Fragments vs lectins - allosterically

Carbohydrates are ubiquitous in nature but largely ignored in drug discovery. This is because interactions between carbohydrates and proteins, while important, tend to be quite weak; sugar binding sites in proteins rarely have deep, ligandable binding pockets. The few case studies we’ve highlighted (here, here, and here) have resulted in weak and/or large ligands.

However, you don’t need to target the active site to inhibit a protein: one of the most advanced fragment-derived drugs in the clinic is an allosteric inhibitor. Recognizing that many proteins contain secondary (and potentially allosteric) binding sites, Marc Nazaré (Leibniz Forschungsinstitut für Molekulare Pharmakologie), Christoph Rademacher (Max Planck Institute) and collaborators at Freie Universität Berlin and Berlin Institute of Health set out to find some, as they report in a recent paper in J. Am. Chem. Soc.

The researchers were interested in the protein langerin, a C-type lectin receptor involved in pathogen recognition. They screened the extracellular domain against a total of 871 fragments using a combination of NMR methods: STD, T₂-filtered, and ¹⁹F NMR. A total of 78 fragments confirmed in at least two of these assays, of which 53 also confirmed by SPR. Three of these fragments inhibited the binding interaction between langerin and the polysaccharide mannan.

Next, the researchers acquired or synthesized more than a hundred derivatives of the active fragments and tested them in their battery of assays. Throughout the process they were careful to look for and exclude compounds that showed bad behavior such as aggregation or instability.

Ultimately, the best compounds showed triple-digit micromolar affinity by SPR and double-digit micromolar inhibition in the mannan-binding assay. Interestingly, these compounds do appear to be allosteric: they reduce the affinity of langerin towards mannan but don’t appear to directly block binding. Moreover, two-dimensional (HSQC) NMR studies suggest that the compounds bind to a different binding site on the protein than the carbohydrate does.

Of course there is still a long way to go: the compounds are far too weak to be useful chemical probes at this point. Still, this is a nice tour-de-force of biophysics. And perhaps – as we’ve seen before – someone else will be able to improve the potency of these molecules.

Fragment Ontology

We here at Practical Fragments look for papers in the literature about fragments.  Typically, it is a Web of Science search, or I see something come in an alert that has "fragment" in the title.  Well, not everything with fragment in the title is not really about fragments as we typically think of them. So, I recently came across this paper titled : "Genetically Encoded Fragment-Based Discovery of Glycopeptide Ligands for Carbohydrate-Binding Proteins".  I decided to give the paper a good perusal, largely because one of the authors is from where I did my post-doc.

The authors are interested in making competitive inhibitors of carbohydrate recognition domains for the treatment of a variety of diseases.  The challenge with lectin inhibitors is that the native carbohydrate has relatively low affinity and are synthetically complex.  As you would think, you can use the carbohydrate for binding specificity and then add something more "drug-like" to increase affinity through other interactions.  This approach has been successful but require complex multistep syntheses.  In this paper, they decided to search for peptides which can synergize with carbohydrates rather than serving solely as a linker or standalone recognition element.  To do this, and increase throughput they used a genetically encoded library, phage display.  In short, they created a glycopeptide library of 10^8  molecules through derivatization of a peptide library with carbohydrate.  This approach allows the addition of different carbohydrates (targeting different lectins) with the same peptide library.  

Figure 1.  Library Screening Approach for Genetically Encoded Glycopeptide Libraries.

In this approach, the first library (Man-X7) is screened against the target and anti-target.  The second library (methyl-X7) and the third library (Ser-X7) are screened only against the target.  After the first round of panning, they identified a weak consensus of Man-[WYF]Y[SDEA].  These peptides were made and able to compete with ConA for ligand in SPR, the mannose was shown to be essential to activity, the specific peptide sequence was required for synergistic binding.  Further work showed that the final four residues of the peptide contributed minimally to binding, so they lopped them off.  

They then performed two more rounds of panning with Man-WY[D/E]-X7.  All of the hits from these rounds had single digit micromolar affinity and the glycan-proximal ligands are responsible for most of the affinity.  How did they know if this is actuallly binding to where they want it to?

Figure 2.  Man-WYD co-crystalllized with ConA. 

Figure 2. shows the crystal structure of Man-WYD.  The mannose moiety binds where it is expected.  However, the peptide is not binding in the remainder of the trisachharide binding site, but instead in a somewhat deeper cavity near Y12.  Additionally, a latent hydrophobic site is opened up through induced fit (asterisk), filled by the Y residue of the glycopeptide.  

This approach led to the discovery of a novel class of compounds which would not have been discoverable by "standard" approaches.  But, is this fragments?  In my eyes, fragments takes simple compounds and screen them against the target.  It then optimizes the actives as quickly as possible and does iterations.  A key component to FBDD is SBDD and identification of how the actives/hits bind.  To me, this approach adheres to all the tenets of FBDD.  We have seen super huge screening molecules before, so that should not be an issue. As I have said, FBDD is about small little things being screened effectively.  I think this paper shows it is more about how you think about your system. 

The First Protein-Carbohydrate Interaction Inhibitor

Immunomodulation is all the rage, particularly in terms of cancer.  Hyaluronan (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.