Ulrich Schieborr

Molecular Mechanism of SSR128129E, an Extracellularly Acting, Small-Molecule, Allosteric Inhibitor of FGF Receptor Signaling

The fibroblast growth factor (FGF)/fibroblast growth factor receptor (FGFR) signaling network plays an important role in cell growth, survival, differentiation, and angiogenesis. Deregulation of FGFR signaling can lead to cancer development. Here, we report an FGFR inhibitor, SSR128129E (SSR), that binds to the extracellular part of the receptor. SSR does not compete with FGF for binding to FGFR but inhibits FGF-induced signaling linked to FGFR internalization in an allosteric manner, as shown by crystallography studies, nuclear magnetic resonance, Fourier transform infrared spectroscopy, molecular dynamics simulations, free energy calculations, structure-activity relationship analysis, and FGFR mutagenesis. Overall, SSR is a small molecule allosteric inhibitor of FGF/FGFR signaling, acting via binding to the extracellular part of the FGFR.

NMR backbone assignment of a protein kinase catalytic domain by a combination of several approaches: application to the catalytic subunit of cAMP-dependent protein kinase.

Protein phosphorylation is one of the most important mechanisms used for intracellular regulation in eukaryotic cells. Currently, one of the best‐characterized protein kinases is the catalytic subunit of cAMP‐dependent protein kinase or protein kinase A (PKA). PKA has the typical bilobular structure of kinases, with the active site consisting of a cleft between the two structural lobes. For full kinase activity, the catalytic subunit has to be phosphorylated. The catalytic subunit of PKA has two main phosphorylation sites: Thr197 and Ser338. Binding of ATP or inhibitors to the ATP site induces large structural changes. Here we describe the partial backbone assignment of the PKA catalytic domain by NMR spectroscopy, which represents the first NMR assignment of any protein kinase catalytic domain. Backbone resonance assignment for the 42 kDa protein was accomplished by an approach employing 1) triply (2H,13C,15N) labeled protein and classical NMR assignment experiments, 2) back‐calculation of chemical shifts from known X‐ray structures, 3) use of paramagnetic adenosine derivatives as spin‐labels, and 4) selective amino acid labeling. Interpretation of chemical‐shift perturbations allowed mapping of the interaction surface with the protein kinase inhibitor H7. Furthermore, structural conformational changes were observed by comparison of backbone amide shifts obtained by 2D 1H,15N TROSY of an inactive Thr197Ala mutant with the wild‐type enzyme.

How Much NMR Data Is Required To Determine a Protein–Ligand Complex Structure?

Here we present an NMR‐based approach to solving protein–ligand structures. The procedure is guided by biophysical, biochemical, or knowledge‐based data. The structures are mainly derived from ligand‐induced chemical‐shift perturbations (CSP) induced in the resonances of the protein and ligand‐detected saturated transfer difference signals between ligands and selectively labeled proteins (SOS‐NMR). Accuracy, as judged by comparison with X‐ray results, depends on the nature and completeness of the experimental data. An experimental protocol is proposed that starts with calculations that make use of readily available chemical‐shift perturbations as experimental constraints. If necessary, more sophisticated experimental results have to be added to improve the accuracy of the protein–ligand complex structure. The criteria for evaluation and selection of meaningful complex structures are discussed. These are exemplified for three complexes, and we show that the approach bridges the gap between theoretical docking approaches and complex NMR schemes for determining protein–ligand complexes; especially for relatively weak binders that do not lead to intermolecular NOEs.

Influence of Heparin Mimetics on Assembly of the FGF-FGFR4 Signaling Complex

Fibroblast growth factor (FGF) signaling regulates mammalian development and metabolism, and its dysregulation is implicated in many inherited and acquired diseases, including cancer. Heparan sulfate glycosaminoglycans (HSGAGs) are essential for FGF signaling as they promote FGF·FGF receptor (FGFR) binding and dimerization. Using novel organic synthesis protocols to prepare homogeneously sulfated heparin mimetics (HM), including hexasaccharide (HM6), octasaccharide (HM8), and decasaccharide (HM10), we tested the ability of these HM to support FGF1 and FGF2 signaling through FGFR4. Biological assays show that both HM8 and HM10 are significantly more potent than HM6 in promoting FGF2-mediated FGFR4 signaling. In contrast, all three HM have comparable activity in promoting FGF1·FGFR4 signaling. To understand the molecular basis for these differential activities in FGF1/2·FGFR4 signaling, we used NMR spectroscopy, isothermal titration calorimetry, and size-exclusion chromatography to characterize binding interactions of FGF1/2 with the isolated Ig-domain 2 (D2) of FGFR4 in the presence of HM, and binary interactions of FGFs and D2 with HM. Our data confirm the existence of both a secondary FGF1·FGFR4 interaction site and a direct FGFR4·FGFR4 interaction site thus supporting the formation of the symmetric mode of FGF·FGFR dimerization in solution. Moreover, our results show that the observed higher activity of HM8 relative to HM6 in stimulating FGF2·FGFR4 signaling correlates with the higher affinity of HM8 to bind and dimerize FGF2. Notably FGF2·HM8 exhibits pronounced positive binding cooperativity. Based on our findings we propose a refined symmetric FGF·FGFR dimerization model, which incorporates the differential ability of HM to dimerize FGFs.

Structure and Biophysical Characterization of the S-adenosylmethionine Dependent O-methyltransferase PaMTH1, a Putative Enzyme Accumulating during Senescence of Podospora anserina

Background: PaMTH1, a putative O-methyltransferase protects Podospora anserina from oxidative stress during senescence and acts as a longevity assurance factor. Results: Crystal structures of PaMTH1/PaMTH1-SAM/SAH co-complexes and NMR-based characterization of enzymatic methylation of its substrate were obtained. Conclusion: PaMTH1 catalyzes methyl group transfer from the co-factor to the substrate in a cation-dependent manner. Significance: This work facilitates the identification of endogenous polyphenolic compounds directly involved in metal-induced oxidative stress. Low levels of reactive oxygen species (ROS) act as important signaling molecules, but in excess they can damage biomolecules. ROS regulation is therefore of key importance. Several polyphenols in general and flavonoids in particular have the potential to generate hydroxyl radicals, the most hazardous among all ROS. However, the generation of a hydroxyl radical and subsequent ROS formation can be prevented by methylation of the hydroxyl group of the flavonoids. O-Methylation is performed by O-methyltransferases, members of the S-adenosyl-l-methionine (SAM)-dependent O-methyltransferase superfamily involved in the secondary metabolism of many species across all kingdoms. In the filamentous fungus Podospora anserina, a well established aging model, the O-methyltransferase (PaMTH1) was reported to accumulate in total and mitochondrial protein extracts during aging. In vitro functional studies revealed flavonoids and in particular myricetin as its potential substrate. The molecular architecture of PaMTH1 and the mechanism of the methyl transfer reaction remain unknown. Here, we report the crystal structures of PaMTH1 apoenzyme, PaMTH1-SAM (co-factor), and PaMTH1-S-adenosyl homocysteine (by-product) co-complexes refined to 2.0, 1.9, and 1.9 Å, respectively. PaMTH1 forms a tight dimer through swapping of the N termini. Each monomer adopts the Rossmann fold typical for many SAM-binding methyltransferases. Structural comparisons between different O-methyltransferases reveal a strikingly similar co-factor binding pocket but differences in the substrate binding pocket, indicating specific molecular determinants required for substrate selection. Furthermore, using NMR, mass spectrometry, and site-directed active site mutagenesis, we show that PaMTH1 catalyzes the transfer of the methyl group from SAM to one hydroxyl group of the myricetin in a cation-dependent manner.

Folding and activity of cAMP-dependent protein kinase mutants

The catalytic subunit of cAMP‐dependent protein kinase (PKA) can easily be expressed in Escherichia coli and is catalytically active. Four phosphorylation sites are known in PKA (S10, S139, T197 and S338), and the isolated recombinant protein is a mixture of different phosphorylated forms. Obtaining uniformly phosphorylated protein requires separation of the protein preparation leading to significant loss in protein yield. It is found that the mutant S10A/S139D/S338D has similar properties as the wild‐type protein, whereas additional replacement of T197 with either E or D reduces protein expression yield as well as folding propensity of the protein. Due to its high sequence homology to Akt/PKB, which cannot easily be expressed in E. coli, PKA has been used as a surrogate kinase for drug design. Several mutations within the ATP binding site have been described to make PKA even more similar to Akt/PKB. Two proteins with Akt/PKB‐like mutations in the ATP binding site were made (PKAB6 and PKAB8), and in addition S10, S139 and S338 phosphorylation sites have been removed. These proteins can be expressed in high yields but have reduced activity compared to the wild‐type. Proper folding of all proteins was analyzed by 2D 1H, 15N‐TROSY NMR experiments.

Bias-free separation of internal and overall motion of biomolecules.

Collective internal motions are known to be important for the function of biological macromolecules. It has been discussed in the past whether the application of superimposing algorithms to remove the overall motion from a structural ensemble introduces artificial correlations between distant atoms. Here we present a new method to eliminate residual rotation and translation from cartesian modes derived from a normal mode analysis or from a principal component analysis. Bias‐free separation is based on the idea that the addition of modes of pure rotation/translation can compensate the residual overall motion. Removal of overall motion must reduce the “total amount of motion” (TAM) in the mode. Our algorithm allows to back‐calculate revised covariance matrices. The approach was applied to two model systems that show residual overall motion, when analyzed using all atoms as reference for the superimposing algorithm. In both cases, our algorithm was capable of eliminating residual covariances caused by the overall motion, while retaining internal covariances even for very distant atoms. A structural ensemble obtained for a 13‐ns molecular dynamics simulation of the protein Ribonuclease T1 showed a covariance matrix of the corrected modes with significantly sharper contours after applying the bias‐free separation. Proteins 2001;45:207–218.

1H, 13C and 15N assignment of D2 domain of human fibroblast growth factor receptor 4

Fibroblast growth factor receptor (FGFR) 4 has been associated with progression of melanoma, breast, head and neck and hepatocellular carcinoma and is therefore an interesting target for therapeutic intervention (Ho et al. in J Hepatol 50:118–127, 2009). The extracellular D2 domain of the FGFR4 receptor contains a heparin binding site and the main interaction site with the fibroblast growth factor. We report the sequential backbone and side chain resonance assignment of the D2 domain of human FGFR4.

High-resolution crystal structure of cAMP-dependent protein kinase from Cricetulus griseus.

Protein kinases (PKs) are dynamic regulators of numerous cellular processes. Their phosphorylation activity is determined by the conserved kinase core structure, which is maintained by the interaction and dynamics with associated domains or interacting proteins. The prototype enzyme for investigations to understand the activity and regulation of PKs is the catalytic subunit of cAMP-dependent protein kinase (PKAc). Major effects of functional regulation and ligand binding are driven by only minor structural modulations in protein-protein interactions. In order to resolve such minor structural differences, very high resolution structures are required. Here, the high-resolution X-ray structure of PKAc from Cricetulus griseus is reported.

MOTOR: Model assisted software for NMR structure determination

Eukaryotic proteins with important biological function can be partially unstructured, conformational flexible, or heterogenic. Crystallization trials often fail for such proteins. In NMR spectroscopy, parts of the polypeptide chain undergoing dynamics in unfavorable time regimes cannot be observed. De novo NMR structure determination is seriously hampered when missing signals lead to an incomplete chemical shift assignment resulting in an information content of the NOE data insufficient to determine the structure ab initio. We developed a new protein structure determination strategy for such cases based on a novel NOE assignment strategy utilizing a number of model structures but no explicit reference structure as it is used for bootstrapping like algorithms. The software distinguishes in detail between consistent and mutually exclusive pairs of possible NOE assignments on the basis of different precision levels of measured chemical shifts searching for a set of maximum number of consistent NOE assignments in agreement with 3D space. Validation of the method using the structure of the low molecular‐weight‐protein tyrosine phosphatase A (MptpA) showed robust results utilizing protein structures with 30–45% sequence identity and 70% of the chemical shift assignments. About 60% of the resonance assignments are sufficient to identify those structural models with highest conformational similarity to the real structure. The software was benchmarked by de novo solution structures of fibroblast growth factor 21 (FGF21) and the extracellular fibroblast growth factor receptor domain FGFR4 D2, which both failed in crystallization trials and in classical NMR structure determination. Proteins 2013; 81:2007–2022.