Fragments vs membrane proteins with SPR

Membrane proteins such as GPCRs account for something like half of all drug targets, but they present a serious challenge for fragment-based approaches. This is partly because the biophysical methods usually used for fragment screening often don’t work for membrane proteins, and partly because, in the absence of structural information, it’s hard to know what to do with fragment hits. But there is progress. We’ve highlighted a couple papers that use functional screens or TINS to find fragments against membrane proteins, and in a recent issue of Biochem. Pharmacol. U. Helena Danielson and colleagues at Beactica and two academic institutes show how surface-plasmon resonance (SPR) can also be applied.

The researchers were interested in GABA_A receptors, a class of ion channels involved in multiple physiological functions. The receptors normally form hetero-pentamers, but for simplicity the researchers used a homo-oligomeric receptor, consisting of five β3 subunits. Each β3 subunit carried a tag containing eight histidine residues that could be recognized by antibodies immobilized to the surface of the SPR chip. The GABA_A receptors were detergent-solubilized; control channels contained antibodies and detergent with no receptors. The resulting GABA_A-modified chips were quite stable; the researchers report being able to run roughly 200 samples over the course of 20 hours with a single chip. (The specific detergents and conditions are critical, so if you’re interested in pursuing this yourself the experimental section is invaluable.)

A set of 51 histaminergic and 15 GABAergic ligands were tested for binding, resulting in nearly two dozen hits with dissociation constants (K_Ds) between 13 and 300 micromolar. Some of these are exceptionally small: for example, histamine, with a molecular weight of 111 g/mol and just 8 heavy atoms showed a K_D of 98 micromolar, which is consistent with published results using different methods. A number of other ligands were also identified, some for the first time, though other previously reported ligands did not repeat in this system.

It will be fun to see the screening results of a larger, unbiased library. Of course, finding fragment hits against a membrane protein is only the first step to developing drugs – one still needs to figure out how to improve potency, most likely in the absence of structure. But, to paraphrase Churchill, at least this paper and related research represent the end of the beginning.

Paying the fee for ligand efficiency

Practical Fragments has highlighted a couple cases in which larger molecules have been deconstructed into fragments and then analyzed for binding (see for example here and here). In the most recent issue of J. Med. Chem., Peter Brandt, Matthis Geitmann, and U. Helena Danielson of Beactica have applied this strategy to inhibitors of HIV reverse transcriptase (HIV-1 RT). They also delve into the theory and energetics.

The researchers dissect three non-nucleoside reverse transcriptase inhibitors (NNRTIs) into a total of 21 commercially available “fragments”. Each of these was then tested for binding using SPR (see also this paper for a detailed account of how they perform these screens, and this one for discovery of new fragments against this target). If the binding energies of the fragments were evenly distributed across the entire parent NNTRIs, most of the fragments would be predicted to be sub-millimolar. In fact, most of them were much worse: only 9 showed any evidence at for binding, and only 3 were fragment-sized (the other six had molecular weights above 300 Da).

This sort of result – that fragments of larger molecules bind less effectively than predicted – has now been seen several times, and the researchers asked why. One issue is that when a molecule binds to a protein it loses translational and rotational entropy, and this imposes an energetic cost. This “fee” is, unfortunately, hard to estimate, and complicated by the fact that there may be further energetic costs if the protein itself is flexible (as in the case of HIV-1 RT). The authors provide a nice review of the literature, where values range from 2.5 to a whopping 16 kcal/mol (see here for more discussion on this). When they (admittedly arbitrarily) subtracted 7.0 kcal/mol, the agreement between expected and observed binding of their fragments improved.

However, as the researchers acknowledge, this model still assumes that the binding energy is equally distributed over the entire parent molecule – in other words, it ignores the existence of hot spots. The fact that hot spots exist probably accounts for the decrease in maximum observed ligand efficiency with an increase in the number of heavy atoms:

Once [the hot spot] is occupied, larger molecules need also to interact with other parts of the ligand binding pocket. Hence, a decrease in ligand efficiency will be observed for larger molecules.

True, and to complicate things even more, different proteins will have hot spots of different sizes and “temperature” – or perhaps none at all. This variation calls into question the utility of using notions such as fit quality or %LE, which attempt to normalize ligand efficiency for the size of the ligand. The problem is that different proteins are likely to have different maximal affinity ligands; kinases tend to have high-affinity binding sites where high ligand efficiency can be achieved, while for protein-protein interactions the ligand binding site is likely to be larger and the ligand efficiencies lower. Thus, one-size fits all metrics could prove too stringent – or not stringent enough.

Ligand efficiency hot spots

Hot spots are regions of a protein with a particular predilection for binding to small molecules – thermodynamic sinkholes, so to speak. Discovering one of these can get you to potent molecules very quickly. In an effort to better understand hot spots, Iwan de Esch and colleagues at VU University in Amsterdam and collaborators at Beactica have deconstructed a potent ligand for nicotinic acetylcholine binding protein (AChBP), a model protein for ligand-gated ion channels, which are implicated in a variety of neurological diseases. They report their results in a recent issue of J. Med. Chem.

The researchers started with the previously reported quinuclidine compound 6 (see figure) and fragmented this into 20 analogs. They tested these in a surface plasmon resonance (SPR) assay as well as in a more conventional radioligand binding assay; the agreement between these very different assay formats was excellent, further validating the utility of SPR as a useful tool for discovering fragments.

Not surprisingly, some of the fragments have higher ligand efficiencies than the larger, more potent molecule, suggesting that there is a hot-spot that recognizes the core fragment 25 (which is structurally related to nicotine). This concept of “group efficiency” has been described previously, and can be useful for optimizing fragments. For example, compound 22, without a basic nitrogen atom, has the lowest ligand efficiency in the bunch; presumably, simply adding the nitrogen would give a sizable boost in potency.

However, one needs to be cautious. The researchers use computer docking to develop models of how each of these fragments bind, but as we have seen before, isolated fragments do not always recapitulate the binding modes of fully elaborated molecules. Still, particularly in the absence of structure (as is the case with many ion channels), exercises such as this could provide useful ideas for what to do with fragment hits.

Surface Plasmon Resonance (SPR)

Fragment-based drug discovery took off with NMR in the 1990s and went mainstream with X-ray crystallography in the 2000s. Now surface plasmon resonance (SPR) is becoming increasingly popular as a primary means of identifying hits. The technique has been mentioned more than a dozen times on Practical Fragments, but we’ve never devoted an entire post to it until now.

This post follows up on two recent publications. The first is an excellent summary of SPR by our friends at FBDD-Lit. Peter Kenny gives an overview of the technique and reports on a workshop given by SPR mavens Dave Myszka and Rebecca Rich. He also covers some of the seminal papers in the field.

The second report is in the brand new journal ACS Medicinal Chemistry Letters. In it, Iva Navratilova and Andrew Hopkins of the University of Dundee provide practical advice on using SPR for fragment-screening.

The authors describe their work on using SPR to identify fragments that bind to carbonic anhydrase II, a popular target for proof-of-concept studies. They screened a library of 656 fragments with molecular weights between 94 to 341 Da, with an average of 187 Da, or about 13 non-hydrogen atoms. The entire screen, which was done at three concentrations (16.6, 50, and 150 micromolar) took 4 weeks from assay development to hit confirmation on a Biacore T100, and consumed a total of 27 micrograms of protein.

Importantly, Navratilova and Hopkins were keenly aware of the potential for false positives or nonspecific binders (of which there were 230 at the highest concentration!) One way they controlled for such artifacts was to include an unrelated reference protein; data could be corrected by subtracting the response to the reference protein from the response to the target protein. Another analytical method to reduce the number of false positives was to only consider compounds that exceeded a minimum threshold for ligand efficiency (a metric invented by Hopkins and co-workers), a decision justified here given the often high affinities observed for carbonic anhydrase inhibitors. After these filters, an examination of the stoichiometry of binding revealed a dozen specific binders and four non-specific binders, a hit rate of 1.8%.

My one reservation with this paper is that carbonic anhydrase is a particularly easy test case, unlikely to fairly represent many of targets that people screen. Indeed, the confirmed hits (all of which contain sulfonamides), have affinities from 0.13 to 14 micromolar – far better than a typical fragment screen, and comparable to many HTS screens. Still, the tools and analyses described should apply to more challenging targets.

Finally, it is worth noting that if you want access to SPR technology but don’t have the resources or expertise to do it yourself, at least a couple companies (Beactica and Graffinity) specialize in applying SPR to FBDD.