Osteoporotic fractures and subsequent fractures: imminent fracture risk from an analysis of German real-world claims data.

PURPOSE: In osteoporosis, prior fracture is a strong predictor of subsequent fracture. This study aimed to assess the imminent risk of subsequent fracture following an initial fracture in osteoporosis patients in Germany, and to identify clinical and demographic characteristics that are independently associated with subsequent fracture risk. METHODS: In this retrospective, observational cohort study using German real-world claims data, male and female patients aged ≥ 50 years with osteoporosis who experienced an initial ("index") hip/femur, vertebral, forearm/wrist/hand or shoulder/upper arm fracture between 2010 and 2014 were included. The incidence and timing of subsequent fractures during a 1-year follow-up period were analyzed. Independent risk factors for subsequent fracture were identified by multivariate regression analysis. RESULTS: A total of 18,354 patients (mean age: 77 years; standard deviation: 9.8) were included. Of these, 2918 (15.9%) suffered a subsequent fracture during the 1-year follow-up period. The incidence of subsequent fracture was higher following an index vertebral fracture (18.0%) than after an index forearm/wrist/hand fracture (14.1%) or index hip/femur fracture (12.1%). Subsequent 1-year fracture incidence was generally higher in older patients. Index fracture type, age, epilepsy/use of antiepileptics, and heart failure were all independently associated with subsequent fracture risk. CONCLUSION: Osteoporosis patients in Germany are at imminent risk of subsequent fracture during the first year following an initial fracture. They should be targeted for immediate post-fracture treatment to reduce the risk of further fractures, especially in the presence of specific risk factors such as old age or index vertebral fracture.

TMSEG: Novel prediction of transmembrane helices.

Transmembrane proteins (TMPs) are important drug targets because they are essential for signaling, regulation, and transport. Despite important breakthroughs, experimental structure determination remains challenging for TMPs. Various methods have bridged the gap by predicting transmembrane helices (TMHs), but room for improvement remains. Here, we present TMSEG, a novel method identifying TMPs and accurately predicting their TMHs and their topology. The method combines machine learning with empirical filters. Testing it on a non-redundant dataset of 41 TMPs and 285 soluble proteins, and applying strict performance measures, TMSEG outperformed the state-of-the-art in our hands. TMSEG correctly distinguished helical TMPs from other proteins with a sensitivity of 98 ± 2% and a false positive rate as low as 3 ± 1%. Individual TMHs were predicted with a precision of 87 ± 3% and recall of 84 ± 3%. Furthermore, in 63 ± 6% of helical TMPs the placement of all TMHs and their inside/outside topology was correctly predicted. There are two main features that distinguish TMSEG from other methods. First, the errors in finding all helical TMPs in an organism are significantly reduced. For example, in human this leads to 200 and 1600 fewer misclassifications compared to the second and third best method available, and 4400 fewer mistakes than by a simple hydrophobicity-based method. Second, TMSEG provides an add-on improvement for any existing method to benefit from. Proteins 2016; 84:1706-1716. © 2016 Wiley Periodicals, Inc.

Structures of aminoarabinose transferase ArnT suggest a molecular basis for lipid A glycosylation.

Polymyxins are antibiotics used in the last line of defense to combat multidrug-resistant infections by Gram-negative bacteria. Polymyxin resistance arises through charge modification of the bacterial outer membrane with the attachment of the cationic sugar 4-amino-4-deoxy-l-arabinose to lipid A, a reaction catalyzed by the integral membrane lipid-to-lipid glycosyltransferase 4-amino-4-deoxy-L-arabinose transferase (ArnT). Here, we report crystal structures of ArnT from Cupriavidus metallidurans, alone and in complex with the lipid carrier undecaprenyl phosphate, at 2.8 and 3.2 angstrom resolution, respectively. The structures show cavities for both lipidic substrates, which converge at the active site. A structural rearrangement occurs on undecaprenyl phosphate binding, which stabilizes the active site and likely allows lipid A binding. Functional mutagenesis experiments based on these structures suggest a mechanistic model for ArnT family enzymes.

Structure of the polyisoprenyl-phosphate glycosyltransferase GtrB and insights into the mechanism of catalysis.

The attachment of a sugar to a hydrophobic polyisoprenyl carrier is the first step for all extracellular glycosylation processes. The enzymes that perform these reactions, polyisoprenyl-glycosyltransferases (PI-GTs) include dolichol phosphate mannose synthase (DPMS), which generates the mannose donor for glycosylation in the endoplasmic reticulum. Here we report the 3.0 Å resolution crystal structure of GtrB, a glucose-specific PI-GT from Synechocystis, showing a tetramer in which each protomer contributes two helices to a membrane-spanning bundle. The active site is 15 Å from the membrane, raising the question of how water-soluble and membrane-embedded substrates are brought into apposition for catalysis. A conserved juxtamembrane domain harbours disease mutations, which compromised activity in GtrB in vitro and in human DPM1 tested in zebrafish. We hypothesize a role of this domain in shielding the polyisoprenyl-phosphate for transport to the active site. Our results reveal the basis of PI-GT function, and provide a potential molecular explanation for DPM1-related disease.

A draft network of ligand-receptor-mediated multicellular signalling in human.

Cell-to-cell communication across multiple cell types and tissues strictly governs proper functioning of metazoans and extensively relies on interactions between secreted ligands and cell-surface receptors. Herein, we present the first large-scale map of cell-to-cell communication between 144 human primary cell types. We reveal that most cells express tens to hundreds of ligands and receptors to create a highly connected signalling network through multiple ligand-receptor paths. We also observe extensive autocrine signalling with approximately two-thirds of partners possibly interacting on the same cell type. We find that plasma membrane and secreted proteins have the highest cell-type specificity, they are evolutionarily younger than intracellular proteins, and that most receptors had evolved before their ligands. We provide an online tool to interactively query and visualize our networks and demonstrate how this tool can reveal novel cell-to-cell interactions with the prediction that mast cells signal to monoblastic lineages via the CSF1-CSF1R interacting pair.

A Combined Omics Approach to Generate the Surface Atlas of Human Naive CD4+ T Cells during Early T-Cell Receptor Activation.

Naive CD4(+) T cells are the common precursors of multiple effector and memory T-cell subsets and possess a high plasticity in terms of differentiation potential. This stem-cell-like character is important for cell therapies aiming at regeneration of specific immunity. Cell surface proteins are crucial for recognition and response to signals mediated by other cells or environmental changes. Knowledge of cell surface proteins of human naive CD4(+) T cells and their changes during the early phase of T-cell activation is urgently needed for a guided differentiation of naive T cells and may support the selection of pluripotent cells for cell therapy. Periodate oxidation and aniline-catalyzed oxime ligation technology was applied with subsequent quantitative liquid chromatography-tandem MS to generate a data set describing the surface proteome of primary human naive CD4(+) T cells and to monitor dynamic changes during the early phase of activation. This led to the identification of 173 N-glycosylated surface proteins. To independently confirm the proteomic data set and to analyze the cell surface by an alternative technique a systematic phenotypic expression analysis of surface antigens via flow cytometry was performed. This screening expanded the previous data set, resulting in 229 surface proteins, which were expressed on naive unstimulated and activated CD4(+) T cells. Furthermore, we generated a surface expression atlas based on transcriptome data, experimental annotation, and predicted subcellular localization, and correlated the proteomics result with this transcriptional data set. This extensive surface atlas provides an overall naive CD4(+) T cell surface resource and will enable future studies aiming at a deeper understanding of mechanisms of T-cell biology allowing the identification of novel immune targets usable for the development of therapeutic treatments.

Protein structure. Structure and activity of tryptophan-rich TSPO proteins.

Translocator proteins (TSPOs) bind steroids and porphyrins, and they are implicated in many human diseases, for which they serve as biomarkers and therapeutic targets. TSPOs have tryptophan-rich sequences that are highly conserved from bacteria to mammals. Here we report crystal structures for Bacillus cereus TSPO (BcTSPO) down to 1.7 Å resolution, including a complex with the benzodiazepine-like inhibitor PK11195. We also describe BcTSPO-mediated protoporphyrin IX (PpIX) reactions, including catalytic degradation to a previously undescribed heme derivative. We used structure-inspired mutations to investigate reaction mechanisms, and we showed that TSPOs from Xenopus and man have similar PpIX-directed activities. Although TSPOs have been regarded as transporters, the catalytic activity in PpIX degradation suggests physiological importance for TSPOs in protection against oxidative stress.

Evaluation of transmembrane helix predictions in 2014.

Experimental structure determination continues to be challenging for membrane proteins. Computational prediction methods are therefore needed and widely used to supplement experimental data. Here, we re-examined the state of the art in transmembrane helix prediction based on a nonredundant dataset with 190 high-resolution structures. Analyzing 12 widely-used and well-known methods using a stringent performance measure, we largely confirmed the expected high level of performance. On the other hand, all methods performed worse for proteins that could not have been used for development. A few results stood out: First, all methods predicted proteins in eukaryotes better than those in bacteria. Second, methods worked less well for proteins with many transmembrane helices. Third, most methods correctly discriminated between soluble and transmembrane proteins. However, several older methods often mistook signal peptides for transmembrane helices. Some newer methods have overcome this shortcoming. In our hands, PolyPhobius and MEMSAT-SVM outperformed other methods.

Structure and selectivity in bestrophin ion channels.

Human bestrophin-1 (hBest1) is a calcium-activated chloride channel from the retinal pigment epithelium, where mutations are associated with vitelliform macular degeneration, or Best disease. We describe the structure of a bacterial homolog (KpBest) of hBest1 and functional characterizations of both channels. KpBest is a pentamer that forms a five-helix transmembrane pore, closed by three rings of conserved hydrophobic residues, and has a cytoplasmic cavern with a restricted exit. From electrophysiological analysis of structure-inspired mutations in KpBest and hBest1, we find a sensitive control of ion selectivity in the bestrophins, including reversal of anion/cation selectivity, and dramatic activation by mutations at the cytoplasmic exit. A homology model of hBest1 shows the locations of disease-causing mutations and suggests possible roles in regulation.

Structural basis for a pH-sensitive calcium leak across membranes.

Calcium homeostasis balances passive calcium leak and active calcium uptake. Human Bax inhibitor-1 (hBI-1) is an antiapoptotic protein that mediates a calcium leak and is representative of a highly conserved and widely distributed family, the transmembrane Bax inhibitor motif (TMBIM) proteins. Here, we present crystal structures of a bacterial homolog and characterize its calcium leak activity. The structure has a seven-transmembrane-helix fold that features two triple-helix sandwiches wrapped around a central C-terminal helix. Structures obtained in closed and open conformations are reversibly interconvertible by change of pH. A hydrogen-bonded, pKa (where Ka is the acid dissociation constant)-perturbed pair of conserved aspartate residues explains the pH dependence of this transition, and biochemical studies show that pH regulates calcium influx in proteoliposomes. Homology models for hBI-1 provide insights into TMBIM-mediated calcium leak and cytoprotective activity.

PredictProtein--an open resource for online prediction of protein structural and functional features.

PredictProtein is a meta-service for sequence analysis that has been predicting structural and functional features of proteins since 1992. Queried with a protein sequence it returns: multiple sequence alignments, predicted aspects of structure (secondary structure, solvent accessibility, transmembrane helices (TMSEG) and strands, coiled-coil regions, disulfide bonds and disordered regions) and function. The service incorporates analysis methods for the identification of functional regions (ConSurf), homology-based inference of Gene Ontology terms (metastudent), comprehensive subcellular localization prediction (LocTree3), protein-protein binding sites (ISIS2), protein-polynucleotide binding sites (SomeNA) and predictions of the effect of point mutations (non-synonymous SNPs) on protein function (SNAP2). Our goal has always been to develop a system optimized to meet the demands of experimentalists not highly experienced in bioinformatics. To this end, the PredictProtein results are presented as both text and a series of intuitive, interactive and visually appealing figures. The web server and sources are available at http://ppopen.rostlab.org.

An estimated 5% of new protein structures solved today represent a new Pfam family.

High-resolution structural knowledge is key to understanding how proteins function at the molecular level. The number of entries in the Protein Data Bank (PDB), the repository of all publicly available protein structures, continues to increase, with more than 8000 structures released in 2012 alone. The authors of this article have studied how structural coverage of the protein-sequence space has changed over time by monitoring the number of Pfam families that acquired their first representative structure each year from 1976 to 2012. Twenty years ago, for every 100 new PDB entries released, an estimated 20 Pfam families acquired their first structure. By 2012, this decreased to only about five families per 100 structures. The reasons behind the slower pace at which previously uncharacterized families are being structurally covered were investigated. It was found that although more than 50% of current Pfam families are still without a structural representative, this set is enriched in families that are small, functionally uncharacterized or rich in problem features such as intrinsically disordered and transmembrane regions. While these are important constraints, the reasons why it may not yet be time to give up the pursuit of a targeted but more comprehensive structural coverage of the protein-sequence space are discussed.

Structural genomics plucks high-hanging membrane proteins.

Recent years have seen the establishment of structural genomics centers that explicitly target integral membrane proteins. Here, we review the advances in targeting these extremely high-hanging fruits of structural biology in high-throughput mode. We observe that the experimental determination of high-resolution structures of integral membrane proteins is increasingly successful both in terms of getting structures and of covering important protein families, for example, from Pfam. Structural genomics has begun to contribute significantly toward this progress. An important component of this contribution is the set up of robotic pipelines that generate a wealth of experimental data for membrane proteins. We argue that prediction methods for the identification of membrane regions and for the comparison of membrane proteins largely suffice to meet the challenges of target selection for structural genomics of membrane proteins. In contrast, we need better methods to prioritize the most promising members in a family of closely related proteins and to annotate protein function from sequence and structure in absence of homology.

Investigating the mechanisms of photosynthetic proteins using continuum electrostatics.

Computational methods based on continuum electrostatics are widely used in theoretical biochemistry to analyze the function of proteins. Continuum electrostatic methods in combination with quantum chemical and molecular mechanical methods can help to analyze even very complex biochemical systems. In this article, applications of these methods to proteins involved in photosynthesis are reviewed. After giving a short introduction to the basic concepts of the continuum electrostatic model based on the Poisson-Boltzmann equation, we describe the application of this approach to the docking of electron transfer proteins, to the comparison of isofunctional proteins, to the tuning of absorption spectra, to the analysis of the coupling of electron and proton transfer, to the analysis of the effect of membrane potentials on the energetics of membrane proteins, and to the kinetics of charge transfer reactions. Simulations as those reviewed in this article help to analyze molecular mechanisms on the basis of the structure of the protein, guide new experiments, and provide a better and deeper understanding of protein functions.

An extended dead-end elimination algorithm to determine gap-free lists of low energy states.

Proteins are flexible systems and commonly populate several functionally important states. To understand protein function, these states and their energies have to be identified. We introduce an algorithm that allows the determination of a gap-free list of the low energy states. This algorithm is based on the dead-end elimination (DEE) theorem and is termed X-DEE (extended DEE). X-DEE is applicable to discrete systems whose state energy can be formulated as pairwise interaction between sites and their intrinsic energies. In this article, the computational performance of X-DEE is analyzed and discussed. X-DEE is implemented to determine the lowest energy protonation states of proteins, a problem to which DEE has not been applied so far. We use X-DEE to calculate a list of low energy protonation states for two bacteriorhodopsin structures that represent the first proton transfer step of the bacteriorhodopsin photocycle.

Electrostatic potential at the retinal of three archaeal rhodopsins: implications for their different absorption spectra.

The color tuning mechanism of the rhodopsin protein family has been in the focus of research for decades. However, the structural basis of the tuning mechanism in general and of the absorption shift between rhodopsins in particular remains under discussion. It is clear that a major determinant for spectral shifts between different rhodopsins are electrostatic interactions between the chromophore retinal and the protein. Based on the Poisson-Boltzmann equation, we computed and compared the electrostatic potential at the retinal of three archaeal rhodopsins: bacteriorhodopsin (BR), halorhodopsin (HR), and sensory rhodopsin II (SRII) for which high-resolution structures are available. These proteins are an excellent test case for understanding the spectral tuning of retinal. The absorption maxima of BR and HR are very similar, whereas the spectrum of SRII is considerably blue shifted--despite the structural similarity between these three proteins. In agreement with their absorption maxima, we find that the electrostatic potential is similar in BR and HR, whereas significant differences are seen for SRII. The decomposition of the electrostatic potential into contributions of individual residues, allowed us to identify seven residues that are responsible for the differences in electrostatic potential between the proteins. Three of these residues are located in the retinal binding pocket and have in fact been shown to account for part of the absorption shift between BR and SRII by mutational studies. One residue is located close to the beta-ionone ring of retinal and the remaining three residues are more than 8 A away from the retinal. These residues have not been discussed before, because they are, partly because of their location, no obvious candidates for the spectral shift among BR, HR, and SRII. However, their contribution to the differences in electrostatic potential is evident. The counterion of the Schiff base, which is frequently discussed to be involved in the spectral tuning, does not contribute to the dissimilarities between the electrostatic potentials.