Forschung

Complex glycan structures have evolved as versatile regulators of many aspects of health and disease such as in immune cell recognition, development, hormone activity, tissue organization, and metastasis. Many functions of carbohydrates in a biological context are tightly coupled to their recognition by glycan binding proteins (GBPs). Only the side-by-side analysis of the recognition process at atomic resolution and functional studies in a relevant biological environment provide means to fully elucidate a carbohydrate structure-function relationship. Therefore, we apply biophysical techniques, such as nuclear magnetic resonance (NMR) and combine the results with computational methods. Defined chemical probes are then developed to expand these investigations into characterization of the biochemical and cell biological roles of glycan/GBP interactions.

The Mission. Many naturally occurring glycans are recognized by more than one lectin. The reverse also holds true, so that the majority of lectins are not highly specific for one single complex carbohydrate structure. The origin of this ambiguity can be described by the so-called “Red Queen Effect”, a concept in evolution that explains the pressure of co-evolving components of a biological system and its consequences. Building on the existing carbohydrate scaffold by chemical modification is a route towards the development of highly specific and defined tools to study glycobiology and glycomimetic drugs.

Methods. Nuclear magnetic resonance (NMR) is an extremely versatile biophysical technique that allows for the structural elucidation of carbohydrate/GBP interactions. In the Structural Glycobiology group, we use a broad palette of techniques to foster our goal to develop probes for glycobiology on the basis of a detailed description of the recognition process (Figure 1). Moreover, NMR screening techniques are employed to expand the structural information and develop carbohydrates into specific glycan analogs (Figure 2 & 3). Virtual Screening and molecular modeling techniques complement these endeavors to yield a more comprehensive picture of the interaction.

Figure 1: (A) Transferred NOE (trNOE) experiments yield structural information on the bioactive conformation of a bound ligand. In NMR spectroscopy the nuclear Overhauser effect can be utilized to derive distance information between two spins. A series of NOESY spectra is recorded and the conformation of the ligand in the bound state can be deduced from the quantitative analysis. (B) Saturation Transfer Difference (STD) NMR delivers information on the binding epitope of a small molecule ligand interacting with its receptor. A series of selective pulses saturates the receptor during the STD experiment. Only those protons of interacting ligands are saturated that are in close proximity to the receptor interface and thereby imprint a binding epitope. The recognition interface between a ligand and its receptor is revealed and offers important information on the design of small molecules.

Figure 2: NMR screening methods are employed to identify hits from screening libraries. Large compound libraries of either drug-like or fragment-like molecules can be explored for binding events during an NMR experiment. This information can then be used to identify hits for the development of specific ligands for a given receptor protein.

Figure 3: Fragment-based ligand design. In this example, three fragments were identified from a previous screening. (A) NMR techniques such as interligand NOE (ILOE) are then utilized to explore their relative orientation in a ternary complex. (B) This information guides the rational design for a high affinity ligand.

Figure 4: Structural Bioinformatics and Molecular Modeling. Glycomimetic compounds are design using computer-aided methods.

Figure 5: Glycoinformatics. A simplified glycan annotation (Consortium for Functional Glycomics) serves as a starting point to derive a linear descriptor of highly complex glycan structures. (a) Bit strings encode the presence of certain glycan fragments and can then be used in combination with chemoinformatic tools to analyze glycan libraries. (b) This has many implications, for instance for the design and diversification of glycan microarrays. (Rademacher & Paulson, ACS Chem. Biol. 2012).