Interferon response to respiratory syncytial virus by bronchial epithelium from children with asthma is inversely correlated with pulmonary function.

BACKGROUND: Respiratory viral infection in early childhood, including that from respiratory syncytial virus (RSV), has been previously associated with the development of asthma. OBJECTIVE: We aimed to determine whether ex vivo RSV infection of bronchial epithelial cells (BECs) from children with asthma would induce specific gene expression patterns and whether such patterns were associated with lung function among BEC donors. METHODS: Primary BECs from carefully characterized children with asthma (n = 18) and matched healthy children without asthma (n = 8) were differentiated at an air-liquid interface for 21 days. Air-liquid interface cultures were infected with RSV for 96 hours and RNA was subsequently isolated from BECs. In each case, we analyzed gene expression using RNA sequencing and assessed differences between conditions by linear modeling of the data. BEC donors completed spirometry to measure lung function. RESULTS: RSV infection of BECs from subjects with asthma, compared with uninfected BECs from subjects with asthma, led to a significant increase in expression of 6199 genes. There was significantly greater expression of 195 genes in BECs from children with asthma and airway obstruction (FEV1/forced vital capacity < 0.85 and FEV1 < 100% predicted) than in BECs from children with asthma without obstruction, or in BECs from healthy children. These specific genes were found to be highly enriched for viral response genes induced in parallel with types I and III interferons. CONCLUSIONS: BECs from children with asthma and with obstructive physiology exhibit greater expression of types I and III interferons and interferon-stimulated genes than do cells from children with normal lung function, and expression of interferon-associated genes correlates with the degree of airway obstruction. These findings suggest that an exaggerated interferon response to viral infection by airway epithelial cells may be a mechanism leading to lung function decline in a subset of children with asthma.

IL-17RA Signaling in Airway Inflammation and Bronchial Hyperreactivity in Allergic Asthma.

Asthma is a heterogeneous disease characterized by airway inflammation and hyperreactivity. IL-17 receptor A (IL-17RA) is a shared receptor subunit required for activity of IL-17 family cytokines, including IL-17A and IL-25. IL-17A and IL-25 induce different proinflammatory responses, and concentrations are elevated in subjects with asthma. However, the individual contributions of IL-17A and IL-25 to disease pathogenesis are unclear. We explored proinflammatory activities of the IL-17 pathway in models of pulmonary inflammation and assessed its effects on contractility of human bronchial airway smooth muscle. In two mouse models, IL-17RA, IL-17RB, or IL-25 blockade reduced airway inflammation and airway hyperreactivity. Individually, IL-17A and IL-25 enhanced contractility of human bronchial smooth muscle induced by methacholine or carbachol. IL-17A had more pronounced effects on methacholine-induced contractility in bronchial rings from donors with asthma compared with donors without asthma. Blocking the IL-17 pathway via IL-17RA may be a useful therapy for some patients with asthma by reducing pulmonary inflammation and airway hyperreactivity.

The eptinezumab:CGRP complex structure - the role of conformational changes in binding stabilization.

To further elucidate the mechanism of action and binding properties of eptinezumab to calcitonin gene-related peptide (CGRP), X-ray crystallography, computational alanine scanning, and molecular dynamics were used. X-ray diffraction data were collected to determine the three-dimensional structures of the unbound eptinezumab antigen-binding fragment (Fab) and the Fab:CGRP complex. Molecular dynamics simulations were performed to analyze the transition between uncomplexed and complex states. The amidated C-terminus of CGRP was shown to bind in a pocket formed by the Fab heavy and light chains. There was extensive contact between all six complementarity-determining regions (CDRs; composed of light-chain [L1, L2, and L3] and heavy-chain [H1, H2, H3]) of eptinezumab and CGRP. The complex demonstrated a high ligand-binding surface area dominated by aromatic residues. CDR L3 contains a disulfide bond that stabilizes the loop, contributes surface area to the binding pocket, and provides van der Waals contacts. Comparison of the uncomplexed and complex structures revealed motion near the binding cleft. The CDR loops H2 and H3 were displaced ~1.4-2.0 Å and residue H-Tyr33 changed conformation, creating a 'latch-and-lock' mechanism for binding CGRP and preventing dissociation. Computational alanine scanning of CGRP identified energetic 'hot spots' that contribute to binding energy; mutating these positions to residues in homologous neuropeptides resulted in unfavorable binding energies. The attributes of the Fab region and the conformational changes that occur in eptinezumab during binding to CGRP contribute to the specificity, durability, and strength of the interaction, and likely underlie the rapid and sustained migraine preventive effect observed in clinical studies.

DNA copy number, including telomeres and mitochondria, assayed using next-generation sequencing.

BACKGROUND: DNA copy number variations occur within populations and aberrations can cause disease. We sought to develop an improved lab-automatable, cost-efficient, accurate platform to profile DNA copy number. RESULTS: We developed a sequencing-based assay of nuclear, mitochondrial, and telomeric DNA copy number that draws on the unbiased nature of next-generation sequencing and incorporates techniques developed for RNA expression profiling. To demonstrate this platform, we assayed UMC-11 cells using 5 million 33 nt reads and found tremendous copy number variation, including regions of single and homogeneous deletions and amplifications to 29 copies; 5 times more mitochondria and 4 times less telomeric sequence than a pool of non-diseased, blood-derived DNA; and that UMC-11 was derived from a male individual. CONCLUSION: The described assay outputs absolute copy number, outputs an error estimate (p-value), and is more accurate than array-based platforms at high copy number. The platform enables profiling of mitochondrial levels and telomeric length. The assay is lab-automatable and has a genomic resolution and cost that are tunable based on the number of sequence reads.

Progress and challenges in high-resolution refinement of protein structure models.

Achieving atomic level accuracy in de novo structure prediction presents a formidable challenge even in the context of protein models with correct topologies. High-resolution refinement is a fundamental test of force field accuracy and sampling methodology, and its limited success in both comparative modeling and de novo prediction contexts highlights the limitations of current approaches. We constructed four tests to identify bottlenecks in our current approach and to guide progress in this challenging area. The first three tests showed that idealized native structures are stable under our refinement simulation conditions and that the refinement protocol can significantly decrease the root mean square deviation (RMSD) of perturbed native structures. In the fourth test we applied the refinement protocol to de novo models and showed that accurate models could be identified based on their energies, and in several cases many of the buried side chains adopted native-like conformations. We also showed that the differences in backbone and side-chain conformations between the refined de novo models and the native structures are largely localized to loop regions and regions where the native structure has unusual features such as rare rotamers or atypical hydrogen bonding between beta-strands. The refined de novo models typically have higher energies than refined idealized native structures, indicating that sampling of local backbone conformations and side-chain packing arrangements in a condensed state is a primary obstacle.

Free modeling with Rosetta in CASP6.

We describe Rosetta predictions in the Sixth Community-Wide Experiment on the Critical Assessment of Techniques for Protein Structure Prediction (CASP), focusing on the free modeling category. Methods developed since CASP5 are described, and their application to selected targets is discussed. Highlights include improved performance on larger proteins (100-200 residues) and the prediction of a 70-residue alpha-beta protein to near-atomic resolution.

Analysis of anisotropic side-chain packing in proteins and application to high-resolution structure prediction.

pi-pi, Cation-pi, and hydrophobic packing interactions contribute specificity to protein folding and stability to the native state. As a step towards developing improved models of these interactions in proteins, we compare the side-chain packing arrangements in native proteins to those found in compact decoys produced by the Rosetta de novo structure prediction method. We find enrichments in the native distributions for T-shaped and parallel offset arrangements of aromatic residue pairs, in parallel stacked arrangements of cation-aromatic pairs, in parallel stacked pairs involving proline residues, and in parallel offset arrangements for aliphatic residue pairs. We then investigate the extent to which the distinctive features of native packing can be explained using Lennard-Jones and electrostatics models. Finally, we derive orientation-dependent pi-pi, cation-pi and hydrophobic interaction potentials based on the differences between the native and compact decoy distributions and investigate their efficacy for high-resolution protein structure prediction. Surprisingly, the orientation-dependent potential derived from the packing arrangements of aliphatic side-chain pairs distinguishes the native structure from compact decoys better than the orientation-dependent potentials describing pi-pi and cation-pi interactions.

Protein-protein docking predictions for the CAPRI experiment.

We predicted structures for all seven targets in the CAPRI experiment using a new method in development at the time of the challenge. The technique includes a low-resolution rigid body Monte Carlo search followed by high-resolution refinement with side-chain conformational changes and rigid body minimization. Decoys (approximately 10(6) per target) were discriminated using a scoring function including van der Waals and solvation interactions, hydrogen bonding, residue-residue pair statistics, and rotamer probabilities. Decoys were ranked, clustered, manually inspected, and selected. The top ranked model for target 6 predicted the experimental structure to 1.5 A RMSD and included 48 of 65 correct residue-residue contacts. Target 7 was predicted at 5.3 A RMSD with 22 of 37 correct residue-residue contacts using a homology model from a known complex structure. Using a preliminary version of the protocol in round 1, target 1 was predicted within 8.8 A although few contacts were correct. For targets 2 and 3, the interface locations and a small fraction of the contacts were correctly identified.

Rosetta predictions in CASP5: successes, failures, and prospects for complete automation.

We describe predictions of the structures of CASP5 targets using Rosetta. The Rosetta fragment insertion protocol was used to generate models for entire target domains without detectable sequence similarity to a protein of known structure and to build long loop insertions (and N-and C-terminal extensions) in cases where a structural template was available. Encouraging results were obtained both for the de novo predictions and for the long loop insertions; we describe here the successes as well as the failures in the context of current efforts to improve the Rosetta method. In particular, de novo predictions failed for large proteins that were incorrectly parsed into domains and for topologically complex (high contact order) proteins with swapping of segments between domains. However, for the remaining targets, at least one of the five submitted models had a long fragment with significant similarity to the native structure. A fully automated version of the CASP5 protocol produced results that were comparable to the human-assisted predictions for most of the targets, suggesting that automated genomic-scale, de novo protein structure prediction may soon be worthwhile. For the three targets where the human-assisted predictions were significantly closer to the native structure, we identify the steps that remain to be automated.

Physically realistic homology models built with ROSETTA can be more accurate than their templates.

We have developed a method that combines the ROSETTA de novo protein folding and refinement protocol with distance constraints derived from homologous structures to build homology models that are frequently more accurate than their templates. We test this method by building complete-chain models for a benchmark set of 22 proteins, each with 1 or 2 candidate templates, for a total of 39 test cases. We use structure-based and sequence-based alignments for each of the test cases. All atoms, including hydrogens, are represented explicitly. The resulting models contain approximately the same number of atomic overlaps as experimentally determined crystal structures and maintain good stereochemistry. The most accurate models can be identified by their energies, and in 22 of 39 cases a model that is more accurate than the template over aligned regions is one of the 10 lowest-energy models.

Toward high-resolution de novo structure prediction for small proteins.

The prediction of protein structure from amino acid sequence is a grand challenge of computational molecular biology. By using a combination of improved low- and high-resolution conformational sampling methods, improved atomically detailed potential functions that capture the jigsaw puzzle-like packing of protein cores, and high-performance computing, high-resolution structure prediction (<1.5 angstroms) can be achieved for small protein domains (<85 residues). The primary bottleneck to consistent high-resolution prediction appears to be conformational sampling.

Progress in modeling of protein structures and interactions.

The prediction of the structures and interactions of biological macromolecules at the atomic level and the design of new structures and interactions are critical tests of our understanding of the interatomic interactions that underlie molecular biology. Equally important, the capability to accurately predict and design macromolecular structures and interactions would streamline the interpretation of genome sequence information and allow the creation of macromolecules with new and useful functions. This review summarizes recent progress in modeling that suggests that we are entering an era in which high-resolution prediction and design will make increasingly important contributions to biology and medicine.

Three-dimensional structure of the amino-terminal domain of syntaxin 6, a SNAP-25 C homolog.

Soluble N-ethylmaleimide-sensitive factor attachment protein receptor (SNARE) proteins are required for intracellular membrane fusion, and are differentially localized throughout the cell. SNAREs on vesicle and target membranes contain "SNARE motifs" which interact to form a four-helix bundle that contributes to the fusion of two membranes. SNARE motif sequences fall into four classes, homologous to the neuronal proteins syntaxin 1a, VAMP 2, and the N- and C-terminal SNARE motifs of SNAP-25 (S25N and S25C), and it is thought that one member from each class interacts to form a SNARE complex. Many SNAREs also feature N-terminal domains believed to function in regulating SNARE complex assembly or other aspects of vesicle transport. Syntaxin 6 is a SNARE found primarily in endosomal transport vesicles and whose SNARE motif shows significant homology to both syntaxin 1a and S25C. The crystal structure of the syntaxin 6 N-terminal domain reveals strong structural similarity with the N-terminal domains of syntaxin family members syntaxin 1a, Sso1p, and Vam3p, despite a very low level of sequence similarity. The syntaxin 6 SNARE motif can substitute for S25C in in vitro binding experiments, supporting the classification of syntaxin 6 as an S25C family member. Secondary structure prediction of SNARE proteins shows that the N-terminal domains of many syntaxin, S25N, and S25C family members are likely to be similar to one another, but are distinct from those of VAMP family members, indicating that syntaxin, S25N, and S25C SNAREs may have shared a common ancestor.