29 October 2017

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

There are many great testaments to humanity's perseverance.   The Pyramids at Gizahttps://www.ancient.eu/uploads/images/display-5687.jpg, the Cathedral of Notre Dame https://upload.wikimedia.org/wikipedia/commons/thumb/b/be/Notre_Dame_de_Paris%2C_East_View_140207_1.jpg/220px-Notre_Dame_de_Paris%2C_East_View_140207_1.jpg, the Great Wall of Chinahttp://vizts.com/wp-content/uploads/2016/02/great-wall-of-china-view.jpg, 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.

23 October 2017

Poll results: does your primary fragment library contain racemates?

Our latest poll asked just this question. We received 72 responses, and the results are shown here.

Almost half of respondents said they include racemates in their library, as recommended by Claudio Dalvit and Stefan Knapp in the paper that inspired this poll. Another 40% said they had some racemates and some pure enantiomers in their library, which presumably reflects the fact that some enantiomers are more readily available than others.

Only about 10% of respondents said that all chiral fragments in their library are pure enantiomers.

And perhaps most surprisingly, only a single respondent said he or she doesn’t screen chiral fragments at all.

Personally I like racemates because they present an easy follow up experiment: if the two enantiomers have different activity, you are more likely looking at genuine activity as opposed to some sort of artifact

Of course, these poll results don’t tell how many chiral compounds are in the typical library. One source told me that his organization's 5000 molecule collection does contain chiral fragments - but only about 20 of them. It will be interesting to see whether we start to see more chiral fragments appear in fragment success stories.

16 October 2017

Docking for finding and optimizing fragments

Docking can sometimes seem like the Rodney Dangerfield of FBDD: it don’t get no respect. In last year’s poll of fragment finding methods, computational approaches ranked in seventh place. This partly reflects the largely biophysical origins of FBDD, but it is also true that ranking low affinity fragments is inherently challenging. Still, the continuing rise in computational power means that methods are rapidly improving. A recent paper in J. Med. Chem. by Jens Carlsson and collaborators at Uppsala University, the Karolinska Institute, and Stockholm University illustrates just how far they can take you.

The researchers were interested in the enzyme MTH1, whose role in DNA repair makes it a potential anti-cancer target. The crystal structure of the protein bound to an inhibitor had previously been reported, and this was used for a virtual screen (using DOCK3.6) of 300,000 commercially available molecules, all with < 15 non-hydrogen atoms, from the ZINC database.

Finding fragments is one thing, but one really wants slightly larger, more potent compounds to begin lead optimization. Thus, the top 5000 fragments were analyzed to look for analogs with up to 6 additional non-hydrogen atoms among the 4.4 million commercial possibilities. This led to 118,421 compounds, each of which was then virtually screened against MTH1. Of the initial 5000 fragments, the top 1000 that had at least 5 analogs with (predicted) higher affinity were manually inspected. Of 22 fragments purchased and tested in an enzymatic assay, 12 showed some activity, with the 5 most active showing IC50 values between 5.6 and 79 µM and good ligand efficiencies.

Since each of these fragments had commercially available larger analogs, the researchers purchased several to see if these did indeed have better affinities. Impressively, this turned out to be the case: both compounds 1a and 4a bound more than two orders of magnitude more tightly than their fragments. Interestingly, while the researchers were unable to obtain crystal structures of fragments 1 and 4 bound to MTH1, they were able to obtain crystal structures of 1a and a close analog of 4a, and these bound as predicted.

Of course, not everything worked: in the case of one fragment, among 19 commercial analogs purchased, the best was only 7-fold better. The crystal structure of this initial fragment bound to MTH1 was eventually solved, revealing that it bound in a different manner than predicted, thus explaining the modest results. In another case the most interesting commercial analogs turned out not to be available after all, but during the course of the study a different research group published a low nanomolar inhibitor with the same scaffold.

One notable aspect of this work is going from fragments to more potent leads without using experimentally determined structural information, something the majority of respondents in our poll earlier this year said they would not attempt. Although such advancement is not unprecedented, published examples are still rare.

In some ways this work is similar to the Fragment Network approach we highlighted last month, the key difference being that while Fragment Network was focused on looking for other fragments, this is focused on finding larger molecules. But how general is it? The researchers found that, while there are a median of just 3 commercial analogs in which a fragment is an exact substructure of a larger molecule, this increases to 700 when the criterion is relaxed to similarity (for example compound 1 and 1a). These numbers undoubtedly become even more favorable for organizations with large internal screening decks.

Eight years ago I ended a post about another successful computational screen with the statement that “the computational tools are ready, as long as they are applied to appropriate systems.” This new paper demonstrates that the tools have continued to improve. I expect we will see computational fragment finding and optimization methods move increasingly to the fore.

09 October 2017

Fragments vs ketohexokinase (KHK) deliver a chemical probe

Anyone who has paid any attention to health news will be aware of concerns over high fructose corn syrup. Just a few years ago the stuff was ubiquitous. Today, due to consumer backlash, it is less common, though still widely used as a cheap sweetener in foods and beverages.

In humans fructose metabolism, unlike glucose metabolism, is not regulated by feedback inhibition, so the sugar is metabolized preferentially. Overconsumption of fructose has been correlated with all sorts of metabolic disorders, from insulin resistance to obesity. But even if you avoid consuming any fructose, your body can still convert glucose into fructose.

The rate-determining step in fructose metabolism is the enzyme ketohexokinase (KHK). Mice lacking this enzyme are healthy and resistant to metabolic diseases. Could a pill do the same thing? Although previous KHK inhibitors have been reported – one starting from fragments discussed here – these did not seem suitable for in vivo studies, not least because they are considerably less potent on rat KHK than human KHK. In a recent J. Med. Chem. paper, Kim Huard and her colleagues at Pfizer describe a chemical probe for KHK.

The researchers used STD NMR to screen their 2592-fragment library in pools of 4 or 10 compounds, with each at 240 µM. This resulted in a formidable 451 hits, of which 448 were screened in full dose response curves using SPR. Of these, 179 confirmed, and 114 had affinities better than 100 µM. All of the SPR-validated hits were tested in an enzymatic assay, leading to 23 fragments with IC50 values from 46 to 439 µM. All 23 of these were soaked into crystals of KHK, and all of them yielded structures showing them bound in the ATP-binding pocket. (Incidentally, this is a lovely example of a successful screening cascade using multiple orthogonal methods, though it would be interesting to know what the outcome would have been had the researchers jumped directly to the X-ray screen.)

But what do you do with 23 fragment hits, all with decent ligand efficiencies and experimentally determined binding modes? Rather than focusing on a single fragment, the researchers noticed that many shared common features, for instance a central heterocycle surrounded by various lipophilic substituents, as in compounds 4 and 5. Many, such as compound 4, also contained a nitrile that made a hydrogen bond to a conserved water molecule.

Next, the researchers combed the full Pfizer screening library for compounds that merged common elements of the fragment hits. This led to more potent inhibitors, such as compound 9 (which was present in the library as a racemate – make sure to vote in the poll on the right!). Parallel chemistry around analogs of this and another hit led to compound 12. In contrast to previously reported molecules, this compound is equipotent on rat and human KHK. It also has decent pharmacokinetics, is orally bioavailable, and is quite selective against a broad panel of off-targets. Rat experiments revealed that the compound inhibits fructose metabolism in vivo.

This story is a nice illustration of how lots of different crystal structures can enable fragment merging. There is still some way to go – the potency in particular could be improved. Also, there are actually two human isoforms of KHK, and compound 12 hits both equally – which may or may not be desirable. Nonetheless, this chemical probe should help further elucidate KHK biology, and help to address whether the enzyme is druggable, or merely ligandable.

02 October 2017

Dynamic combinatorial chemistry revisited: why it’s so difficult

Last year we discussed the application of dynamic combinatorial chemistry (DCC) to fragment linking. The idea is that a protein will shift the equilibrium of a reversible reaction, selecting the tightest binder. Over the past twenty years practitioners of DCC have generated plenty of papers, some quite nice, but I do not recall seeing examples of the technique generating novel and attractive chemical leads. A new paper in Chem. Eur. J. by Beat Ernst and colleagues at the University of Basel explains why it is so difficult.

The researchers were interested in the bacterial protein FimH, which helps microbes colonize the urinary tract by adhering to human proteins that are decorated with mannose. The chemistry the researchers decided to explore for DCC was the reaction of aldehydes with hydrazides to form acylhydrazones. This reaction is slowly reversible at pH 7, allowing exchange between library members to occur, but it can be essentially frozen by raising the pH.

To try to understand every aspect of their system, the researchers focused on a tiny library. Two aldehydes were chosen, one based on mannose, the other based on glucose. Four (quite similar) commercially available hydrazides were purchased.

The researchers made and tested the affinity of each of the eight possible library members using surface plasmon resonance (SPR). The four acylhydrazones based on mannose had dissociation constants (KD) ranging from 0.33 to 0.76 µM, while the mannose aldehyde came in at 3.2 µM. In contrast, the four acylhydrazones based on glucose had KD values between 152 and 735 µM, comparable to the glucose aldehyde itself (194 µM). Since mannose is the natural ligand for FimH while glucose is not, this was expected.

One challenge of DCC is separating library members from the protein for analysis; releasing bound ligands can be particularly challenging if they bind tightly to the protein. A variety of methods were tested, including microfiltration, but this gave “massive alterations in composition.” Various attempts at protein denaturation and precipitation using organic solvents or heat also failed. The fact that this step was so difficult, even for closely related ligands (the difference between mannose and glucose is the stereochemistry around a single hydroxyl group) underscores the challenge of analyzing DCC mixtures.

The problem was finally solved by using a biotinylated version of FimH which could be captured using commercial streptavidin agarose beads.

The most general approach works as follows.

1. Incubate 100 µM FimH protein with library (with each aldehyde and hydrazide at 50-200 µM) at pH 7 for 3 days in the presence of 10 mM aniline, which catalyzes the acylhydrazone exchange.

2. Raise the pH to 8.5 to stop the reaction, add streptavidin agarose, centrifuge, and discard the supernatant containing the unbound molecules.

3. Resuspend the agarose beads containing the protein, add a competitor to release bound ligands, increase the pH to 12 to ensure release, and analyze the product ratios using HPLC.

Although cumbersome, this protocol does work: mannose-derived compounds were enriched relative to glucose-derived compounds, as expected due to their higher affinities, and the most potent compound was enriched over the less potent ones. That said, the robustness of the results were dependent on the ratios of library components.

So will DCC ever be practical? I’m not so sure. But, as the researchers end hopefully but not hypefully, their work “is a contribution to this challenge.”