How can we define and analyse drug exposure more precisely to improve the prediction of hospitalizations in longitudinal (claims) data?

BACKGROUND: Risk prediction models can be powerful tools to support clinical decision-making, to help targeting interventions, and, thus, to improve clinical and economic outcomes, provided that model performance is good and sensitivity and specificity are well balanced. Drug utilization as a potential risk factor for unplanned hospitalizations has recently emerged as a meaningful predictor variable in such models. Drug treatment is a rather unstable (i.e. time-dependent) phenomenon and most drug-induced events are concentration-dependent and therefore individual drug exposure will likely modulate the risk. This especially applies to longitudinal monitoring of appropriate drug treatment within claims data as another promising application for prediction models. METHODS AND RESULTS: To guide future research towards this direction, we firstly reviewed current risk prediction models for unplanned hospitalizations that explicitly included information on drug utilization and were surprised to find that these models rarely attempted to consider dose and frequent modulators of drug clearance such as interactions with co-medication or co-morbidities. As another example, they often presumed class effects where in fact, differences between active moieties were well established. In addition, the study designs and statistical risk analysis disregarded the fact that medication and risk modulators and, thus, adverse events can vary over time. In a simulation study, we therefore evaluated the potential benefit of time-dependent Cox models over standard binary regression approaches with a fixed follow-up period. CONCLUSIONS: Longitudinal drug information could be utilized much more efficiently both by precisely estimating individual drug exposure and by applying more refined statistical methodology to account for time-dependent drug utilization patterns.

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.

Structure and Biophysical Characterization of the S-Adenosylmethionine-dependent O-Methyltransferase PaMTH1, a Putative Enzyme Accumulating during Senescence of Podospora anserina.

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.

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.

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.

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.

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 (HM(6)), octasaccharide (HM(8)), and decasaccharide (HM(10)), we tested the ability of these HM to support FGF1 and FGF2 signaling through FGFR4. Biological assays show that both HM(8) and HM(10) are significantly more potent than HM(6) 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 HM(8) relative to HM(6) in stimulating FGF2.FGFR4 signaling correlates with the higher affinity of HM(8) to bind and dimerize FGF2. Notably FGF2.HM(8) 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.

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.

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.

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 ((2)H,(13)C,(15)N) 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 (1)H,(15)N TROSY of an inactive Thr197Ala mutant with the wild-type enzyme.