Docking covalent fragments

Most drugs interact non-covalently with their target. The conventional wisdom was that covalent drugs – especially irreversible ones – would have dangerous side effects. Although this is still a concern, the success of drugs such as ibrutinib and dimethyl fumarate has caused a resurgence of interest. In a new paper in Nature Chemical Biology, Brian Shoichet, Jack Taunton, and colleagues at the University of California San Francisco describe how computational chemistry can be used to find new covalent inhibitors.

The researchers created a modified version of the program DOCK called – wait for it – DOCKovalent. Happily, they have made this available for free to anyone. To start, you upload your crystal structure and choose which amino acid residue you are interested in targeting. You can then pick from 9 different libraries of various electrophiles, each covering a different class of covalent “warhead”: epoxides, aldehydes, etc. There are about 650,000 molecules in total, roughly half of which easily qualify as fragments, with the rest being lead-like (still < 350 Da). Each molecule is either commercially available or readily synthesized in one or two steps.

The program then virtually links each molecule with the selected protein residue (typically cysteine or serine) and calculates scores based on predicted van der Waals and electrostatic interactions as well as desolvation. Multiple conformations of each ligand are sampled (with fragments there are not that many) as are different rotamers of the nucleophile. Users then manually inspect and test the top hits.

The researchers first benchmarked the program against four proteins with known covalent inhibitors, where it performed well. In the case of the bacterial protein AmpC β-lactamase (which we previously discussed here), the program retrospectively predicted the correct structure of 15 out of 23 known boronic acid ligands. In one case where the prediction differed from the reported co-crystal structure, the researchers re-determined the co-crystal structure at high resolution and found that DOCKovalent was actually correct.

Thus confident, the researchers docked 23,000 commercial boronic acids against AmpC and selected 6 on the basis of score and structural novelty. Of these, 5 had inhibition constants of 3.55 µM or better, with the best being 40 nM. A crystal structure of this compound bound to the protein led them to purchase 7 additional compounds, one of which had K_i = 10 nM and a ligand efficiency of 0.73 kcal/mol/atom. Most of the molecules were also selective against 4 other proteases and were able to reverse antibiotic resistance in AmpC-expressing bacteria.

Of course, by design all of these molecules have a boronic acid warhead; will any such molecule inhibit this enzyme? To find out, the researchers tested 5 low-scoring molecules and found that 4 of them showed, as hoped, less than 10% inhibition at 10 µM. However, a fifth molecule showed reasonable inhibition, with Ki = 3.2 µM. To understand this false-negative, the team solved the crystal structure of the molecule bound to AmpC. Interestingly, the molecule bound in a conformation different than had been predicted – one that also required conformational changes in the protein, which are not allowed in DOCKovalent.

The researchers took a similar approach to seek novel inhibitors of the kinases RSK2 and MSK1 using reversible cyanoacrylamide-containing molecules (previously highlighted here). Here too the researchers were able to identify selective nanomolar cell-active inhibitors.

This looks like a very nice approach. Of course, it does require a crystal structure (or at least a good model). Also, as mentioned above, the fact that the protein is kept rigid means the program will be unable to detect ligands that bind to cryptic pockets, so there is still plenty of opportunity for empirical surprises. Still, the fact that DOCKovalent is freely available will hopefully encourage people to give it a try on their favorite protein.

Deconstruction, superadditivity, and selectivity

One of the more exciting phenomena in fragment-based approaches is synergy (or superadditivity), in which the binding energy of linked fragments is greater than the sum of the binding energies of the individual fragments. Extreme cases are relatively rare, and the underlying thermodynamics can be counterintuitive, so it is always fun to see new examples. Cosimo Altomare and collaborators at the University of Bari and Consiglio Nazionale delle Ricerche (Italy) describe one in a recent paper in J. Med. Chem.

The proteases factor Xa (fXa) and thrombin (fIIa) are two heavily-studied anticoagulant targets. The paper characterizes a previously described molecule (compound 3) that is selective for fXa but still potent against fIIa, leading to good anticoagulant activity in human plasma as well as profibrinolytic activity. The researchers took a fragment deconstruction approach to better understand the binding to both targets.

As seen previously for fXa, the chlorothiophene moiety (red) is essential for binding, and removing it (compound 14) obliterates any detectable activity on both enzymes. However, while removing the glucose moiety (green) to give compound 1 reduced affinity for fXa by less than ten-fold, it reduced affinity for fIIa by more than two orders of magnitude. In contrast, removing the piperidine moiety (blue) to give compound 6a reduced affinity to both enzymes by several orders of magnitude.

However, these results are context-dependent. Removing both the piperidine moiety and the glucose moiety gives compound 4a, which has similar activity against fIIa as compounds 1 and 6a, where only a single moiety has been removed. In fact, compound 4a (without the glucose) is actually slightly more potent than compound 6a (with the glucose) against fIIa. But, as mentioned above, adding the glucose to compound 1 gives an impressive 110-fold boost in affinity for fIIa. In comparison, a famous early example of cooperativity in an NMR by SAR study gave only a 14-fold boost.

The researchers solved the crystal structure of compound 3 bound to fIIa, which reveals several hydrogen bond interactions between the glucose moiety and amino acid residues that have been previously implicated in allosteric activation of the protein. Perhaps compound 3 is exploiting this allosteric mechanism to bind more tightly.

This is a careful, thorough study and serves as a useful reminder that cooperativity can be huge, but it is still difficult to explain, much less predict.

Pleasant Surprise

Epigenetics is big.  Wicked big.  How big?  This big.  Papers come from everywhere.  In this paper, an academic group from Minnesota, goes after SIRT2 with fragments.  SIRT2 is a type III HDAC that resides primarily in the cytoplasm that uses NAD+ as a co-factor (Figure 1).

Figure 1.  Biochemical Reaction of SIRT2

Sirtuins (there are seven) have a long history aready in pharma.  SIRT2 has been fingered as a potential treatment for Parkinson's Disease (PD) and other pathologies, including bacterial infection.  There are a nice range of available inhibitors for SIRT2.

Figure 2.  Known Sirtuin2 Inhibitors

Suramin, a drug originally made in 1916.  I think it was made by pouring hot sulfuric acid over naptha tar (but my chemistry may be off).  Of course, when I saw this I got my dander up and got ready both barrels.  [It also made me chuckle, because many moons ago I co-authored a paper on suramin against RANK-RANKL.  In that paper suramin blocked a PPI.]  In this paper suramin is highly selective for SIRT1 over SIRT2 and 3.  So, as my wife says, your mind is like a parachute, it only works when open.  So, let see what they did.

One of the known inhibitors is

First, they evaluated a SIRT5-suramin crystal structure, where suramin mainly occupies the peptide binding site and a sulfonate protrudes into the nicontinamide binding site.  With this, they came up with the following generic plan (Figure 3). In this case, the circled napthalene is close to the  nicotinamide binding site.  They proposed to merge/link nicotinamide compounds to the appropriate suramin-like moiety. 

Figure 3.  Merging Strategy for SIRT2 Inhibitors

So, my quibble, and its not a big one, but their molecules are big (20 heavy atoms or more).  Oh well, a fragment is in the eye of the beholder.  Dan would call this FADD maybe.  Well, how did they do, you ask?  Well, they were able to generate sub-micromolar compounds (64 being the best) (50 nM![edited]), with selectivity against SIRT1 and 3.  The MOA was competitive vs. substrate and noncompetitive vs. NAD+ (although they could not rule out uncompetitive).  It had low cytotoxicity.  YAY.  Yet, it only had moderate anti-cancer activtity.  Well, those two outcomes could still allow it to be a good PD compound.  But their data indicated that it would have a low probability for crossing the BBB. 

So, in the end, I was pleasantly surprised.  This ended up being nice work with a good breadth of work.  I don't know if this makes it into the "lead-like" space or will remain in the "tool" space, but I like to see this kind of work, especially from academic groups. 

Plenty of room at the bottom (of chemical space)

One of the key selling points of fragment-based lead discovery is that small fragments can search chemical space much more efficiently than larger compounds, since there are fewer possibilites. Nonetheless, the numbers are still daunting: more than 166 billion molecules with up to 17 non-hydrogen atoms. The question of how many of these are commercially available has come up before. In a paper just published online in Prog. Biophys. Mol. Biol., Chris Murray and colleagues at Astex take a new look at this – and related – questions.

Rather than considering all possible molecules, the researchers focused on six-membered rings with one or two small substituents of no more than six non-hydrogen atoms. Six-membered rings are found in many drugs, so this is a useful area of chemical space on which to focus. The researchers first considered “topologies,” simple two-dimensional representations of molecules. In the coarsest version, benzene, cyclohexane, pyridine, and piperidine would all have identical topologies: a six-membered ring with no substituents.

The researchers looked at how many topologies having up to 16 atoms were listed in the available chemicals directory (ACD) of 2.7 million commercial molecules. Even using the coarse definition where all non-hydrogen atoms were considered equivalent, less than half of 16-atom topologies are commercially available. At finer resolution (for example, differentiating carbon from nitrogen), the numbers dropped even more: less than 4% of the 2223 16-atom topologies with a pyridazine core were available.

However, things get better the smaller the molecule. When considering only molecules with 11 non-hydrogen atoms, all of the coarsest topologies are available, as are more than 70% of pyridazines. From this, the researchers concluded:

We need to focus on fragments with lower heavy atom counts and… improve the sensitivity of our screening methods to make sure that we can identify the binding of these smaller fragments.

The rest of the paper discusses how they applied this approach, and what lessons they learned.

The researchers assert that X-ray crystallography (upon which Astex was founded) is the most sensitive screening method. That may elicit some debate, but is defensible given the presence of extremely weak binders (water, buffer components, detergents) in many crystal structures. They also argue that while NMR may allow detection of fragments with lower solubilities, this may not be a good thing.

Of the 1633 fragments that were in the Astex library between 2001 and 2007, 22% came up as X-ray hits (ie, they showed up in at least one crystal structure). Strikingly, fragments with 11 or 12 atoms were enriched far above their representation in the overall library, while fragments with 17 or more atoms were underrepresented. This is a beautiful confirmation of the “molecular complexity” hypothesis, the idea that there is a sweet spot where molecules are large enough to make productive interactions with a target but not so complex that negative interactions become dominant.

These results led the researchers to redesign their library to focus on fragments having fewer than 17 non-hydrogen atoms, which entailed considerable custom synthesis. The resulting library has 1371 fragments, of which 47% have shown up as X-ray hits. The average size of hits is the same as that of the overall library (12.2 vs 12.4 non-hydrogen atoms and 172 vs 176 Da, respectively), though the hits are slightly more lipophilic (cLogP = 1.1 vs 0.9).

What about “three-dimensionality?” This is a topic that has been discussed quite a lot (here, here, here, here, and here, for starters), so it is nice to have some solid data. One problem is how to define three-dimensionality: simple metrics such as Fsp³ don’t account for the fact that aromatic compounds such as 2,6-substituted biphenyls can be very non-planar. Many people use PMI, but the Astex researchers chose deviation from planarity (DFP). This method puts a hypothetical plane through the molecule that minimizes the deviation of all non-hydrogen atoms from the plane; the average deviation from the plane for each molecule is calculated in Ångstroms. So, for example, benzene has DFP = 0.0 Å, while cycloleucine has DFP = 0.54 Å. In this study, the researchers used a single conformation for each molecule, but since these fragments have on average only 1.3 rotatable bonds this is probably a reasonable simplification.

Roughly 40% of the Astex library has a DFP < 0.05 Å, but these “flat” fragments were enriched to ~50% among hits. Not surprisingly, kinase hits tended to be even more two-dimensional (>60%), but even protein-protein interaction (PPI) hits were, if anything, slightly more planar than the overall collection, which is consistent with another recent study. Indeed, there seems to be nothing special at all about PPI hits, more than half of which were also found against non-PPI targets. The researchers argue that 3D-fragments are inherently more complex and thus less likely to show up as hits, which supports Teddy’s Safran Zunft challenge.

One of the arguments in favor of three-dimensionality is that such molecules may have better physicochemical properties, and the researchers examine the DFP for fragments and resulting leads. It turns out that there is a weak correlation between the shapeliness of a fragment and that of the resulting lead, but there are many exceptions (such as this one).

Some of these data have been publicly presented, but this paper should broaden the discussion. Coming back to the title of this post, the conclusion is that fragments should be made as small as detectable with your assay. And flat is the new black.

Still Impractical, but Getting Better...

Dan and I don't see every fragment paper and so it's nice when people point out papers to us.  Its typically their recently published paper and they are looking for some sort of recognition/validation from us.  Sometimes its a paper we have on our radar, sometimes it isn't.  Recently, I received an email pointing out this paper from someone I met at FBLD2014.  Well, this is a follow up paper to a paper I discussed a few years back.  The title of the post sums up my thoughts: "Another (Impractical) NMR Method."  One comment from that post (by a co-author from Astex on the current paper) was

This is a relaxation filtered ligand based method (like T1rho or selective T1). You therefore may consider using it in competition mode if you find one suitable "spy" molecule: this would allow with a single point experiment screening mixtures and/or ranking for low affinity hits(especially if solubility is limiting). I would actually give it a try.

So, it looks like she did.  The advantages of Long Lived States (LLS) NMR is that the the dynamic range is wider and it works at low protein concentrations (3 uM or roughly the same as STD or WaterLOGSY) or with very weak affinities.  Against the workhorse HSP90 system, they screened mixtures using LLS and a spy molecule.

  

I still don't think this is a very practical method because it still requires a lot of tailoring to individual systems; in particular the compounds need pairs of protons which are suitable for excitation to the LLS.  Using it in "spy" mode gets around this. I would still hold that this is an impractical NMR method.  I like to see people developing new methods and trying to improve them.  We also need people doing good comparisons of "standard" experiments to new ones.  (Here is how NOT to do a method comparison.) I won't dismiss this out of hand, but there is still a lot of work to be done here to move it into a "front line" screening technique.

Fragments as enzyme activators

About half of all approved drugs are small molecules that inhibit enzymes. This makes sense intuitively: an enzyme is like a complicated little machine, and there are lots of ways you can wreck a machine. But there are times when you might want to activate an enzyme, and this is conceptually more difficult. In a new paper in Angew. Chem. Int. Ed., Rod Hubbard and colleagues at the University of York show how fragments can help.

The researchers were interested in the enzyme O-GlcNAc hydrolase (OGA), which removes N-acetylglucosamine from proteins. They were looking for inhibitors of a bacterial version of this enzyme, so they screened it against 100 fragments using three ligand-observed NMR methods (STD NMR, PO-WaterLOGSY, and T_1ρ-filter). This resulted in a very high hit rate: 22 fragments showed binding in all three assays, and 18 of these were competitive with a known substrate-like inhibitor, PUGNAc. Some of these were also active in an enzymatic assay.

More interestingly, the four hits that were not competitive with PUGNAc actually appeared to bind more strongly to the protein in the presence of that inhibitor. In this case, the inhibitor can be considered a stand-in for the natural substrate, and the results suggested that the fragments might enhance binding of the enzyme to its substrate. Indeed, when these fragments were tested in the enzymatic assay, one of them (compound 2) actually activated the enzyme, with an “AC₅₀” value of 3.5 mM.

The activator was further characterized by several orthogonal methods. NMR revealed that, in the presence of PUGNAc, compound 2 bound with a dissociation constant of 3.1 mM, very close to its AC₅₀ value. In the absence of PUGNAc, the dissociation constant was too weak to be determined. Isothermal titration calorimetry experiments revealed that compound 2 increased the affinity of the enzyme for PUGNAc by more than three-fold, while Michaelis-Menten kinetics revealed that, at a concentration of 8 mM, compound 2 nearly doubled the k_cat/K_M. A crystal structure of both compound 2 and PUGNAc bound to the enzyme revealed that the two molecules bind near one another in what appears to be a catalytically active conformation of the protein.

Next, the researchers took an “SAR by catalog” approach to find more potent molecules, leading to compound 4, with an AC₅₀ value roughly ten-fold better than compound 2. Detailed enzymatic characterization revealed that the molecule acts as a “nonessential reversible activator,” and improves substrate binding roughly 7-fold while improving k_cat by a factor of 1.7.

Interestingly, differential scanning fluorimetry (DSF) revealed that all the activators destabilize the enzyme, while PUGNAc stabilizes the enzyme. This is yet more evidence that compounds can decrease the melting temperature of a protein while still binding specifically.

This is an academic study in the best sense of the phrase. The immediate utility of these molecules is tenuous, as they do not work with human OGA (which has some important active site differences), though there may be industrial applications. The more important finding of this rigorous paper is that discovering enzyme activators might be easier than expected. There aren’t that many reported, but this may just be because people tend not to look for them: if you find an activator of an enzyme you are trying to shut down you probably won’t pursue it. That said, a few companies have been founded on enzyme activators. Perhaps fragments can help discover more.