21 October 2014

Benchmark Your Process

So, not everybody agrees with me on what a fragment is.  As has been pointed out years ago, FBDD can be a FADD.  In this paper, from earlier this year, a group from AZ discusses how FBDD was implemented within the infectious disease group. Of course, because of the journal, it emphasizes how computational data is used, but you skim over that and still enjoy the paper :-). 

Hot Spots: This is a subject of much work, particularly from the in silico side.  In short, a small number of target residues provide the majority of energy for interaction with ligands.  Identifying these, especially for non-active site targets (read PPI), is highly enabling, for both FBDD and SBDD. To this end, the authors discuss various in silico approches to screening fragments.  They admit they are not as robust as would be desired (putting it kindly).  As I am wont to say, your computation is only as good as your experimental follow up.  The authors indicate that the results of virtual screens must be experimentally tested.  YAY!  They also state that NMR is the preferred method; 1D NMR in particular being the AZ preferred method.  [This is something (NMR as the first choice for screening) that I think has become true only recently.  Its something I have been saying for more than a decade, but I guarantee my cheerleading is not why.] They do note that of the two main ligand-based experiments, STD is far less sensitive than WaterLOGSY.  There is no citation, so I would like to put it out there, is this the general consensus of the community?  Has anyone presented data to this effect?  Specifically, they screen fragments 5-10 per pool with WaterLOGSY and relaxation-edited techniques.  2D screening is only done for small proteins (this is in Infection) and where a gram or more of protein is available.

Biophysics:  They have SPR, ITC, EPIC, MS, and X-ray.  They mention that SPR and MS require high protein concentrations to detect weak binders and thus are prone to artifacts.  They single out the EPIC instrument as being the highest throughput.  [As an aside, I have heard a lot of complaints about the EPIC and wonder if this machine is still the frontline machine at AZ.]  60% of targets they tried to immobilize were successful.  They also use "Inverse" SPR, putting the compounds down; the same technology NovAliX has in their Chemical Microarray SPR.  In their experience, 25% of these "Target Definition Compounds" still bind to their targets. 

They utilize a fragment-based crystallography proof of principle (fxPOP).  Substrate-like fragments (kinda like this?) are screened in the HTS, hits [not defined] are then soaked into the crystal system, and at least one structure of a fragment is solved.  This fragment is then used for in silico screening, pharmacophore models, and the like.  So, this would seem to indicate that crystals are required before FBDD starts.  They cite the Astex Pyramid where fragments of diverse shape are screened and the approach used at JnJ where they screen similar shaped fragments and use the electron density to design a second library to screen.

As I have always said, there are non-X-ray methods to obtain structural information.  AZ notes that SOS-NMR, INPHARMA, and iLOE are three ways.  These are three of the most resource intensive methods: SOS-NMR requires labeled protein (and not of the 15N kind), INPHARMA requires NOEs between weakly competitive ligands (and a boatload of computation), while iLOE requires NOEs of simultaneously binding ligands.  I think there are far better methods, read as requiring fewer resources, to give structural information more quickly (albeit at lower resolution).

The Library:  The describe in detail how they generated their fragment libraries.  They have a 20,000 fragment HCS library.  The only hard filter is to restrict HA<18 .="" 1200="" a="" as="" behind="" bias="" br="" built="" can="" fragment="" have="" hcs="" i="" infection="" library="" nbsp="" nmr="" on="" rules="" same="" stand="" targets="" that.="" the="" they="" towards="" with="">

The Process:   The authors list three ways to tie these methods together:
  1. Chemical Biology: Exploration of binding sites/development of pharmacophores.  I would add that this is also for target validation.  As shown by Hajduk et al. and Edfeldt et al., fragment binding is highly correlated to advancement of the project. 
  2. Complementary to HTS.  At the conference I am at today, one speaker (from Pfizer) said that HTS was for selectivity, FBDD was for efficiency (or Lord, here comes Pete with that one).  I really like that approach.
  3. Lastly, stand alone hit generation.  
I think this paper is a nice reference for those looking to see how one company put their FBDD process in place. Not every company will do it the same, nor should they.  But there is a FBDD process for every company.

20 October 2014

Caveat emptor

Practical Fragments rarely has guest bloggers, but we do make exceptions in special cases. What follows is a (lightly edited) analysis from Darren Begley that appeared on the Emerald blog last year, but since the company's transformation to Beryllium it is impossible to find. This post emphasizes how important it is to carefully analyze commercial compounds. (–DAE)

In a LinkedIn Discussion post, Ben Davis posed the following question:

Do any of the commercially available fragment libraries come with reference 1D NMR spectra acquired in aqueous solution?

Most commercial vendors of fragments do not offer nuclear magnetic resonance (NMR) reference spectra with their compounds useful to fragment screeners; if anything, the experiment is conducted in 100% organic solvent, at room temperature, at relatively low magnetic field strength (DAE: though see here for an exception). The NMR spectra of fragments and other small molecules are greatly affected by solvents, and can vary from sample to sample. Different buffers, solvents, temperatures and magnetic field strengths can generate large spectral differences for the exact same compound. As a result, NMR reference spectra acquired for fragments in organic solvent cannot be used to design fragment mixtures, a common approach in NMR screening. Furthermore, solubility in organic solvent is no measure of solubility in the mostly aqueous buffer conditions typically used in NMR-based fragment screening.

At Emerald [now Beryllium], we routinely acquire NMR reference spectra for all our commercially-sourced fragment screening compounds as part of our quality control (QC) procedures. This is necessary to ensure the identity, the purity and the solubility of each fragment we use for screening campaigns. These data are further used to design cocktails of 9-10 fragments with minimal peak overlap for efficient STD-NMR screening in-house. 

Recently, we selected a random set of commercial fragment compounds, and closely examined those that failed our QC analysis. The most common reason for QC failure was insolubility (47%), followed by degradation or impurities (39%), and then spectral mismatch (17%) (Since compounds can acquire multiple QC designations, total incidences > 100%.) Less than 4% of all compounds assayed failed because they lacked requirements for NMR screening (that is, sufficiently distinct from solvent peaks or lack of non-exchangeable protons). Failure rates were as high as 33% per individual vendor, with an overall average of 16% (see Figure).

These results highlight the importance of implementing tight quality control measures for preliminary vetting of commercially-sourced materials, as well as maintaining and curating a fragment screening library. They also suggest that 10-15% of compounds will fail quality control, regardless of vendor. Do these numbers make sense to you? How do they measure up with your fragment library?

Let us know what you think. (–DB)

15 October 2014

When a Fragment is DEFINITELY not a Fragment

There are lots of papers that use "fragments" or "fragment approaches".  I find a lot of computational papers do this, is it because FBDD has won the field, or its sexy?  Well, in this paper the authors take an interesting spin on the term fragment. For many targets (particularly PPI), peptides are the only tool to assess binding, or the best binders.  However, despite a small vocal minority, I think most people don't consider peptides to be drugs, but instead good starting points.  The REPLACE (Replacement with Partial Ligand Alternatives through Computational Enrichment) method is used to identify fragments for the CDK2A system to identify fragment alternatives to N-terminal portions of the peptide and especially the crucial arginine residue.  As I say, repeatedly, Your Computation is only as good as your Experimental Follow up

This group took a very cautious approach to the initial modeling, understanding that PPIs are difficult to study via computational methods.  They used crystal structures of FLIPs (Fragment Ligated Inhibitory Peptides) and modeled in the compounds against subunit B and D.  Subunit B gave better results and so that was used for further modeling.  [I hate this kind of stuff, strikes me as wrong.]  After further work, they concluded that the modeling was validated and would be predictive for new compounds.  Then designed a library based on a pharmacophore model using scaffolds phenylacetate, five member heterocycles, and picolinates.  
Modeled Compounds.  Cyclin residues have three letter code, peptides one letter codes.  The solid lines show interactions between acidic cyclin D1 residues and the piperinzinylmethyl group of the inhibitor.
They then, bless their hearts, made some compounds. 
In the end, they showed that it is possible to turn peptides into small molecule-ish compounds.  Please note these activities are in millimolar!  So, even with the current debate as to what PPI fragments should look like, I find it very hard to believe that these molecules are in anyway fragments.  Grafting a fragment looking something onto a big something is not "Fragment based Discovery". 

13 October 2014

New poll: FBLD in academia

Since almost half our readers come from academia, we thought the following poll would be of interest. It is being conducted by Michelle Arkin of the University of California San Francisco, one of the powerhouses of FBLD, and should take just a couple minutes.

Please click here to answer four questions regarding your lab, whether you do FBLD, which fragment-finding techniques you use, and how you follow up on fragment hits. The results will be published in a forthcoming new edition of "Fragment-based Approaches in Drug Discovery."


08 October 2014

PPI Fragment Libraries...what do YOU think they should look like?

Dan and I are at the CHI Discovery on Target meeting in Boston.  We taught our award-winning course on FBDD yesterday, but with an emphasis on PPI.  And just in time, Andrew Turnbull, Susan Boyd, and Bjorn Walse  published a paper on PPIs and FBDD (it's open access[Ed:Link fixed]).  The paper is a nice review of PPIs in general (which have already been covered here): structural characteristics, the "hot spot", and computational approaches.  What I thought interesting was their discussion of the physico-chemical properties of PPI fragments.  This is an area were this is a lot of common knowledge, but nothing rigorously studied.  So, into the breach.

They discuss vendor supplied PPI libraries: Asinex, Otava (which does not seem to be a fragment library with a mean MW of~500),  and Life Chemicals.  PPI compounds are thought to need to be more 3D and obey the rule of 4: PPI compounds will tend to be larger and more lipophilic.  Does ontogeny recapitulate philogeny?  To explore this, they looked at 100 fragments orthosterically active against PPI targets (unpublished data) and compared to 100 fragments active against non-PPI targets. 
It appears that PPI fragments are a little larger and more lipophilic than "standard" fragments, but NOT any more 3D.  It should also be noted that the PPI fragments had double the acid and base containing fragments than "standard" fragments.  The authors agree that their dataset is small, and other groups are looking at larger datasets.  But, the conclusion they draw is that PPI fragments should be larger, more lipophilic, and contain at least one polar moiety. 

06 October 2014

Physical properties in drug design

This is the title of a magisterial review by Rob Young of GlaxoSmithKline in Top. Med. Chem. At 68 pages it is not a quick read, but it does provide ample evidence that physical properties are ignored at one’s peril. It also offers a robust defense of metrics such as ligand efficiency.

The monograph begins with a restatement of the problem of molecular obesity: the tendency of drug leads to be too lipophilic. I think everyone – even Pete Kenny – agrees that lipophilicity is a quality best served in moderation. After this introduction Young provides a thorough review of physical properties including lipophilicity/hydrophobicity, pKa, and solubility. This is a great resource for people new to the field or those looking for a refresher.

In particular, Young notes the challenges of actually measuring qualities such as lipophilicity. Most people use log P, the partition coefficient of a molecule between water and 1-octanol. However, it turns out that it is difficult to experimentally measure log P for highly lipophilic and/or insoluble compounds. Also, as Kenny has pointed out, the choice of octanol is somewhat arbitrary. Young argues that chromatographic methods for determining lipophilicity are operationally easier, more accurate, and more relevant. The idea is to measure the retention times of a series of compounds on a C-18 column eluted with buffer/acetonitrile at various pH conditions to generate “Chrom log D” values. Although a stickler could argue this relies on arbitrary choices (why acetonitrile? Why a C-18 column?) it seems like a reasonable approach for rapidly assessing lipophilicity.

Next, Young discusses the influence of aromatic ring count on various properties. Although the strength of the correlation between Fsp3 and solubility has been questioned, what’s not up for debate is the fact that the majority of approved oral drugs have 3 or fewer aromatic rings.

Given that 1) lipophilicity should be minimized and 2) most drugs contain at most just a few aromatic rings, researchers at GlaxoSmithKline came up with what they call the Property Forecast Index, or PFI:

PFI = (Chrom log D7.4) + (# of aromatic rings)

An examination of internal programs suggested that molecules with PFI > 7 were much more likely to be problematic in terms of solubility, promiscuity, and overall development. PFI looks particularly predictive of solubility, whereas there is no correlation between molecular weight and solubility. In fact, a study of 240 oral drugs (all with bioavailability > 30%) revealed that 89% of them have PFI < 7.

Young summarizes: the simple mantra should be to “escape from flatlands” in addition to minimising lipophilicity.

The next two sections discuss how the pharmacokinetic (PK) profile of a drug is affected by its physical properties. There is a nice summary of how various types of molecules are treated by relevant organs, plus a handy diagram of the human digestive track, complete with volumes, transit times, and pH values. There is also an extensive discussion of the correlation between physical properties and permeability, metabolism, hERG binding, promiscuity, serum albumin binding, and intrinsic clearance. The literature is sometimes contradictory (see for example the recent discussion here), but in general higher lipophilicity and more aromatic rings are deleterious. Overall, PFI seems to be a good predictor.

The work concludes with a discussion of various metrics, arguing that drugs tend to have better ligand efficiency (LE) and LLE values than other inhibitors for a given target. For example, in an analysis of 46 oral drugs against 25 targets, only 2.7% of non-kinase inhibitors have better LE and LLE values than the drugs (the value is 22% for kinases). Similarly, the three approved Factor Xa inhibitors have among the highest LLEAT values of any compounds reported.

Some of the criticism of metrics has focused on their arbitrary nature; for example, the choice of standard state. However, if metrics correlate with a molecule's potential to become a drug, it doesn’t really matter precisely how they are defined.

The first word in the name of this blog is Practical. The statistician George Box once wrote, “essentially, all models are wrong, but some are useful.” Young provides compelling arguments that accounting for physical properties – even with imperfect models and metrics – is both practical and useful.

Young says essentially this as one sentence in a caveat-filled paragraph:

The complex requirements for the discovery of an efficacious drug molecule mean that it is necessary to maintain activity during the optimisation of pharmacokinetics, pharmacodynamics and toxicology; these are all multi-factorial processes. It is thus perhaps unlikely that a simple correlation between properties might be established; good properties alone are not a guarantee of success and some effective drugs have what might be described as sub-optimal properties. However, it is clear that the chances of success are much greater with better physical properties (solubility, shape and lower lipophilicity). These principles are evident in both the broader analyses with attrition/progression as a marker and also in the particular risk/activity values in various developability screens.

In other words, metrics and rules should not be viewed as laws of nature, but they can be useful guidelines to control physical properties.

01 October 2014

Safran Zunft Challenge

Dan has already hit the highlights of FBLD 2014.  I won't do the lowlights.  They were few and far between.  I will try to give some flavor of the conference.  If you missed it, they t-shirts given out had this as a design
This was designed by Lukasz Skora of Novartis.  It is keywords used here at the blog, sized by frequency.  That is pretty cool.  It also gives us an idea of what we are really talking about here.  I have some other "flavor of Basel pictures" posted here.  

The conference was excellent, just the right size to allow people to interact at a high level.  The dinner was especially good for this (and the unending wine/beer didn't hurt!).   I have been lucky this year to be at many conferences with many different people.  Damian Young at the Baylor College of Medicine Center for Drug Discovery (and recently of the Broad) has been speaking at all of them about his Diversity Oriented Synthesis (DOS) approach to generating fragments.  Well, this has bothered me, DOS is not Fragments.  Am I some sort of Luddite?  Am I being too purist?  Could be.  

Well, an eminent group of FBLD-ers was gathered around a table during the conference dinner, including Justin Bower and Martin Drysdale of the Beatson, Chris Smith of Takeda, the aforementioned Dr. Young, myself, Terry Crawford of Genentech, and Beth Thomas of the CCDC.  So, out of this discussion, comes the Safran Zunft Challenge, administered by Dr. Bower.  I bet Damian that his molecules are too complex to be "fragments".  What will this mean?  I am betting that a "bad" interaction is worse than a good one, that is going all the way back to the Hann Model.  

So, this one molecule from Damian's presentation.  I have nothing against it per se, but for illustrative purposes.  I bet that his molecules will not have a LEAN (pIC50/HAC) >0.3.  [This is the metric I like, Pete.  I understand the limitations.]  By FBLD2016, Damian expects to have data on his molecules (and he is looking for partners).  If I lose, I owe the undersigned a beer.  Below we have preserved for posterity the discussion and those who were there (no hopping on the beer bandwagon late people!).  

I also think this is a good way for us to discuss the ontology of a "fragment"?  To me, its not just size, it is more of its "nature".  Fragments rely on simple molecules, adding complexity even with small molecules, strips away the "fragment-ness", IMNSHO

29 September 2014

FBLD 2014

FBLD 2014, the fifth in an illustrious series of conferences, took place in Basel, Switzerland last week. Organizers Wolfgang Jahnke (Novartis), Michael Hennig (Roche), and Rod Hubbard (University of York & Vernalis) put together a fantastic event. With 35 talks, 45 posters, and more than 200 delegates, I won’t attempt to give more than a few impressions here. In addition to Teddy’s (and others’) Tweets, Derek Lowe put up several posts (see here, here, and here); please share your thoughts below.

Harren Jhoti delivered a lively and wide-ranging opening keynote summarizing the past 15 years of FBLD as viewed from Astex. Among many other innovations, researchers there are responsible for the Rule of 3, which has been the subject of some debate. Harren emphasized that the “Voldemort Rule” should not be a strait-jacket. Like the Kobayashi Maru, rules are there to be broken, though you need to be something of a James T. Kirk to do so effectively.

Astex has produced what is likely the largest collection of protein-fragment crystal structures, and Harren noted that many proteins appear to have fragment binding sites outside the active site: across 25 different proteins, the average number of total sites is slightly greater than 2. Astex is increasingly targeting these sites for allosteric lead discovery.

The theme of crystallography carried through the conference. As Armin Ruf (Roche) exhorted, “more crystals, more structures.” One challenge is that not all crystal forms are suitable for fragments, and it is not always clear from the outset which forms will work. Armin described their chymase project in which an initial crystal form gave 8 fragment structures, but additional crystal forms allowed them to obtain 6 more. Without the different crystal forms these later fragments would have been crystallographic false negatives, yet the potential of different crystal forms to reveal more hits is under-appreciated: Armin noted that the majority of recent fragment papers reported using only a single crystal form.

The importance of crystallography was emphasized again by Nick Skelton (Genentech), who discussed their NAMPT program (which we covered here). In this project, which utilized dozens of crystal structures, a single atom change to a fragment could completely and unpredictably alter the binding mode.

Obtaining a good crystal is not necessarily easy, though. Andreas Lingel (Novartis) described their efforts to produce a form of B-RAF that would diffract to higher resolution and allow fragment soaks (as opposed to co-crystallization). They tried reducing the “surface entropy” by mutating glutamate and lysine residues to alanine, but only one of a dozen or so mutants expressed well and gave superior crystals. Although this turned out to be useful, the team is still at a loss to explain why the specific mutants are effective.

Continuing the theme of crystallography, Matt Clifton (Beryllium) described what looks to be a significant advance for the protein MCL-1. (This is a collaboration with the Broad Institute, and we previously noted some of their progress here.) The researchers have developed a maltose-binding protein (MBP) fusion of this oncology target that diffracts to 1.9 Å in the absence of any ligand. (MBP fusions are used to help crystallize challenging proteins.) Since they developed this construct in May of this year, the researchers have already solved more crystal structures than had been reported publicly to date, and uncovered some interesting findings. For example, the initial fragment that Steve Fesik’s group found binds in a similar manner to one of his more potent later leads, as does one of the AbbVie fragments; however another AbbVie fragment binds in a somewhat different fashion than the elaborated lead.

The subject of how to effectively sample chemical space was another theme, and to this end Alison Woolford (Astex) proposed the concept of a “minimal pharmacophore”: the minimal interactions necessary to drive fragment binding. Researchers at Astex have systematically cataloged several dozen of these, which include such simple entities as amines, acids, aromatic chlorides, and more abstract concepts such as a 1-bond donor-acceptor (think pyrazole). Alison showed an interesting graph with targets on the y-axis and minimal pharmacophores on the x-axis which revealed some obvious patterns such as the preference of donor-acceptor minimal pharmacophores by kinases, but there were unexpected features as well. In a sense, this is an empirical realization of early docking studies, but it also has interesting implications for library design. For example, Alison suggested avoiding fragments with more than one minimal pharmacophore, as these will not be able to effectively sample as many different sites on a protein: with two pharmacophores, a fragment would be limited to binding sites having matching recognition elements to both rather than just one. This idea ties in with the concept of molecular complexity, but from a more chemocentric point of view.

On the subject of chemistry, Dalia Hammoudeh (St Jude’s Hospital) gave a lovely talk on her experiences developing allosteric inhibitors of DHPS, an antibiotic target. Among other fragment hits from the Maybridge library, one was ostensibly 4-trifluoromethylbenzylamine, but turned out to actually be the Schiff base of this with the corresponding aldehyde. Yet another reminder to always carefully check what you think you have.

Practical Fragments has previously discussed the Genentech MAP4K4 program (here and here), and Terry Crawford gave a nice summary. One of the challenges they faced was that their initial leads had excellent brain penetration, leading to animal toxicity. This forced them to increase size and polar surface area. Although it was problematic in this case, this emphasizes how small and drug-like fragment-derived leads can be. Indeed Vicki Nienaber, who was a prime mover behind the original FBLD 2008 meeting, has devoted much of her efforts at Zenobia to CNS targets.

Finally, Derek Lowe (Vertex) gave a rollicking history of the drug industry, ending with his view of where fragments fit in. He noted that chemists – Valinor not withstanding – play a central role, and in that sense the field is a departure from the general trend of the past decade or so. It still remains to be seen how many of the 30+molecules FBLD has delivered to the clinic will come out the other side, but at least for now the field is thriving. As Chris Lipinski stated last year, “if I had to single out one technology that really took me by surprise and has been very successful, it has been fragment screening.”

24 September 2014

PAINS in Nature

Practical Fragments has previously noted that many pan-assay interference compounds (PAINS) can be found in nature. Indeed, they’ve also found their way – unintentionally – into journals published by Nature Publishing Group. In an effort to educate the scientific community about these artifacts, Jonathan Baell (Monash University) and Mike Walters (University of Minnesota) have just published a Comment in Nature entitled “Chemical con artists foil drug discovery”. This is the clearest discussion I’ve yet seen of PAINS, and it deserves to be widely read.

Since the article is open-access I won’t go into depth here, other than to say that the researchers propose three steps to avoid PAINS.

1) Learn disreputable structures.
As a start, the paper provides a rogue’s gallery of some of the worst molecules, along with memorable interpretations by award-winning New Yorker cartoonist Roz Chast. It would be nice to see this posted in every academic screening center.

2) Check the literature.
This is even easier than having to learn structures, and should prevent people from embarrassing themselves by publishing research that is obviously flawed.

3) Assess assays.
Multiple orthogonal assays are useful for all science, not just FBLD!

Together with the recent C&ENstory and ACS symposium, this article ensures that PAINS are finally reaching the level of recognition such that scientists, reviewers, and editors will no longer be able to claim ignorance. Willful negligence may be another matter, but at least people will be able to recognize it as such.

21 September 2014

Substrate activity screening revisited: substrates as inhibitors

Last year Practical Fragments highlighted substrate activity screening (SAS) as a means for identifying enzyme inhibitors. The idea is to make libraries consisting of potential substrates, modified to reveal interactions: for example, amides that release a fluorescent reporter group when cleaved by a protease. These libraries are then screened against a protein of interest, and any new substrates identified can be transformed into inhibitors by replacing the cleavable bond with some sort of warhead. At the end of that post, we asked why more people weren’t using SAS. In a new paper in ChemBioChem, Pieter Van der Veken and colleagues at the University of Antwerp have partially answered that question, and provided a solution.

The researchers were interested in the oncology target urokinase (uPA), a trypsin-like protease. They built potential substrates from an amino-methylcoumarin designed to fluoresce when cleaved. They used this to assemble a library of 137 molecules, each consisting of the amino-methylcoumarin coupled to a variable fragment. Of these, about 50 contained positively charged moieties likely to interact with the large S1 pocket of uPA, which has a predilection for cationic species. (The rest were diverse molecules.) The library was then screened against the enzyme to look for substrates, but the researchers ran into several difficulties.

First, since all the substrates are poor, the researchers had to use quite a bit of enzyme (about 2.5 micrograms per well) to get a good signal. Second, for the same reason, they had to run the assay for a long time (6 hours). Third, and somewhat unexpectedly, it turns out that SAS is susceptible to an interesting artifact: low levels of contaminating enzymes can cleave substrates, giving false positives. Indeed, the researchers found that commercial uPA isolated from human urine produced a number of hits that did not repeat with recombinant (and presumably purer) enzyme and could not be competed by addition of a potent uPA inhibitor.

Despite these challenges, the researchers identified 11 hits. However, notably absent were some of the fragments known to have affinity for the S1 pocket, such as several guanidines. This is not surprising: for a molecule to be processed as a substrate it needs to be able to fit in the S1 pocket as well as to position the cleavable bond near the catalytic machinery – subtle changes in geometry will prevent processing. This got the researchers thinking about alternative ways to use their library.

The approach they came up with, “modified substrate activity screening” (MSAS), starts by first looking for inhibitors rather than substrates, since a poor substrate can behave as an inhibitor. The idea is to incubate library members with the enzyme and a single potent substrate. This allowed the researchers to reduce the enzyme concentration by 10-fold and run a much shorter assay (10 minutes). It also reduces the risk that contaminating enzymes will be responsible for activity, though of course inhibition assays are susceptible to all sorts of other artifacts.

When the researchers applied MSAS to uPA, not only did they rediscover the 11 hits they had identified as substrates previously, they also identified 17 additional molecules, including all the guanidine-containing fragments.

The researchers propose a flowchart for MSAS in which compounds are first screened for inhibition. These hits are then followed up using SAS to determine whether some of these inhibitors are substrates too. Any substrates thus identified can be readily transformed into inhibitors by adding an appropriate warhead. Inhibitors identified in the first step that aren’t substrates can also be useful to provide structure-activity relationships and new fragments to take forward.

Of course, one could argue that if you are doing inhibition assays, there is no point in going to all the trouble of making custom libraries for MSAS. That said, if you’ve already got the substrate-based libraries, doing an initial inhibition screen is probably a good idea.

17 September 2014

From fragment to lead: just remove (high energy) water

The proverb "well begun is half done" suggests that getting started comprises much of the work. Such is the case for fragments that bind to “hot spots,” sites on a protein that are particularly adept at binding small molecules and other proteins. Though fragment-to-lead efforts can give impressive improvements in potency, much of the binding energy of the final molecule resides in the initial fragment. In a new paper in ChemMedChem, Osamu Ichihara and colleagues at Schrödinger have asked why.

The researchers examined 23 published fragment-to-lead examples for which crystal structures and affinities of the fragment and lead were available and in which the fragment maintained its binding mode. They then used a computational tool called WaterMap to assess the water molecules displaced by both the initial fragment as well as the optimized molecule. They compared the calculated thermodynamic parameters (free energy, enthalpy, and entropy) of the water molecules displaced by the initial fragment (core hydration sites) or the bits added to it in the lead (auxiliary hydration sites).

When a protein is surrounded by water, water molecules bind just about everywhere. However, some of these water molecules may “prefer” to be in bulk solvent rather than, say, confined within a hydrophobic pocket on the protein. Perhaps not surprisingly, most of the water molecules displaced by ligands turned out to be of this “high-energy” or unstable variety. Also, the researchers consistently found that the core hydration sites were more unstable than the auxiliary hydration sites. In other words, fragments appear to displace the most unstable water molecules. Moreover, most of this higher energy was due to unfavorable entropy.

It is important to note that the focus here is on individual water molecules (or hydration sites) assessed computationally. The researchers are careful to stress that these may not correlate with thermodynamic parameters obtained by isothermal titration calorimetry (ITC). This is because ITC measures the entire system – protein, ligand, and all of the water – and factors such as protein flexibility can confound predictions.

The researchers summarize their findings as follows.
1) The presence of hydrogen bond motifs in a well-shaped small hydrophobic cavity is the typical feature of the hot spot surface  
2) Because of these unique surface features, the water molecules at hot spots are entropically destabilized to give high-energy hydration sites 
3) Fragments recognize hot spots by displacing these high-energy hydration sites
This provides a framework for understanding several phenomena. First, it describes the origin of hot spots. Second, it explains why much of the binding energy of an optimized molecule resides in the initial fragment; additional waters displaced are not as unstable as those displaced by the fragment, so they don’t give you as much bang for your atom. As a corollary, this might help explain the leveling off or decline in ligand efficiency often observed as molecules become larger.

The researchers go on to discuss specific examples of high-energy waters, noting that a water molecule involved in one or more hydrogen bonds may be particularly hard to replace because recapitulating the precise interaction(s) may be difficult. This is especially true for fragment-growing efforts (where one is likely to be limited in the choice of vector and distance) that aim to displace a high-energy water. Thus, the researchers suggest focusing on fragments that themselves displace high-energy waters, rather than trying to displace these later.

This seems like sound advice, but it likely reflects what folks already do. Since fragments that displace high-energy waters are likely to bind most effectively, won’t these be prioritized anyway? Regardless, this is an interesting and thought-provoking paper.

15 September 2014

A COMT Tease...

S-adenosyl-methionine (SAM) is a hot molecule; you could probably make a good living selling it these days.  SAM-transferases of all types are "hot" targets, especially in epigenetics.  However, one current target is COMT, or catechol-O-methyl transferase.  COMT lives in a far different space than the epigenetics one, neurodegeneration.  There are several current Parkinson's Disease treatments based upon catechol, but as you would expect, there is toxicity associated with these.  
So, a team at Takeda decided to go after SAM-competitive molecules.  To this end, they screened 11,000 fragments using a enzymatic assay @100 uM.  52 hits (>15% inhibition) were found for a 0.15% hit rate.  They note this is a very low hit rate for what appears to be a very ligandable pocket. They then used LC-MS/MS and SPR to remove reactive moieties and non-SAM competitive molecules.  This led to compounds (4-6) and SAR by Corporate Collection (7). 
They followed up on these four compounds with DSF, STD-NMR, and X-ray.  They were able to co-crystallize 5 with mouse COMT.  This is the first (reported) structure of COMT with a SAM-competitive molecule. 

They mention that they took a "build up" approach, but I presume that is for for future papers. 

10 September 2014

Whatcha Want? Whatcha Really Really Want?

There is a rule in our house: You cannot decorate your room for Christmas until November 1st.  Well, the countdown has begun as my son reminded me that is less than two months away.  So, to help everyone get into the Christmas (Hannukah, Diwali, and so on) spirit, I wanted to ask what cha want?  So what cha want?

Let's divide this in to two lists: Aspirational and Possible.  Below are some that Dan and I came up with.  But this is really your wish list.  Let us know in the comments.

Possible: Aqueous spectra for all commercially available fragments. Maybridge and Key Organics are here/getting here. 
Experimental solubility and 24 hour stability for commercial libraries.  
No PAINS in commercially available libraries.  I believe it is ~8% right now.  
No more rhodanines, anywhere and ever!

Aspirational: I know Peter Kenny wants people to stop using metrics that are arbitrarily defined.
Standard vocabulary for the field.  What's an active, hit, lead, etc.?

08 September 2014

Fragments vs MAP4K4

Mitogen Activated Protein Kinase Kinase Kinase Kinase 4, or MAP4K4, is one of the 500+ human kinases that doesn’t get a whole lot of attention, in part perhaps because there aren’t many good tool compounds out there. A new paper from Genentech in Bioorg. Med. Chem. Lett. reports an attempt to change this.

The researchers started with a surface plasmon resonance (SPR) screen of 2361 fragments, yielding 225 confirmed hits with KD values between 10 and 2010 µM, all with ligand efficiency (LE) values above 0.3 kcal/mol/atom. This seems like a good use of LE: with hundreds of hits to choose from, some sort of triage is necessary, and you might as well go with those with the highest LE.

Compound 1 had moderate potency and excellent LE, as well as a structure familiar from other kinase programs. Modeling suggested growing off the amine, and a small set of compounds were made including compound 7, which gave a 10-fold boost in potency, albeit with a loss in LE. Crystallography of a close analog of compound 7 revealed that it bound as expected, and also suggested a fragment growing approach.

A number of substituents were introduced, all with an eye towards keeping lipophilicity low (clogD < 3.5). Compound 16 was the most potent, though the solubility was poor, and adding polar substituents didn’t help much. Compound 25 had similar potency, and in this case adding a polar substituent (compound 44) improved solubility too. The PK profile in mice was also reasonable.

Unfortunately, when tested at 1 µM against 63 kinases, compound 44 inhibited 16 of them by at least 75%, suggesting that it will not make a useful tool compound. The team reported better selectivity earlier this year with a series of compounds derived from a different fragment hit identified in the same SPR screen. Yet despite the outcome, this is a nice case study in using ligand efficiency, calculated hydrophobicity, and structural information to guide fragment growing.

03 September 2014

Fragment growing vs fragment linking

Results from our latest poll are in. As expected, fragment growing is both more successful and (thus) more popular than fragment linking, but there are a few surprises.

First, it was interesting to see that more than a third of the 69 respondents have not tried fragment linking. Actually, the fraction is probably higher since people could vote more than once (though unfortunately Polldaddy does not provide information as to how many did).

Second, despite its reputation for difficulty, roughly half of respondents who tried fragment linking reported that it worked “OK” or “well.” In fact, more people said that it worked well than that it failed outright. Again, these numbers should be taken cautiously since multiple people at the same organization may have voted on the same projects. And of course, one person’s definition of “OK” may be another’s definition of “marginal.” Still, if you have a tough target where fragment linking looks like a way forward, feel free to use these poll results to bolster your case. And please share your experiences in the comments, positive or negative.

01 September 2014


Just a quick heads-up that Celia Arnaud has a nice story on pan-assay interference compounds (PAINS) in the latest issue of Chemical and Engineering News. Celia attended the PAINS symposium at the ACS meeting last month and spoke with several of the speakers for the piece.

As far as I know this is the first time C&EN has devoted an entire article to PAINS. It’s a fast read so I won’t summarize it here, other than to say that she does pick up on the concept of PAINS-shaming, which Teddy has also advocated. Although Practical Fragments has done some of this, most PAINS are not fragments, so it wouldn’t really be appropriate to do much of it here (though please visit HTSpains).

I do hope Celia’s article is widely read by practicing scientists, journal editors, and reviewers. The need for more PAINS recognition is amply illustrated by this article published in the most recent issue of J. Med. Chem. which reviews reported inhibitors of AP-1, many of them dubious. Let's hope that the C&EN piece cuts down on future pollution.

28 August 2014

The First Protein-Carbohydrate Interaction Inhibitor

Immunomodulation is all the rage, particularly in terms of cancerHyaluronan (HA) is a component of the extracellular matrix.  CD44 is a major cell receptor of HA and its fragments.  Its differential response to HA or HA fragments leads to the different biologies. However, due to the different biologies there are limitations to what can be done with HA fragments.  A selective inhibitor of CD44-HA would prove an invaluable tool. Also, in the grandest of Grant-Application-ese, a small molecule inhibitor could be useful for inflammatory diseases and cancer.  

In this paper, results are presented towards this goal.  The hyaluronan-binding domain (HABD) of CD44 is competent to bind oligosaccharides, and even better has been crystallized. In terms of the binding site:
From the structural data, one might conclude that CD44 is not an easily druggable target. The murine HABD−HA complex reveals an extended HA binding site with surface area exceeding 800 Å^2 and molecular binding stabilized by a large number of weak interactions involving at least seven consecutive saccharide units of HA. The HABD has no well formed or deep pockets that would serve as attractive binding sites for small molecule inhibitors and is known to undergo small but important conformational changes upon binding HA. In many respects, the protein−polysaccharide complex resembles protein−protein interactions that are difficult to disrupt effectively with small molecules.

Using SPR, they screened 1000 fragments from the Maybridge Ro3 fragment library at 5 mM resulting in a 4% hit rate. 21 fragments were crystallized (Table 3 in SI), resulting in 5 co-crystals.  Cpds 1 and 2 were deemed worthy based upon their binding site. 
They were poor in terms of blocking HA binding to CD44.  So, they then did some Analog by Catalog and some merging, based upon other scaffolds and ended up with 5a, which has improved affinity for the HABD and had a measurable ability to block HA binding to the HABD.  

This is a interesting paper to me simply because of the target choice:protein-carbohydrate interaction.  I believe this is the first example of FBHG against a PCI. 

25 August 2014

Metallophilic fragments – or PAINS?

Several years ago we described fragment libraries designed to chelate metal ions. The idea is that these could serve as affinity anchors to target metal-containing proteins. However, in designing any fragment library, it is essential to avoid pan-assay interference compounds (PAINS), molecules that act through pathological mechanisms. A new paper in Bioorg. Med. Chem. Lett. by Amy Barrios and collaborators at the University of Utah and University of California San Diego illustrates one of these mechanisms.

The researchers were interested in a protein tyrosine phosphatase (PTP) called LYP. PTPs contain catalytic cysteine residues and are thus particularly prone to false positives caused by oxidation or adventitious metals such as zinc. The researchers screened a library of 96 metal-chelating fragments against LYP in the presence or absence of zinc to find fragments that could either rescue the enzyme or inhibit it, either cooperatively with zinc or on their own. Not surprisingly, they were able to find several fragments that could rescue LYP from added zinc, presumably by coordinating the metal and removing it from the active site.

The most potent inhibitor of the enzyme was 1,2-dihydroxynaphthalene, with an IC50 of 2.5 µM. However, the researchers quickly discovered that it was time-dependent, showing greater potency the longer it was incubated with the enzyme. This is a classic sign of something funny going on, and the researchers realized that molecules like this can oxidize spontaneously. In fact, the oxidized product (1,2-naphthoquinone) is even more potent, and also time-dependent (IC50 = 1.1 µM after 2 hours). Not only can napthoquinones directly modify cysteine residues, they can generate reactive oxygen species that can in turn modify cysteine residues – this very molecule was reported as doing so more than five years ago.

This is the kind of mechanism you want to avoid, and it is likely to rear its ugly head whenever compounds of this ilk are screened, particularly against a protein with an active-site cysteine. Hopefully this publication will serve as a warning to folks who may be using this screening library.

One could argue that this paper falls into the category of “you probably already knew this.” However, even if you knew it, many others likely did not. At the ACS meeting symposium on PAINS earlier this month, Kip Guy urged people to publish their PAINS stories. They may not be the sexiest papers, but if they inform others what to avoid they may be among the most useful.

20 August 2014

Like the Elves to Valinor?

There are some perqs to being a consultant.  I go to work most days in my jammies, I can work from anywhere with WiFi, and get to work with great people.  I also have a lot of freedom with what I can say/do/write.  Back in April at the CHI Drug Discovery Chemistry meeting, I ran into an editor from an ACS publication.  Now, if you have ever been at a conference with me you know I am a social butterfly.  New face, let's chit chat.  This editor was very nice and after some social niceties, I asked who is refereeing your journal?  This was a general query having to do with some poor quality fragment papers recently, and before I even saw this!  She was polite and asked what do you mean?  I said, well I blog on fragments and we come across crap in JMedChem and the like all the time.  Like this.  I think at this point she obviously was thinking of me like this http://3.bp.blogspot.com/-_Vv1dw3xm-w/TzwEGm5D-YI/AAAAAAAAFAA/eROp1AEvGTo/s1600/basement2.jpg.  Then I mentioned that the blog was Practical Fragments and her attitude changed.  So, this blog has "street cred"!!  She then asked me if I would write a Viewpoint on the future of FBDD.  Sure, I said.  This could be fun.  

At the same time, I was preparing a talk for the Zing FBDD conference.  So, I decided to make that talk (that's a link to SlideShare, I hope it works) a demo for the Viewpoint. Give it a read, its short and sweet (at least I think).  

For those of you without 10 minutes to spare, here are the take home points from the Viewpoint:
  • Fragonomics is a key component of most (all?) hit generation processes
  • It is a fully mature field.  The current debates amount to quibbling about details.
  • It has no future as a stand-alone field.  But there are still challenges for it to tackle.
  • Medchemists no longer rule the field.  
"The age of the medchemist is over; now is the time of the biophysicist." 
 This got some serious push back at the conference, and I expect (hope?) it will here too.  Of course, I am paraphrasing this. I am not suggesting that medchemists make like the Elves and sail off to Valinor.  They are still incredibly important and can still play a role in early hit generation.  However, the focus, thanks to Fragonomics, is vastly different.  A chemically trained biophysicist can run a fragment-based hit generation project and you don't have to have engage the most precious resource (medchem) until well into the process.  This is a good thing.  

Well, I have planted my flag.  Now its time for you all to weigh in.

18 August 2014

248th ACS National Meeting

The Fall ACS National Meeting was held in my beautiful city of San Francisco last week, and a number of topics of interest to Practical Fragments were on the agenda.

First up (literally – Sunday morning) was a session on pan-assay interference compounds (PAINS) organized by HTSPAINS-master Mike Walters of the University of Minnesota. Mike developed his interest in PAINS like many – from painful experience. After screening 225,000 compounds against the anti-fungal target Rtt109, he and his group found several hits that they identified as PAINS, but not before spending considerable time and effort, including filing a patent application and preparing a manuscript that had to be pulled. One compound turned out to be a “triple threat”: it is electrophilic, a redox cycler, and unstable in solution.

Mike had some nice phrases that were echoed throughout the following talks, including “subversively reactive compounds” and SIR for “structure-interference relationships,” the evil twin of SAR. To try to break the “PAINS cycle” Mike recommended more carefully checking the literature around screening hits and close analogs (>90% similarity). Of course, it’s better if you don’t include PAINS in your library in the first place.

Jonathan Baell (Monash), who coined the term PAINS back in 2010, estimated that 7-15% of commercial compounds are PAINS, and warned that even though PAINS may be the most potent hits, they are rarely progressable, advice that is particularly needed in academia. For example, the majority of patent applications around the rhodanine moiety come from academia, whereas the majority of patent applications around a more reasonable pharmacophore come from industry. Jonathan also warned about apparent SAR being driven by solubility. Finally, he noted that while it is true that ~6.5% of drugs could be classified as PAINS, these tend to have unusual mechanisms, such as DNA intercalation.

As we discussed last week, anyone thinking about progressing a PAIN needs to make decisions based on sound data. R. Kip Guy (St. Jude) discussed an effort against T. brucei, the causative agent of sleeping sickness. One hit from a cellular screen contained a parafluoronitrophenyl group that presumably reacts covalently with a target in the trypanosome and was initially deemed unprogressable. However, a student picked it up and managed to advance it to a low nanomolar lead that could protect mice against a lethal challenge. It was also well tolerated and orally bioavailable. Kip noted that in this case chemical intuition was too conservative; in the end, empirical evidence is essential. On that note he also urged people to publish their experiences with PAINS, both positive and negative.

There were a scattering of nice fragment talks and posters. Doctoral student Jonathan Macdonald (Institute of Cancer Research) described how very subtle changes to the imidazo[4,5-b]pyridine core could give fragments with wildly different selectivities. I was particularly tickled by his opening statement that he didn’t need to introduce the concept of fragment-based lead discovery in a general session on medicinal chemistry – another indication that FBLD is now mainstream.

Chris Johnson (Astex) told the story of their dual cIAP/XIAP inhibitor, a compound in preclinical development for cancer. As we’ve mentioned previously, most IAP inhibitors are peptidomimetics and are orders of magnitude more potent against cIAP than XIAP. Astex was looking for a molecule with similar potency against both targets. A fragment screen gave several good alanine-based fragments, as found in the natural ligand and most published inhibitors, but these were considerably more potent against cIAP. They also found a non-alanine fragment that was very weak (less than 20% inhibition at 5 mM!) but gave a well-defined crystal structure. The researchers were able to improve the affinity of this by more than six orders of magnitude, ultimately identifying compounds with low or sub-nanomolar activity in cells and only a 10-fold bias towards cIAP. This is a beautiful story that illustrates how important it is to choose a good starting point and not be lured solely by the siren of potency.

Alba Macias (Vernalis) talked about their efforts against the anti-cancer targets tankyrases 1 and 2 (we’ve previously written about this target here). In contrast to most fragment programs at Vernalis, this one started with a crystallographic screen, resulting in 62 structures (of 1563 fragments screened). Various SPR techniques, including off-rate screening, were used to prioritize and further optimize fragments, ultimately leading to sub-nanomolar compounds.

The debate over metrics and properties continued with back-to-back talks by Michael Shultz (Novartis) and Rob Young (GlaxoSmithKline). Michael gave an entertaining talk reprising some of his views (previously discussed here). I was happy to see that he does agree with the recent paper by Murray et al. that ligand efficiency is in fact mathematically valid; his previous criticism was based on use of the word “normalize” rather than “average”. While this is a legitimate point, it does smack of exegesis. Rob discussed the importance of minimizing molecular obesity and aromatic ring count and maximizing solubility, focusing on experimental (as opposed to calculated) properties. However, it is important to do the right kinds of measurements: Rob noted that log D values of greater than 4 are essentially impossible to measure accurately.

Of course, this was just a tiny fraction of the thousands of talks; if you heard something interesting please leave a comment.

13 August 2014

Intentionally dirty fragments

Practical Fragments has tried to publicize the dangers of pan-assay interference compounds, or PAINS. These compounds show up as nuisance hits in lots of assays. So what are we to make of a new paper in Curr. Opin. Microbiol. by Pooja Gopal and Thomas Dick, both at the National University of Singapore, entitled “Reactive dirty fragments: implications for tuberculosis drug discovery”?

As the researchers point out, several approved anti-tuberculosis drugs are fragment-sized and hit multiple targets; they are “dirty drugs”. For example, isoniazid (MW 137, 10 heavy atoms), is an acylhydrazide that is metabolically activated and forms an adduct with an essential cofactor, causing havoc to the pathogen. Ethionamide (MW 166, 11 heavy atoms), a thioamide, works similarly. The fact that these molecules are so small probably allows them easier passage through the microbe’s rather impermeable cell membrane, and the fact that they hit multiple targets may make it more difficult for the organism to develop resistance. The researchers conclude:
The success of small dirty drugs and prodrugs suggests that fragment-based whole cell screens should be re-introduced in our current antimycobacterial drug discovery efforts.
While it is true that many antimicrobials do have reactive warheads, and it is also true that there is a huge need for new antibiotics, I worry about this approach. Not only is there an increased risk of toxicity (isoniazid in particular has a long list of nasty side effects), it can be very hard to determine the mechanism of action for these molecules, complicating optimization and development. As evidence, look no further than pyrazinamide (MW 123, 9 heavy atoms). Despite being used clinically for more than 60 years, the mechanism remains uncertain.

Fragment-based lead discovery is typically more mechanistic: find an ideal molecule for a given target. Indeed, much of modern drug discovery takes this view. Gopal and Dick propose a return to a more phenomenological, black-box approach. This may have value in certain cases, but at the risk of murky or worse misleading mechanisms.

If you do decide to put PAINS into your library, you might want to read a new paper in Bioorg. Med. Chem. by Kim Janda and collaborators at Scripps and Takeda. They were interested in inhibitors of the botunlinum neurotoxin serotype A (BoNT/A), which causes botulism.

Since BoNT/A contains an active-site cysteine, the researchers decided to pursue covalent inhibitors, and the warheads they chose, benzoquinones and napthoquinones, are about as PAINful as they get. However, in contrast to other groups, they went into this project with their eyes wide open to the issue of selectivity and examined the reactivity of their molecules towards glutathione. Reaction with this low molecular weight thiol suggests that a compound is not selective for the protein. Not surprisingly, selectivity was generally low, though a few molecules showed some bias toward the protein.

The researchers also tried building off the benzoquinone moiety to target a nearby zinc atom, and although they were able to get low micromolar inhibitors, these no longer reacted with the cysteine; apparently when the ligand binds to zinc, the protein shifts conformation such that the cysteine residue is no longer accessible.

To return to the premise of Gopal and Dick, there can be a therapeutic role for dirty molecules. The fact that dimethyl fumarate is a highly effective blockbuster drug for multiple sclerosis calls for a certain degree of humility. However, if you do decide to pursue PAINS, you should do so in full awareness that your road to a drug – not to mention a mechanism – will likely be much longer and more difficult.

11 August 2014

Measuring 3D Fragments

3D fragments is still a topic up for discussion/debate.  Of course, determining what is a 3D fragment is also open to debate.  As presented last year, nPMI seems to be the current "best" method.  FOB Chris Swain has done some neat analyses around nPMI and included it in his overview of commercial libraries.  Last year at the NovAliX Biophysics conference, Glyn Williams from Astex presented the "plane of best fit" (PBF) as a superior way to analyze 3D-arity.  At the recent Zing FBDD conference, Chris Murray presented the "plane of best fit" and argued again that it was superior.  So, of course, I asked Chris Swain if he had compared them, and he said, but wait a minute.  

Well, Chris was able to compile it with the help of his son, Matt (obviously the apple does not fall from the tree).  So, go check out his comparison of nPMI with PBF.  He ran 1000 fragments through both and concluded this: 
Whilst both descriptors are intended to provide information on the 3D structure of the molecule it looks like the PBF provides more granularity which may be particularly useful when looking at small fragments.
 So, I present this as a "go get 'em, folks!".  I am particularly interested to know if people are currently using PBF and if their results jibe with Matt's.