of 21 molecules with W_QB > 6 kcal/mol, 8 confirmed as binders by all three NMR methods – an impressive hit rate of 38%. SPR confirmed binding for four of these (with dissociation constants between 0.077 and 0.73 mM), while three yielded crystal structures. In contrast, only one out of 15 molecules with W_QB between 3 and 6 kcal/mol confirmed, while none of 11 molecules with W_QB < 3 kcal/mol were clear hits. In other words, not only is DUck able to improve identification of true binders, it appears to have a fairly low false negative rate.

In a sense, this approach addresses the question of kinetics. Molecules that dissociate slowly from their target are becoming increasingly fashionable; perhaps DUck can be used to identify them. Although the researchers do not make this claim, several of the authors described an experimental “off-rate screening” approach a few years ago. It will be fun to see further developments, particularly as the method is extended to incorporate information beyond a single hydrogen bond.

Lead Generation: Methods, Strategies, and Case Studies

Lead generation refers to that point in drug discovery when initial screening hits against a target are wrought into compelling chemical matter. This chemical matter is often plagued with deficiencies in terms of potency, pharmacokinetics, or novelty, yet it provides a starting point for further optimization. This is the subject of a massive (800+ pages!) new two-volume work edited by Jörg Holenz (GlaxoSmithKline, formerly AstraZeneca) as part of Wiley’s Methods and Principles in Medicinal Chemistry series. Readers of this blog will not be surprised to find that fragments play a major role; indeed, the molecule on the cover of the book came out of FBLD. I won’t attempt to summarize all 25 chapters here, but will simply highlight those most relevant to FBLD.

Mike Hann (GlaxoSmithKline) sets the stage in chapter 1 by briefly describing the characteristics of successful leads. He emphasizes the importance of physicochemical properties and avoiding molecular obesity, and how judicious use of metrics can help navigate away from perilous chemical space. He also summarizes internal programs that again demonstrate that fragment-derived leads tend to be smaller and less lipophilic than those from other lead discovery techniques.

In chapter 3, Udo Bauer (AstraZeneca) and Alex Breeze (University of Leeds) discuss the concept of ligandability – the ability of a target to bind to a small molecule with high affinity. Fragments are ideally suited for assessing ligandability, and the researchers briefly describe fragment-based experimental and computational approaches to do so. They also include a nice 11-point summary of factors to consider when starting lead generation on a new target, ranging from the presence of small-molecule binding sites to the number of patent applications.

Chapter 6, by Ivan Efremov (Pfizer) and me, is entirely about fragment-based lead generation. I'm undoubtedly biased, but I think it provides a self-contained and fairly detailed guide to FBLD, including topics such as screening methods, hit validation, metrics, hit optimization, fragment growing vs fragment linking, and case studies on vemurafenib, BACE, MMP-2, LDHA, venetoclax, MCL-1, and GPCRs.

Helmut Buschmann and colleagues at RD&C Research, Development, and Consulting, focus in chapter 9 on optimizing side effects of known molecules to develop new drugs, but they also discuss some interesting older work reporting that 418 of 1386 drugs contain other drugs as internal fragments.

Chapter 12, by Dean Brown (AstraZeneca), is devoted to the hit-to-lead stage, and much of his advice is applicable to FBLD. Dean also includes a fantastic metaphor to illustrate the size of chemical space: "if a typical corporate screening collection were to fit on a postcard, the rest of the earth is the amount of available drug-like space." This assumes a million-compound library and a conservative estimate of 10²³ drug-sized molecules, so if anything it is an understatement.

Molecular recognition is critical for both FBLD and lead generation in general, and this is the topic Thorsten Nowak (C4X Discovery Holdings) tackles in chapter 13. He covers key areas such as thermodynamics, emphasizing the importance of enthalpy while acknowledging the difficulty of prospectively using thermodynamic data. The role of water and halogen bonds are covered, along with some freakishly high ligand efficiency values. There are a couple errors: one paper is categorized as using dynamic combinatorial chemistry when in fact it actually used static libraries, and Tethering is confused with Chemotype Evolution, but overall there's lots of good stuff here.

Biophysical methods are covered in chapter 14, by Stefan Geschwindner (AstraZeneca). These include NMR, SPR, ITC, thermal shift assays, native mass spectrometry, microscale thermophoresis, and more.

Chapter 16, by Ken Page and colleagues at AstraZeneca, discusses "lead quality." This often entails various metrics, from simple ones such as ligand efficiency and LLE to more complicated attempts to predict clinical dosages. Although it is easy to poke fun at metrics, most thoughtful scientists find them useful for making sense of the reams of data generated in lead optimization campaigns.

Chapter 17, by Steven Wesolowski and Dean Brown (both AstraZeneca), is arguably the most entertaining. Entitled "The strategies and politics of successful design, make, test, and analyze (DMTA) cycles in lead generation," it is replete with pithy quotes and even an original (and highly geeky) cartoon. Along with multiple examples, the chapter formulates plenty of questions to consider during lead optimization, and ends with a particularly relevant quote by Billings Learned Hand: “Life is made up of a series of judgments on insufficient data, and if we waited to run down all our doubts, it would flow past us.”

In chapter 23, Sven Ruf and colleagues at Sanofi-Aventis Deutschland describe a success story generating leads against cathepsin A, a target for cardiovascular disease. HTS yielded three different chemical series with sub-micromolar activities, each with different liabilities. Crystallography revealed their binding modes, and this allowed the team to mix and match fragments across the different series to generate a molecule that ultimately went into the clinic. Although this may not be classic FBLD, it does seem to be a good case of using concepts from the field, or fragment-assisted drug discovery.

A similar, if less directed, approach is the subject of chapter 25, the last in the book. Pravin Iyer and Manoranjan Panda (both AstraZeneca) describe "fragmentation enumeration," in which known drugs or clinical candidates are fragmented into component fragments and recombined. On some level the fragments themselves are likely to be privileged; the researchers cite the famous quote by Sir James Black that "the most fruitful basis of the discovery of a new drug is to start with an old drug." Most of the work is computational, although one molecule derived from the approach has encouraging cellular activity against Mycobacterium tuberculosis.

There's far more to this book than could be listed even in this relatively long post, including multiple case studies, so for those of you who are interested in lead generation definitely check it out!

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.

Benchmarking native mass spectrometry

Mass spectrometry (MS) is one of the less common tools to find fragments. In the conceptually simplest approach (native mass spectrometry), you incubate your protein with a putative ligand and ionize the mixture. Fragment binding is detected by an increased mass for the complex, and the strength of binding by the ratio of heavier bound complex peak to protein peak. However, the liquid to gas phase transition is a big step, and often the complex does not survive. Aside from more specialized applications of MS (such as here, here, and here) there aren’t many published examples. A recent paper from Federico Sirtori and colleagues at Nerviano and Università degli Studi di Milano in Eur. J. Pharm. Sci. describes fragment screening by native MS in detail.

The researchers used the reliable model protein Hsp90, which was also used in a previous MS study and in benchmarking other techniques. One of the many benefits of Hsp90 is a wealth of well-characterized inhibitors with a range of affinities, and these were used to calibrate the technique. This turned out to be critical: beyond sample preparation itself (beware non-volatile buffer components), all kinds of parameters can be adjusted including various voltages, temperatures, vacuum strength, and ion source. Get one of these wrong and your non-covalent complex either fails to ionize or blows apart.

In addition to using published data on known compounds, the researchers ran both fluorescence polarization (FP) and surface plasmon resonance (SPR) assays to independently determine dissociation constants. Initially the results from MS (a Q-TOF) were quite different, but after optimization the team was ultimately able to find conditions that gave qualitatively as well as quantitatively similar results for ligands with affinities ranging from picomolar to ~100 micromolar.

Thus encouraged, the team embarked on a fragment screening campaign. The Nerviano fragment library consists of 1914 molecules mostly following the rule of 3, though halogenated fragments up to 380 Da are allowed as are compounds with up to 6 hydrogen bond acceptors. The fragments were run in mixtures of 5, with protein at 2.5 µM and each compound at the low concentration of 10 µM. Sample injection and data processing were automated, and the entire screen took 2 days and 2 mg of protein.

Given the low concentration of fragments, the researchers lowered the bar for potential hits, yielding 282 compounds. These were retested individually, yielding 146 confirmed hits that gave signals of 5.2-29.7% bound protein. This is a high hit-rate, particularly given that these binding levels suggest affinities in the 20-179 µM range. Indeed, only 5 fragments could be competed by a high-affinity binder, suggesting either that the others bind outside the active site or are non-specific (false positives). Regarding false negatives, Nerviano reported the results of an NMR fragment screen against Hsp90 last year, and 12 of 14 hits identified there could also be detected by MS. The other two were likely below the detection limit of the MS assay.

Unfortunately, the researchers do not discuss thermodynamics. In theory enthalpic interactions dominate over entropic interactions in the gas phase, but it is unclear whether any of the observed binders were strongly entropy-driven.

In the end, it appears that fragment screening by native MS is workable, but the sensitivity is probably lower than other techniques. Of course, increasing the ligand concentration would increase the sensitivity to weaker binders, but at the cost of more non-specific binding – which is already considerable. Also, Hsp90 is about the friendliest protein one can imagine. I would be reluctant to try this with a more challenging target that lacks good tool ligands. But if you want to give it a go, this paper provides a wealth of information for getting started. And if you have experience with native MS, please share it in the comments.

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.