Ketogenic diet acutely improves gas exchange and sleep apnoea in obesity hypoventilation syndrome: A non-randomized crossover study

BACKGROUND AND OBJECTIVE

Obesity hypoventilation syndrome (OHS) causes hypercapnia which is often refractory to current therapies. We examine whether hypercapnia in OHS can be improved by a ketogenic dietary intervention.

METHODS

We conducted a single-arm crossover clinical trial to examine the impact of a ketogenic diet on CO2 levels in patients with OHS. Patients were instructed to adhere to 1 week of regular diet, 2 weeks of ketogenic diet, followed by 1 week of regular diet in an ambulatory setting. Adherence was assessed with capillary ketone levels and continuous glucose monitors. At weekly visits, we measured blood gases, calorimetry, body composition, metabolic profiles, and sleep studies. Outcomes were assessed with linear mixed models.

RESULTS

A total of 20 subjects completed the study. Blood ketones increased from 0.14 ± 0.08 during regular diet to 1.99 ± 1.11 mmol/L (p < 0.001) after 2 weeks of ketogenic diet. Ketogenic diet decreased venous CO2 by 3.0 mm Hg (p = 0.008), bicarbonate by 1.8 mmol/L (p = 0.001), and weight by 3.4 kg (p < 0.001). Sleep apnoea severity and nocturnal oxygen levels significantly improved. Ketogenic diet lowered respiratory quotient, fat mass, body water, glucose, insulin, triglycerides, leptin, and insulin-like growth factor 1. Rebound hypercapnia was observed after resuming regular diet. CO2 lowering was dependent on baseline hypercapnia, and associated with circulating ketone levels and respiratory quotient. The ketogenic diet was well tolerated.

CONCLUSION

This study demonstrates for the first time that a ketogenic diet may be useful for control of hypercapnia and sleep apnoea in patients with obesity hypoventilation syndrome.

De novo design of small beta barrel proteins

Small beta barrel proteins are attractive targets for computational design because of their considerable functional diversity despite their very small size (<70 amino acids). However, there are considerable challenges to designing such structures, and there has been little success thus far. Because of the small size, the hydrophobic core stabilizing the fold is necessarily very small, and the conformational strain of barrel closure can oppose folding; also intermolecular aggregation through free beta strand edges can compete with proper monomer folding. Here, we explore the de novo design of small beta barrel topologies using both Rosetta energy-based methods and deep learning approaches to design four small beta barrel folds: Src homology 3 (SH3) and oligonucleotide/oligosaccharide-binding (OB) topologies found in nature and five and six up-and-down-stranded barrels rarely if ever seen in nature. Both approaches yielded successful designs with high thermal stability and experimentally determined structures with less than 2.4 Å rmsd from the designed models. Using deep learning for backbone generation and Rosetta for sequence design yielded higher design success rates and increased structural diversity than Rosetta alone. The ability to design a large and structurally diverse set of small beta barrel proteins greatly increases the protein shape space available for designing binders to protein targets of interest.

Protein tertiary structure prediction and refinement using deep learning and Rosetta in CASP14

The trRosetta structure prediction method employs deep learning to generate predicted residue‐residue distance and orientation distributions from which 3D models are built. We sought to improve the method by incorporating as inputs (in addition to sequence information) both language model embeddings and template information weighted by sequence similarity to the target. We also developed a refinement pipeline that recombines models generated by template‐free and template utilizing versions of trRosetta guided by the DeepAccNet accuracy predictor. Both benchmark tests and CASP results show that the new pipeline is a considerable improvement over the original trRosetta, and it is faster and requires less computing resources, completing the entire modeling process in a median < 3 h in CASP14. Our human group improved results with this pipeline primarily by identifying additional homologous sequences for input into the network. We also used the DeepAccNet accuracy predictor to guide Rosetta high‐resolution refinement for submissions in the regular and refinement categories; although performance was quite good on a CASP relative scale, the overall improvements were rather modest in part due to missing inter‐domain or inter‐chain contacts.

Investigation of the damping wiggler effect and application on the PAL fourth-generation storage ring

An investigation of the damping wiggler effect to reduce the emittance in the Pohang Accelerator Laboratory (PAL), a fourth-generation storage ring (4GSR) that uses a multi-bend achromat, is presented. A 4GSR lattice which has reduced emittance and increased dynamic aperture to amplify the synergy with two existing light sources (PLS-II and PAL-XFEL) at PAL is described.

Demonstration of a ring-FEL as an EUV lithography tool

This paper presents the required structure and function of a ring-FEL as a radiation source for extreme ultraviolet radiation lithography (EUVL). A 100 m-long straight section that conducts an extremely low emittance beam from a fourth-generation storage ring can increase the average power at 13.5 nm wavelength to up to 1 kW without degrading the beam in the rest of the ring. Here, simulation results for a ring-FEL as a EUVL source are described.

High-accuracy refinement using Rosetta in CASP13

Because proteins generally fold to their lowest free energy states, energy-guided refinement in principle should be able to systematically improve the quality of protein structure models generated using homologous structure or co-evolution derived information. However, because of the high dimensionality of the search space, there are far more ways to degrade the quality of a near native model than to improve it, and hence, refinement methods are very sensitive to energy function errors. In the 13th Critial Assessment of techniques for protein Structure Prediction (CASP13), we sought to carry out a thorough search for low energy states in the neighborhood of a starting model using restraints to avoid straying too far. The approach was reasonably successful in improving both regions largely incorrect in the starting models as well as core regions that started out closer to the correct structure. Models with GDT-HA over 70 were obtained for five targets and for one of those, an accuracy of 0.5 å backbone root-mean-square deviation (RMSD) was achieved. An important current challenge is to improve performance in refining oligomers and larger proteins, for which the search problem remains extremely difficult.

An analysis and evaluation of the WeFold collaborative for protein structure prediction and its pipelines in CASP11 and CASP12

Every two years groups worldwide participate in the Critical Assessment of Protein Structure Prediction (CASP) experiment to blindly test the strengths and weaknesses of their computational methods. CASP has significantly advanced the field but many hurdles still remain, which may require new ideas and collaborations. In 2012 a web-based effort called WeFold, was initiated to promote collaboration within the CASP community and attract researchers from other fields to contribute new ideas to CASP. Members of the WeFold coopetition (cooperation and competition) participated in CASP as individual teams, but also shared components of their methods to create hybrid pipelines and actively contributed to this effort. We assert that the scale and diversity of integrative prediction pipelines could not have been achieved by any individual lab or even by any collaboration among a few partners. The models contributed by the participating groups and generated by the pipelines are publicly available at the WeFold website providing a wealth of data that remains to be tapped. Here, we analyze the results of the 2014 and 2016 pipelines showing improvements according to the CASP assessment as well as areas that require further adjustments and research.

Protein homology model refinement by large-scale energy optimization

Proteins fold to their lowest free-energy structures, and hence the most straightforward way to increase the accuracy of a partially incorrect protein structure model is to search for the lowest-energy nearby structure. This direct approach has met with little success for two reasons: first, energy function inaccuracies can lead to false energy minima, resulting in model degradation rather than improvement; and second, even with an accurate energy function, the search problem is formidable because the energy only drops considerably in the immediate vicinity of the global minimum, and there are a very large number of degrees of freedom. Here we describe a large-scale energy optimization-based refinement method that incorporates advances in both search and energy function accuracy that can substantially improve the accuracy of low-resolution homology models. The method refined low-resolution homology models into correct folds for 50 of 84 diverse protein families and generated improved models in recent blind structure prediction experiments. Analyses of the basis for these improvements reveal contributions from both the improvements in conformational sampling techniques and the energy function.

Comprehensive computational design of ordered peptide macrocycles

Mixed-chirality peptide macrocycles such as cyclosporine are among the most potent therapeutics identified to date, but there is currently no way to systematically search the structural space spanned by such compounds. Natural proteins do not provide a useful guide: Peptide macrocycles lack regular secondary structures and hydrophobic cores, and can contain local structures not accessible with l-amino acids. Here, we enumerate the stable structures that can be adopted by macrocyclic peptides composed of l- and d-amino acids by near-exhaustive backbone sampling followed by sequence design and energy landscape calculations. We identify more than 200 designs predicted to fold into single stable structures, many times more than the number of currently available unbound peptide macrocycle structures. Nuclear magnetic resonance structures of 9 of 12 designed 7- to 10-residue macrocycles, and three 11- to 14-residue bicyclic designs, are close to the computational models. Our results provide a nearly complete coverage of the rich space of structures possible for short peptide macrocycles and vastly increase the available starting scaffolds for both rational drug design and library selection methods.

Protein structure prediction using Rosetta in CASP12

We describe several notable aspects of our structure predictions using Rosetta in CASP12 in the free modeling (FM) and refinement (TR) categories. First, we had previously generated (and published) models for most large protein families lacking experimentally determined structures using Rosetta guided by co-evolution based contact predictions, and for several targets these models proved better starting points for comparative modeling than any known crystal structure-our model database thus starts to fulfill one of the goals of the original protein structure initiative. Second, while our "human" group simply submitted ROBETTA models for most targets, for six targets expert intervention improved predictions considerably; the largest improvement was for T0886 where we correctly parsed two discontinuous domains guided by predicted contact maps to accurately identify a structural homolog of the same fold. Third, Rosetta all atom refinement followed by MD simulations led to consistent but small improvements when starting models were close to the native structure, and larger but less consistent improvements when starting models were further away.

Seizures in patients with acute pesticide intoxication, with a focus on glufosinate ammonium

The incidence and clinical aspects of seizures remain to be elucidated in patients with acute pesticide intoxication. The present study included subjects who ingested pesticide with the intention of committing suicide and were treated at Soonchunhyang University Hospital (Cheonan, Korea) between January 2011 and December 2014. We analyzed the incidence and characterized the type and frequency of seizure, from the medical records of 464 patients with acute pesticide intoxication, according to the pesticide class. The effect of seizure on the clinical outcome was assessed. The incidence of seizure was 31.5% in patients who ingested glufosinate ammonium {2-amino-4-[hydroxyl (methyl) phosphinoyl] butyrate; ammonium DL-homoalanin-4-yl (methyl) phosphinate}, followed by those who ingested pyrethroid (5.9%) or glycine derivatives (5.4%). All of the seizures developed between 12 and 24 h of pesticide ingestion and had ceased by 72 h after seizure initiation, following treatment with antiseizure medication. Generalized tonic-clonic seizures were the most commonly observed (85.7% of the cases). Multivariable logistic regression analysis showed that the effect of seizure on mortality was not statistically significant. In conclusion, glufosinate ammonium herbicide is the most common seizurogenic pesticide class. Seizure itself was not a risk factor for mortality in patients with acute glufosinate ammonium intoxication.

Protein structure determination using metagenome sequence data

Despite decades of work by structural biologists, there are still ~5200 protein families with unknown structure outside the range of comparative modeling. We show that Rosetta structure prediction guided by residue-residue contacts inferred from evolutionary information can accurately model proteins that belong to large families and that metagenome sequence data more than triple the number of protein families with sufficient sequences for accurate modeling. We then integrate metagenome data, contact-based structure matching, and Rosetta structure calculations to generate models for 614 protein families with currently unknown structures; 206 are membrane proteins and 137 have folds not represented in the Protein Data Bank. This approach provides the representative models for large protein families originally envisioned as the goal of the Protein Structure Initiative at a fraction of the cost.

Simultaneous Optimization of Biomolecular Energy Functions on Features from Small Molecules and Macromolecules

Most biomolecular modeling energy functions for structure prediction, sequence design, and molecular docking have been parametrized using existing macromolecular structural data; this contrasts molecular mechanics force fields which are largely optimized using small-molecule data. In this study, we describe an integrated method that enables optimization of a biomolecular modeling energy function simultaneously against small-molecule thermodynamic data and high-resolution macromolecular structural data. We use this approach to develop a next-generation Rosetta energy function that utilizes a new anisotropic implicit solvation model, and an improved electrostatics and Lennard-Jones model, illustrating how energy functions can be considerably improved in their ability to describe large-scale energy landscapes by incorporating both small-molecule and macromolecule data. The energy function improves performance in a wide range of protein structure prediction challenges, including monomeric structure prediction, protein-protein and protein-ligand docking, protein sequence design, and prediction of the free energy changes by mutation, while reasonably recapitulating small-molecule thermodynamic properties.

Structure prediction using sparse simulated NOE restraints with Rosetta in CASP11

In CASP11 we generated protein structure models using simulated ambiguous and unambiguous nuclear Overhauser effect (NOE) restraints with a two stage protocol. Low resolution models were generated guided by the unambiguous restraints using continuous chain folding for alpha and alpha-beta proteins, and iterative annealing for all beta proteins to take advantage of the strand pairing information implicit in the restraints. The Rosetta fragment/model hybridization protocol was then used to recombine and regularize these models, and refine them in the Rosetta full atom energy function guided by both the unambiguous and the ambiguous restraints. Fifteen out of 19 targets were modeled with GDT-TS quality scores greater than 60 for Model 1, significantly improving upon the non-assisted predictions. Our results suggest that atomic level accuracy is achievable using sparse NOE data when there is at least one correctly assigned NOE for every residue. Proteins 2016; 84(Suppl 1):181-188. © 2016 Wiley Periodicals, Inc.

Improved de novo structure prediction in CASP11 by incorporating coevolution information into Rosetta

We describe CASP11 de novo blind structure predictions made using the Rosetta structure prediction methodology with both automatic and human assisted protocols. Model accuracy was generally improved using coevolution derived residue-residue contact information as restraints during Rosetta conformational sampling and refinement, particularly when the number of sequences in the family was more than three times the length of the protein. The highlight was the human assisted prediction of T0806, a large and topologically complex target with no homologs of known structure, which had unprecedented accuracy-<3.0 Å root-mean-square deviation (RMSD) from the crystal structure over 223 residues. For this target, we increased the amount of conformational sampling over our fully automated method by employing an iterative hybridization protocol. Our results clearly demonstrate, in a blind prediction scenario, that coevolution derived contacts can considerably increase the accuracy of template-free structure modeling. Proteins 2016; 84(Suppl 1):67-75. © 2015 Wiley Periodicals, Inc.

Large-scale determination of previously unsolved protein structures using evolutionary information

The prediction of the structures of proteins without detectable sequence similarity to any protein of known structure remains an outstanding scientific challenge. Here we report significant progress in this area. We first describe de novo blind structure predictions of unprecendented accuracy we made for two proteins in large families in the recent CASP11 blind test of protein structure prediction methods by incorporating residue-residue co-evolution information in the Rosetta structure prediction program. We then describe the use of this method to generate structure models for 58 of the 121 large protein families in prokaryotes for which three-dimensional structures are not available. These models, which are posted online for public access, provide structural information for the over 400,000 proteins belonging to the 58 families and suggest hypotheses about mechanism for the subset for which the function is known, and hypotheses about function for the remainder.

One contact for every twelve residues allows robust and accurate topology-level protein structure modeling

A number of methods have been described for identifying pairs of contacting residues in protein three-dimensional structures, but it is unclear how many contacts are required for accurate structure modeling. The CASP10 assisted contact experiment provided a blind test of contact guided protein structure modeling. We describe the models generated for these contact guided prediction challenges using the Rosetta structure modeling methodology. For nearly all cases, the submitted models had the correct overall topology, and in some cases, they had near atomic-level accuracy; for example the model of the 384 residue homo-oligomeric tetramer (Tc680o) had only 2.9 Å root-mean-square deviation (RMSD) from the crystal structure. Our results suggest that experimental and bioinformatic methods for obtaining contact information may need to generate only one correct contact for every 12 residues in the protein to allow accurate topology level modeling.

ROSETTA3: an object-oriented software suite for the simulation and design of macromolecules

We have recently completed a full re-architecturing of the ROSETTA molecular modeling program, generalizing and expanding its existing functionality. The new architecture enables the rapid prototyping of novel protocols by providing easy-to-use interfaces to powerful tools for molecular modeling. The source code of this rearchitecturing has been released as ROSETTA3 and is freely available for academic use. At the time of its release, it contained 470,000 lines of code. Counting currently unpublished protocols at the time of this writing, the source includes 1,285,000 lines. Its rapid growth is a testament to its ease of use. This chapter describes the requirements for our new architecture, justifies the design decisions, sketches out central classes, and highlights a few of the common tasks that the new software can perform.

ROSETTA3: an object-oriented software suite for the simulation and design of macromolecules

We have recently completed a full re-architecturing of the ROSETTA molecular modeling program, generalizing and expanding its existing functionality. The new architecture enables the rapid prototyping of novel protocols by providing easy-to-use interfaces to powerful tools for molecular modeling. The source code of this rearchitecturing has been released as ROSETTA3 and is freely available for academic use. At the time of its release, it contained 470,000 lines of code. Counting currently unpublished protocols at the time of this writing, the source includes 1,285,000 lines. Its rapid growth is a testament to its ease of use. This chapter describes the requirements for our new architecture, justifies the design decisions, sketches out central classes, and highlights a few of the common tasks that the new software can perform.

ROSETTA3: an object-oriented software suite for the simulation and design of macromolecules

We have recently completed a full re-architecturing of the ROSETTA molecular modeling program, generalizing and expanding its existing functionality. The new architecture enables the rapid prototyping of novel protocols by providing easy-to-use interfaces to powerful tools for molecular modeling. The source code of this rearchitecturing has been released as ROSETTA3 and is freely available for academic use. At the time of its release, it contained 470,000 lines of code. Counting currently unpublished protocols at the time of this writing, the source includes 1,285,000 lines. Its rapid growth is a testament to its ease of use. This chapter describes the requirements for our new architecture, justifies the design decisions, sketches out central classes, and highlights a few of the common tasks that the new software can perform.

Sampling bottlenecks in de novo protein structure prediction

The primary obstacle to de novo protein structure prediction is conformational sampling: the native state generally has lower free energy than nonnative structures but is exceedingly difficult to locate. Structure predictions with atomic level accuracy have been made for small proteins using the Rosetta structure prediction method, but for larger and more complex proteins, the native state is virtually never sampled, and it has been unclear how much of an increase in computing power would be required to successfully predict the structures of such proteins. In this paper, we develop an approach to determining how much computer power is required to accurately predict the structure of a protein, based on a reformulation of the conformational search problem as a combinatorial sampling problem in a discrete feature space. We find that conformational sampling for many proteins is limited by critical "linchpin" features, often the backbone torsion angles of individual residues, which are sampled very rarely in unbiased trajectories and, when constrained, dramatically increase the sampling of the native state. These critical features frequently occur in less regular and likely strained regions of proteins that contribute to protein function. In a number of proteins, the linchpin features are in regions found experimentally to form late in folding, suggesting a correspondence between folding in silico and in reality.

Analytical model development for the prediction of the frictional resistance of a capsule endoscope inside an intestine

For the purpose of optimizing the design of the locomotion mechanism as well as the body shape of a self-propelled capsule endoscope, an analytical model for the prediction of frictional resistance of the capsule moving inside the small intestine was first developed. The model was developed by considering the contact geometry and viscoelasticity of the intestine, based on the experimental investigations on the material properties of the intestine and the friction of the capsule inside the small intestine. In order to verify the model and to investigate the distributions of various stress components applied to the capsule, finite element (FE) analyses were carried out. The comparison of the frictional resistance between the predicted and the experimental values suggested that the proposed model could predict the frictional force of the capsule with reasonable accuracy. Also, the FE analysis results of various stress components revealed the stress relaxation of the intestine and explained that such stress relaxation characteristics of the intestine resulted in lower frictional force as the speed of the capsule decreased. These results suggested that the frontal shape of the capsule was critical to the design of the capsule with desired frictional performance. It was shown that the proposed model can provide quantitative estimation of the frictional resistance of the capsule under various moving conditions inside the intestine. The model is expected to be useful in the design optimization of the capsule locomotion inside the intestine.

Structure prediction for CASP7 targets using extensive all-atom refinement with Rosetta@home

We describe predictions made using the Rosetta structure prediction methodology for both template-based modeling and free modeling categories in the Seventh Critical Assessment of Techniques for Protein Structure Prediction. For the first time, aggressive sampling and all-atom refinement could be carried out for the majority of targets, an advance enabled by the Rosetta@home distributed computing network. Template-based modeling predictions using an iterative refinement algorithm improved over the best existing templates for the majority of proteins with less than 200 residues. Free modeling methods gave near-atomic accuracy predictions for several targets under 100 residues from all secondary structure classes. These results indicate that refinement with an all-atom energy function, although computationally expensive, is a powerful method for obtaining accurate structure predictions.

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.

Automated prediction of domain boundaries in CASP6 targets using Ginzu and RosettaDOM

Domain boundary prediction is an important step in both experimental and computational protein structure characterization. We have developed two fully automated domain parsing methods: the first, Ginzu, which we have described previously, utilizes information from homologous sequences and structures, while the second, RosettaDOM, which has not been described previously, uses only information in the query sequence. Ginzu iteratively assigns domains by homology to structures and sequence families using successively less confident methods. RosettaDOM uses the Rosetta de novo structure prediction method to build three-dimensional models, and then applies Taylor's structure based domain assignment method to parse the models into domains. Domain boundaries observed repeatedly in the models are predicted to be domain boundaries for the protein. Interestingly, RosettaDOM produced quite good domain predictions for proteins of a size typically considered to be beyond the reach of de novo structure prediction methods. For remote fold recognition targets and new folds, both Ginzu and RosettaDOM produced promising results, and in some cases where one method failed to detect the correct domain boundary, it was correctly identified by the other method. We describe here the successes and failures using both methods, and address the possibility of incorporating both protocols into an improved hybrid method.

Prediction of CASP6 structures using automated Robetta protocols

The Robetta server and revised automatic protocols were used to predict structures for CASP6 targets. Robetta is a publicly available protein structure prediction server (http://robetta.bakerlab.org/ that uses the Rosetta de novo and homology modeling structure prediction methods. We incorporated some of the lessons learned in the CASP5 experiment into the server prior to participating in CASP6. We additionally tested new ideas that were amenable to full-automation with an eye toward improving the server. We find that the Robetta server shows the greatest promise for the more challenging targets. The most significant finding from CASP5, that automated protocols can be roughly comparable in ability with the better human-intervention predictors, is repeated here in CASP6.

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.

Frictional resistance characteristics of a capsule inside the intestine for microendoscope design

The design of the capsule body for a self-proplled endoscope is important from the frictional resistance point of view. The motivation of this work was to gain a better understanding of the effect of capsule shape on the frictional resistance of the capsule inside a small intestine. Special experimental set-ups were built to investigate the frictional resistance of the capsule and the viscoelastic deformation characteristics of the small intestine specimen of a pig. Tests were performed with capsules of various shapes and dimensions. Experimental data showed that a smooth cylindrical capsule geometry resulted in the least frictional resistance due to the shape and relatively small surface area. Also, it was found that the variation of frictional resistance of the capsule was closely related to the local change in the viscoelastic property of the intestine due to the heterogeneity of the internal structure of the intestine.

Protein structure prediction and analysis using the Robetta server

The Robetta server (http://robetta.bakerlab.org) provides automated tools for protein structure prediction and analysis. For structure prediction, sequences submitted to the server are parsed into putative domains and structural models are generated using either comparative modeling or de novo structure prediction methods. If a confident match to a protein of known structure is found using BLAST, PSI-BLAST, FFAS03 or 3D-Jury, it is used as a template for comparative modeling. If no match is found, structure predictions are made using the de novo Rosetta fragment insertion method. Experimental nuclear magnetic resonance (NMR) constraints data can also be submitted with a query sequence for RosettaNMR de novo structure determination. Other current capabilities include the prediction of the effects of mutations on protein-protein interactions using computational interface alanine scanning. The Rosetta protein design and protein-protein docking methodologies will soon be available through the server as well.

Protein structure prediction and analysis using the Robetta server

The Robetta server (http://robetta.bakerlab.org) provides automated tools for protein structure prediction and analysis. For structure prediction, sequences submitted to the server are parsed into putative domains and structural models are generated using either comparative modeling or de novo structure prediction methods. If a confident match to a protein of known structure is found using BLAST, PSI-BLAST, FFAS03 or 3D-Jury, it is used as a template for comparative modeling. If no match is found, structure predictions are made using the de novo Rosetta fragment insertion method. Experimental nuclear magnetic resonance (NMR) constraints data can also be submitted with a query sequence for RosettaNMR de novo structure determination. Other current capabilities include the prediction of the effects of mutations on protein-protein interactions using computational interface alanine scanning. The Rosetta protein design and protein-protein docking methodologies will soon be available through the server as well.

Contributions of amino acid side chains to the kinetics and thermodynamics of the bivalent binding of protein L to Ig kappa light chain

Protein L is a bacterial surface protein with 4-5 immunoglobulin (Ig)-binding domains (B1-B5), each of which appears to have two binding sites for Ig, corresponding to the two edges of its beta-sheet. To verify these sites biochemically and to probe their relative contributions to the protein L-Ig kappa light chain (kappa) interaction, we compared the binding of PLW (the Y47W mutant of the B1 domain) to that of mutants designed to disrupt binding to sites 1 and 2, using gel filtration, BIAcore surface plasmon resonance, fluorescence titration, and solid-phase radioimmunoassays. Gel filtration experiments show that PLW binds kappa both in 1:1 complexes and multivalently, consistent with two binding sites. Covalent dimers of the A20C and V51C mutants of PLW were prepared to eliminate site 1 and site 2 binding, respectively; both the A20C and V51C dimers bind kappa in 1:1 complexes and multivalently, indicating that neither site 1 nor site 2 is solely responsible for kappa binding. The A20R mutant was designed computationally to eliminate site 1 binding while preserving site 2 binding; consistent with this design, the A20R mutant binds kappa in 1:1 complexes but not multivalently. To probe the contributions of amino acid side chains to binding, we prepared 75 point mutants spanning nearly every residue of PLW; BIAcore studies of these mutants revealed two binding-energy "hot spots" consistent with sites 1 and 2. These data indicate that PLW binds kappa at both sites with similar affinities (high nanomolar), with the strongest contributions to the binding energy from Tyr34 (site 2) and Tyr36 (site 1). Compared to other protein-protein complexes, the binding is insensitive to amino acid substitutions at these sites, consistent with the large number of main chain interactions relative to side chain interactions. The strong binding of protein L to Ig kappa light chains of various species may result from the ambidextrous binding of the B1-B5 domains and the unimportance of specific side chain interactions.

The 2003 Carl A Moyer Award: real-time metabolic monitors, ischemia-reperfusion, titration endpoints, and ultraprecise burn resuscitation

Real-time metabolic monitoring of varied vascular beds provides the raw data necessary to conduct ultraprecise burn shock resuscitation based on second-by-second assessment of regional tissue perfusion. It also illustrates shortcomings of current clinical practices. Arterial base deficit was continuously monitored during 11 clinical resuscitations of patients suffering burn shock using a Paratrend monitor. Separately, in a 30% TBSA rat burn model (N = 70), three Paratrend monitors simultaneously recorded arterial blood gas and tissue pCO2 of the burn wound and colonic mucosa during resuscitation at 0, 2, 4, 6, and 8 ml/kg/%TBSA. Paratrend data were analyzed in conjunction with previously reported laser Doppler images of actual burn wound capillary perfusion. With current clinical therapy, continuous monitoring of arterial base deficit revealed repetitive cycles of resolution/worsening/resolution during burn shock resuscitation. In the rat model, tissue pCO2 in both burn wounds and splanchnic circulation differed depending on the rate of fluid resuscitation (P <.01 between sham and 0 ml/kg/%TBSA and between 2 ml/kg/%TBSA and 4 ml/kg/%TBSA). Burn wound pCO2 values correlated well with laser Doppler determination of actual capillary perfusion (rho = -.48, P <.01). The following conclusions were reached: 1). Gratuitous and repetitive ischemia-reperfusion-ischemia cycles plague current clinical therapy as demonstrated by numerous "false starts" in the resolution of arterial base deficit; 2). in a rat model, real-time monitoring of burn wound and splanchnic pCO2 demonstrate a dose-response relationship with rate of fluid administration; and 3). burn wound and splanchnic pCO2 are highly correlated with direct measurement of burn wound capillary perfusion by laser Doppler imager. Either technique can serve as a resuscitation endpoint for real-time feedback-controlled ultraprecise resuscitation.

Computational alanine scanning of protein-protein interfaces

Protein-protein interactions are key components of all signal transduction processes, so methods to alter these interactions promise to become important tools in dissecting function of connectivities in these networks. We have developed a fast computational approach for the prediction of energetically important amino acid residues in protein-protein interfaces (available at http://robetta.bakerlab.org/alaninescan), which we, following Peter Kollman, have termed "computational alanine scanning." The input consists of a three-dimensional structure of a protein-protein complex; output is a list of "hot spots," or amino acid side chains that are predicted to significantly destabilize the interface when mutated to alanine, analogous to the results of experimental alanine-scanning mutagenesis. 79% of hot spots and 68% of neutral residues were correctly predicted in a test of 233 mutations in 19 protein-protein complexes. A single interface can be analyzed in minutes. The computational methodology has been validated by the successful design of protein interfaces with new specificity and activity, and has yielded new insights into the mechanisms of receptor specificity and promiscuity in biological systems.

Automated prediction of CASP-5 structures using the Robetta server

Robetta is a fully automated protein structure prediction server that uses the Rosetta fragment-insertion method. It combines template-based and de novo structure prediction methods in an attempt to produce high quality models that cover every residue of a submitted sequence. The first step in the procedure is the automatic detection of the locations of domains and selection of the appropriate modeling protocol for each domain. For domains matched to a homolog with an experimentally characterized structure by PSI-BLAST or Pcons2, Robetta uses a new alignment method, called K*Sync, to align the query sequence onto the parent structure. It then models the variable regions by allowing them to explore conformational space with fragments in fashion similar to the de novo protocol, but in the context of the template. When no structural homolog is available, domains are modeled with the Rosetta de novo protocol, which allows the full length of the domain to explore conformational space via fragment-insertion, producing a large decoy ensemble from which the final models are selected. The Robetta server produced quite reasonable predictions for targets in the recent CASP-5 and CAFASP-3 experiments, some of which were at the level of the best human predictions.

Accurate computer-based design of a new backbone conformation in the second turn of protein L

The rational design of loops and turns is a key step towards creating proteins with new functions. We used a computational design procedure to create new backbone conformations in the second turn of protein L. The Protein Data Bank was searched for alternative turn conformations, and sequences optimal for these turns in the context of protein L were identified using a Monte Carlo search procedure and an energy function that favors close packing. Two variants containing 12 and 14 mutations were found to be as stable as wild-type protein L. The crystal structure of one of the variants has been solved at a resolution of 1.9 A, and the backbone conformation in the second turn is remarkably close to that of the in silico model (1.1 A RMSD) while it differs significantly from that of wild-type protein L (the turn residues are displaced by an average of 7.2 A). The folding rates of the redesigned proteins are greater than that of the wild-type protein and in contrast to wild-type protein L the second beta-turn appears to be formed at the rate limiting step in folding.

Microvascular assessment of burn depth conversion during varying resuscitation conditions

Conversion of partial- to full-thickness injuries, even after the burning has stopped, remains a significant clinical problem. We developed a rat model with a wide range of burn depths to study this phenomenon by microvascular assessment. Fifty-four male Sprague-Dawley rats weighing 460 g on average were studied. Real-time tissue monitoring of pH, paCO2, and paO2 was achieved by placement of a continuous blood gas monitor transducer in the aorta. Ten, 2-cm x 2-cm burns were created on each animal with milled aluminum templates (100 degrees C) with varying contact times. Conversion of burn depth in these wounds was documented by serial laser Doppler imager scanning over a 5-hour period. Animals received Ringer's lactate resuscitation at 0, 2, 4, 6, and 8 ml/kg/%burn. Serial laser Doppler scanning directly demonstrated progressive loss of perfusion to partial-thickness burns dependent upon the amount of fluid resuscitation. Conversion of partial- to full-thickness burns in this rat model (documented by laser Doppler microvascular assessment) was dependent upon how the animals were resuscitated.

Single-site mutations induce 3D domain swapping in the B1 domain of protein L from Peptostreptococcus magnus

BACKGROUND

Thermodynamic and kinetic studies of the Protein L B1 domain (Ppl) suggest a folding pathway in which, during the folding transition, the first beta hairpin is formed while the second beta hairpin and the alpha helix are largely unstructured. The same mutations in the two beta turns have opposite effects on the folding and unfolding rates. Three of the four residues composing the second beta turn in Ppl have consecutive positive phi angles, indicating strain in the second beta turn.

RESULTS

We have determined the crystal structures of the beta turn mutants G55A, K54G, and G15A, as well as a core mutant, V49A, in order to investigate how backbone strain affects the overall structure of Ppl. Perturbation of the hydrophobic interactions at the closed interface by the V49A mutation triggered the domain swapping of the C-terminal beta strand that relieved the strain in the second beta turn. Interestingly, the asymmetric unit of V49A contains two monomers and one domain-swapped dimer. The G55A mutation escalated the strain in the second beta turn, and this increased strain shifted the equilibrium toward the domain-swapped dimer. The K54G structure revealed that the increased stability is due to the reduction of strain in the second beta turn, while the G15A structure showed that increased strain alone is insufficient to trigger domain swapping.

CONCLUSIONS

Domain swapping in Ppl is determined by the balance of two opposing components of the free energy. One is the strain in the second beta turn that favors the dimer, and the other is the entropic cost of dimer formation that favors the monomer. A single-site mutation can disrupt this balance and trigger domain swapping.

Conversion of monomeric protein L to an obligate dimer by computational protein design

Protein L consists of a single alpha-helix packed on a four-stranded beta-sheet formed by two symmetrically opposed beta-hairpins. We use a computer-based protein design procedure to stabilize a domain-swapped dimer of protein L in which the second beta-turn straightens and the C-terminal strand inserts into the beta-sheet of the partner. The designed obligate dimer contains three mutations (A52V, N53P, and G55A) and has a dissociation constant of approximately 700 pM, which is comparable to the dissociation constant of many naturally occurring protein dimers. The structure of the dimer has been determined by x-ray crystallography and is close to the in silico model.

The kinetic pathway of RNA binding to the Escherichia coli transcription termination factor Rho

The Escherichia coli transcription termination factor Rho is structurally and functionally homologous to hexameric helicases that assemble into ring structures. Using stopped-flow fluorescence and presteady-state ATPase kinetics, we have determined the kinetic pathway of poly(C) RNA binding to Rho hexamer, both in the presence and in absence of ATP. These studies indicate a four-step sequential mechanism of RNA binding and reveal the respective roles of the primary and secondary RNA binding sites in initiation and ATPase activation of Rho. The primary RNA binding sites of Rho hexamer interact with poly(C) RNA at a diffusion-limited rate constant close to 8 x 10(8) m(-1) s(-1), resulting in the Rho-RNA species PR1, which subsequently isomerizes to PR2 with a rate constant 21 s(-1). The PR2 isomerizes to PR3 with a rate constant of 32 s(-1) in the presence of ATP, and the formation of PR4 from PR3 results in a species that is fully competent in hydrolyzing ATP at the RNA-stimulated rate. The PR3 to PR4 isomerization occurs at a relatively slow rate of 4.1 s(-1); thus, the presteady-state ATPase kinetics show a distinct lag due to the slow initiation step. The interactions of the RNA with the primary sites trigger ring opening, and we propose that during the last two steps, the RNA migrates into the central channel and interacts with the secondary sites, resulting in the activation of the ATPase activity. The primary RNA binding sites, in addition to promoting sequence specific initiation, kinetically facilitate loading of the RNA into the secondary sites, which are relatively inaccessible, since they are present in the central channel. These studies reveal common features used by hexameric helicases to bind nucleic acids in an efficient and specific manner.

Sensory dermatomal representation in the medial lemniscus

BACKGROUND

Restricted sensory deficits along the somatotopic topography of the medial lemniscus rarely develop in medial medullary infarction. We describe a patient with medial medullary infarction who presented with dermatomal sensory deficits caused by a medial lemniscal lesion.

CASE DESCRIPTION

A 58-year-old man presented with sudden right-sided hemiparesis and paresthesia. He had noticed the paresthesia below the level of the right L5 dermatome, where his vibration and position senses were mildly diminished. His paresthesia was more severe over the right calf and foot. Magnetic resonance images of the brain showed an acute small infarct in the medial-ventral portion of the left rostral medulla oblongata. A nerve conduction study and electromyography showed no abnormalities. At follow-up, the patient's motor and sensory deficits had improved considerably.

CONCLUSIONS

The patient showed lemniscal sensory deficits below the right L5 dermatome that were caused by the partial involvement of the medial lemniscus. These findings suggest that lemniscal sensory dermatomal representation is preserved at least up to the level of the medulla oblongata.

Structures of the B1 domain of protein L from Peptostreptococcus magnus with a tyrosine to tryptophan substitution

The three-dimensional structure of a tryptophan-containing variant of the IgG-binding B1 domain of protein L has been solved in two crystal forms to 1.7 and 1.8 A resolution. In one of the crystal forms, the entire N-terminal histidine-tag region was immobilized through the coordination of zinc ions and its structural conformation along with the zinc coordination scheme were determined. However, the ordering of the histidine tag by zinc does not affect the overall structure of the rest of the protein. Structural comparisons of the tryptophan-containing variant with an NMR-derived wild-type structure, which contains a tyrosine at position 47, reveals a common fold, although the overall backbone root-mean-square difference is 1.5 A. The Y47W substitution only caused local rearrangement of several side chains, the most prominent of which is the rotation of the Tyr34 side chain, resulting in a 6 A displacement of its hydroxyl group. A small methyl-sized cavity bounded by beta-strands 1, 2 and 4 and the alpha-helix was found in the structures of the Y47W-substituted protein L B1 domain. This cavity may be created as the result of subsequent side-chain rearrangements caused by the Y47W substitution. These high-resolution structures of the tryptophan-containing variant provide a reference frame for the analysis of thermodynamic and kinetic data derived from a series of mutational studies of the protein L B1 domain.

Cerebral venous thrombosis associated with tentorial subdural hematoma during oxymetholone therapy

Androgen was reported to cause cerebral venous thrombosis (CVT) during replacement therapy for aplastic anemia. Oxymetholone, a synthetic androgen analogue, has been widely used in the treatment of aplastic anemia. A 40-year-old woman with aplastic anemia visited our hospital because of severe headache, nausea, vomiting, blurred vision and diplopia for a period of 1 month. She had taken oxymetholone for 2 years. Neurological examination revealed bilateral papilledema and bilateral sixth nerve palsies. Brain magnetic resonance imaging (MRI), performed at the time of admission, demonstrated left-sided tentorial SDH, and focal cerebral thrombosis of the left superficial sylvian vein and sigmoid sinus. MR venography revealed multiple irregularities in the superior sagittal sinus and left transverse sinus. CVT with tentorial subdural hematoma (SDH) caused by oxymetholone was strongly suggested. Oxymetholone was immediately discontinued, and her symptoms and signs disappeared. Because of the thrombocytopenia, anticoagulation was not started. She was discharged and visited the outpatient clinic without neurological symptoms for 6 months. This report supports the cautions given about the risk of CVT with oxymetholone supplementation in aplastic anemia. To the best of our knowledge, this is the first report of CVT associated with tentorial SDH that was probably caused by oxymetholone.

The p38 mitogen-activated protein kinase pathway regulates interleukin-6 synthesis in response to tumor necrosis factor in osteoblasts

The induction of interleukin-6 (IL-6), using a proinflammatory cytokine (tumor necrosis factor-alpha), was studied in a human osteoblast cell line (MG-63) in relation to p38 mitogen-activated protein kinase (MAPK) and nuclear factor (NF)-kappaB transcription factor. When added to MG-63 cells, tumor necrosis factor-alpha (TNF-alpha) had a stimulatory effect on the production of IL-6, and this elevation was significantly reduced by SB203580, a specific p38 MAPK inhibitor. In addition, the stimulation of IL-6 release was also reduced by pyrrolidine dithiocarbamate (PDTC) or NF-kappaB SN50, which has been reported to be a potent NF-kappaB inhibitor. Both the NF-kappaB inhibitors in the presence of SB203580 had a more inhibitory effect on IL-6 release. In this study, TNF-alpha stimulated NF-kappaB binding affinity as well as p38 MAP kinase activation, leading to the release of IL-6. However, the specific inhibitor of p38 MAPK, SB203580, had no effect on TNF-alpha-induced NF-kappaB activation and both NF-kappaB inhibitors failed to reduce the p38 MAPK activation in the TNF-alpha-stimulated osteoblasts. In addition, inhibition of p38 MAPK partially, but significantly, impaired TNF-alpha-regulated release of osteocalcin, an important differentiation marker in osteoblasts. These results strongly suggest that both p38 MAPK and NF-kappaB are required in TNF-alpha-induced IL-6 synthesis and that these two TNF-alpha-activated pathways can be primarily dissociated. Furthermore, p38 MAPK may play a significant role in differentiation in MG-63 cells.

Scrub typhus encephalomyelitis with prominent focal neurologic signs

BACKGROUND

Encephalomyelitis with prominent focal neurologic signs and associated neuroradiologic abnormalities has not been previously described in scrub typhus.

CASE DESCRIPTION

A 22-year-old woman was admitted because of fever and an altered mental state. Neurologic examination revealed bilateral sixth and seventh nerve palsies, bilateral gaze evoked nystagmus, anarthria, dysphagia, quadriparesis, and sensory level at T1. Serum and cerebrospinal fluid samples were positive for tsutsugamushi antibody. The patient's magnetic resonance images demonstrated the lesions responsible for the neurologic dysfunctions: in the lower brainstem, cerebellar peduncles, and spinal cord. It was interesting that the gray matter of the spinal cord was predominantly involved.

CONCLUSIONS

The recognition of unusual manifestations and the clinical suspicion of this treatment-responsive disease may be important, particularly in the face of increasing international and intranational travel.

Reversed current structure in a Z-pinch plasma

The current profile of a Z-pinch plasma is investigated using a one-dimensional magnetohydrodynamic code. Simulation results reveal the formation of a reversed current profile, its propagation, and an ejection of plasma at boundary region, which have been observed in previous experiments. A new physical mechanism is proposed to account for such phenomena. The physical mechanism involves the propagation of a shock wave. It is found that a reversed current profile appears when a shock wave reflected at axis expands in a compressing plasma column.

Mechanism of mitogenic effect of fluoride on fetal rat osteoblastic cells: evidence for Shc, Grb2 and P-CREB-dependent pathways

Fluoride stimulates bone cell proliferation and nodule formation in fetal rat calvarial osteoblastic cells. In addition, fluoride enhances alkaline phosphatase activity, a marker of osteoblastic differentiation, in a dose-dependent manner. The effects of fluoroalumino complex (AlFx) on cell proliferation and differentiation were markedly reduced by tyrosine kinase inhibitor; 1 mM genistein or 1 microg/ml herbimycin. It suggests that tyrosine kinase-mediated mitogenic signaling involves a series of protein-protein interactions between tyrosine-phosphorylated receptors, Shc and Grb2, resulting in an AlFx-induced mitogenic effect. The results indicate that AlFx dose-dependently enhances the tyrosine phosphorylation of the adaptor molecule Shc (p52) and its association with Grb2 in the tyrosine kinase mediated pathway. In addition, AlFx decreases the phosphorylation level of CREB without any change on the amount of CREB protein. Taken together, the results suggest that adaptor proteins, including Shc and Grb2 of the protein tyrosine kinase cascade are implicated in fluoride-induced mitogenic activity of fetal rat calvarial osteoblastic cells. Furthermore, CREB which passes signals from cAMP to transcriptional factor CRE, modulates the fluoroaluminate-induced metabolism of bone cells via a decrease of phosphorylation level.