The Energy Landscape, Folding Pathways and the Kinetics of a Knotted Protein

The folding pathway and rate coefficients of the folding of a knotted protein are calculated for a potential energy function with minimal energetic frustration. A kinetic transition network is constructed using the discrete path sampling approach, and the resulting potential energy surface is visualized by constructing disconnectivity graphs. Owing to topological constraints, the low-lying portion of the landscape consists of three distinct regions, corresponding to the native knotted state and to configurations where either the N- or C-terminus is not yet folded into the knot. The fastest folding pathways from denatured states exhibit early formation of the N-terminus portion of the knot and a rate-determining step where the C-terminus is incorporated. The low-lying minima with the N-terminus knotted and the C-terminus free therefore constitute an off-pathway intermediate for this model. The insertion of both the N- and C-termini into the knot occur late in the folding process, creating large energy barriers that are the rate limiting steps in the folding process. When compared to other protein folding proteins of a similar length, this system folds over six orders of magnitude more slowly.Comment: 19 page

Small but crucial : the novel small heat shock protein Hsp21 mediates stress adaptation and virulence in Candida albicans

Peer reviewedPublisher PD

Measurement of the branching fraction and CP content for the decay B(0) -> D(*+)D(*-)

This is the pre-print version of the Article. The official published version can be accessed from the links below. Copyright @ 2002 APS.We report a measurement of the branching fraction of the decay B0→D*+D*- and of the CP-odd component of its final state using the BABAR detector. With data corresponding to an integrated luminosity of 20.4  fb-1 collected at the Υ(4S) resonance during 1999–2000, we have reconstructed 38 candidate signal events in the mode B0→D*+D*- with an estimated background of 6.2±0.5 events. From these events, we determine the branching fraction to be B(B0→D*+D*-)=[8.3±1.6(stat)±1.2(syst)]×10-4. The measured CP-odd fraction of the final state is 0.22±0.18(stat)±0.03(syst).This work is supported by DOE and NSF (USA), NSERC (Canada), IHEP (China), CEA and CNRS-IN2P3 (France), BMBF (Germany), INFN (Italy), NFR (Norway), MIST (Russia), and PPARC (United Kingdom). Individuals have received support from the A.P. Sloan Foundation, Research Corporation, and Alexander von Humboldt Foundation

Measurement of D-s(+) and D-s(*+) production in B meson decays and from continuum e(+)e(-) annihilation at √s=10.6 GeV

This is the pre-print version of the Article. The official published version can be accessed from the links below. Copyright @ 2002 APSNew measurements of Ds+ and Ds*+ meson production rates from B decays and from qq̅ continuum events near the Υ(4S) resonance are presented. Using 20.8 fb-1 of data on the Υ(4S) resonance and 2.6 fb-1 off-resonance, we find the inclusive branching fractions B(B⃗Ds+X)=(10.93±0.19±0.58±2.73)% and B(B⃗Ds*+X)=(7.9±0.8±0.7±2.0)%, where the first error is statistical, the second is systematic, and the third is due to the Ds+→φπ+ branching fraction uncertainty. The production cross sections σ(e+e-→Ds+X)×B(Ds+→φπ+)=7.55±0.20±0.34pb and σ(e+e-→Ds*±X)×B(Ds+→φπ+)=5.8±0.7±0.5pb are measured at center-of-mass energies about 40 MeV below the Υ(4S) mass. The branching fractions ΣB(B⃗Ds(*)+D(*))=(5.07±0.14±0.30±1.27)% and ΣB(B⃗Ds*+D(*))=(4.1±0.2±0.4±1.0)% are determined from the Ds(*)+ momentum spectra. The mass difference m(Ds+)-m(D+)=98.4±0.1±0.3MeV/c2 is also measured.This work was supported by DOE and NSF (USA), NSERC (Canada), IHEP (China), CEA and CNRS-IN2P3 (France), BMBF (Germany), INFN (Italy), NFR (Norway), MIST (Russia), and PPARC (United Kingdom). Individuals have received support from the Swiss NSF, A. P. Sloan Foundation, Research Corporation, and Alexander von Humboldt Foundation

Protein Diffusion in Mammalian Cell Cytoplasm

We introduce a new method for mesoscopic modeling of protein diffusion in an entire cell. This method is based on the construction of a three-dimensional digital model cell from confocal microscopy data. The model cell is segmented into the cytoplasm, nucleus, plasma membrane, and nuclear envelope, in which environment protein motion is modeled by fully numerical mesoscopic methods. Finer cellular structures that cannot be resolved with the imaging technique, which significantly affect protein motion, are accounted for in this method by assigning an effective, position-dependent porosity to the cell. This porosity can also be determined by confocal microscopy using the equilibrium distribution of a non-binding fluorescent protein. Distinction can now be made within this method between diffusion in the liquid phase of the cell (cytosol/nucleosol) and the cytoplasm/nucleoplasm. Here we applied the method to analyze fluorescence recovery after photobleach (FRAP) experiments in which the diffusion coefficient of a freely-diffusing model protein was determined for two different cell lines, and to explain the clear difference typically observed between conventional FRAP results and those of fluorescence correlation spectroscopy (FCS). A large difference was found in the FRAP experiments between diffusion in the cytoplasm/nucleoplasm and in the cytosol/nucleosol, for all of which the diffusion coefficients were determined. The cytosol results were found to be in very good agreement with those by FCS

Dinucleotide controlled null models for comparative RNA gene prediction

<p>Abstract</p> <p>Background</p> <p>Comparative prediction of RNA structures can be used to identify functional noncoding RNAs in genomic screens. It was shown recently by Babak <it>et al</it>. [BMC Bioinformatics. 8:33] that RNA gene prediction programs can be biased by the genomic dinucleotide content, in particular those programs using a thermodynamic folding model including stacking energies. As a consequence, there is need for dinucleotide-preserving control strategies to assess the significance of such predictions. While there have been randomization algorithms for single sequences for many years, the problem has remained challenging for multiple alignments and there is currently no algorithm available.</p> <p>Results</p> <p>We present a program called SISSIz that simulates multiple alignments of a given average dinucleotide content. Meeting additional requirements of an accurate null model, the randomized alignments are on average of the same sequence diversity and preserve local conservation and gap patterns. We make use of a phylogenetic substitution model that includes overlapping dependencies and site-specific rates. Using fast heuristics and a distance based approach, a tree is estimated under this model which is used to guide the simulations. The new algorithm is tested on vertebrate genomic alignments and the effect on RNA structure predictions is studied. In addition, we directly combined the new null model with the RNAalifold consensus folding algorithm giving a new variant of a thermodynamic structure based RNA gene finding program that is not biased by the dinucleotide content.</p> <p>Conclusion</p> <p>SISSIz implements an efficient algorithm to randomize multiple alignments preserving dinucleotide content. It can be used to get more accurate estimates of false positive rates of existing programs, to produce negative controls for the training of machine learning based programs, or as standalone RNA gene finding program. Other applications in comparative genomics that require randomization of multiple alignments can be considered.</p> <p>Availability</p> <p>SISSIz is available as open source C code that can be compiled for every major platform and downloaded here: <url>http://sourceforge.net/projects/sissiz</url>.</p

Psychological and behavioural factors associated with sexual risk behaviour among Slovak students

Background: Knowledge about the prevalence of sexual risk behaviour (SRB) in adolescence is needed to prevent unwanted health consequences. Studies on SRB among adolescents in Central Europe are rare and mostly rely on a single indicator for SRB. This study aims to assess the association of behavioural and psychological factors with three types of SRB in adolescents in Central Europe. Methods: We obtained data on behavioural factors (having been drunk during previous month, smoking during previous week, early sexual initiation), psychological factors (self-esteem, wellbeing, extroversion, neuroticism, religiousness), and SRB (intercourse under risky conditions, multiple sexual partners, and inconsistent condom use) in 832 Slovak university students (response 94.3%). Results: Among those with sexual experience (62%), inconsistent condom use was the most prevalent risk behaviour (81% in females, 72% in males). With the exception of having been drunk in males, no factor was associated with inconsistent condom use. Regarding the other types of SRB, early sexual initiation was most strongly associated. In addition, other, mostly behavioural, factors were associated, in particular having been drunk. Conclusion: Results suggest that behavioural factors are more closely related to SRB than psychological factors. Associations differ by type of SRB and gender but offer few clues to target risk groups for inconsistent condom use. Results show a high need for health-promotion programmes in early adolescence that target SRB in conjunction with other health risk behaviours such as alcohol abuse

High school drinking mediates the relationship between parental monitoring and college drinking: A longitudinal analysis

<p>Abstract</p> <p>Background</p> <p>College drinking is a significant public health problem. Although parental monitoring and supervision reduces the risk for alcohol consumption among younger adolescents, few studies have investigated the impact of earlier parental monitoring on later college drinking. This study examined whether parental monitoring indirectly exerts a protective effect on college drinking by reducing high school alcohol consumption.</p> <p>Methods</p> <p>A longitudinal cohort of 1,253 male and female students, ages 17 to 19, attending a large, public, mid-Atlantic university was studied at two time points. First, data on high school parental monitoring and alcohol consumption were gathered via questionnaire during the summer prior to college entry. Second, during the first year of college, past-year alcohol consumption was measured via a personal interview. Multiple regression models tested the relationship between parental monitoring and past year alcohol use (i.e., number of drinks per drinking day).</p> <p>Results</p> <p>Holding constant demographics, SAT score, and religiosity, parental monitoring had a significant protective effect on both high school and college drinking level. However, the association between parental monitoring and college drinking level became non-significant once high school drinking level was held constant.</p> <p>Conclusion</p> <p>While parental monitoring did not directly influence college alcohol consumption, evidence for mediation was observed, whereby parental monitoring had an indirect influence on college drinking through reductions in high school drinking. Initiatives that promote effective parenting might be an important strategy to curb high-risk drinking among older adolescents. More research is needed to understand the nature and degree of parent-child communication that is necessary to extend the protective influence of parents into the college years.</p

Potential applications of nanotechnology in thermochemical conversion of microalgal biomass

The rapid decrease in fossil reserves has significantly increased the demand of renewable and sustainable energy fuel resources. Fluctuating fuel prices and significant greenhouse gas (GHG) emission levels have been key impediments associated with the production and utilization of nonrenewable fossil fuels. This has resulted in escalating interests to develop new and improve inexpensive carbon neutral energy technologies to meet future demands. Various process options to produce a variety of biofuels including biodiesel, bioethanol, biohydrogen, bio-oil, and biogas have been explored as an alternative to fossil fuels. The renewable, biodegradable, and nontoxic nature of biofuels make them appealing as alternative fuels. Biofuels can be produced from various renewable resources. Among these renewable resources, algae appear to be promising in delivering sustainable energy options. Algae have a high carbon dioxide (CO2) capturing efficiency, rapid growth rate, high biomass productivity, and the ability to grow in non-potable water. For algal biomass, the two main conversion pathways used to produce biofuel include biochemical and thermochemical conversions. Algal biofuel production is, however, challenged with process scalability for high conversion rates and high energy demands for biomass harvesting. This affects the viable achievement of industrial-scale bioprocess conversion under optimum economy. Although algal biofuels have the potential to provide a sustainable fuel for future, active research aimed at improving upstream and downstream technologies is critical. New technologies and improved systems focused on photobioreactor design, cultivation optimization, culture dewatering, and biofuel production are required to minimize the drawbacks associated with existing methods. Nanotechnology has the potential to address some of the upstream and downstream challenges associated with the development of algal biofuels. It can be applied to improve system design, cultivation, dewatering, biomass characterization, and biofuel conversion. This chapter discusses thermochemical conversion of microalgal biomass with recent advances in the application of nanotechnology to enhance the development of biofuels from algae. Nanotechnology has proven to improve the performance of existing technologies used in thermochemical treatment and conversion of biomass. The different bioprocess aspects, such as reactor design and operation, analytical techniques, and experimental validation of kinetic studies, to provide insights into the application of nanotechnology for enhanced algal biofuel production are addressed

Diastolic dysfunction in diabetes and the metabolic syndrome: promising potential for diagnosis and prognosis

Cardiac disease in diabetes mellitus and in the metabolic syndrome consists of both vascular and myocardial abnormalities. The latter are characterised predominantly by diastolic dysfunction, which has been difficult to evaluate in spite of its prevalence. While traditional Doppler echocardiographic parameters enable only semiquantitative assessment of diastolic function and cannot reliably distinguish perturbations in loading conditions from altered diastolic functions, new technologies enable detailed quantification of global and regional diastolic function. The most readily available technique for the quantification of subclinical diastolic dysfunction is tissue Doppler imaging, which has been integrated into routine contemporary clinical practice, whereas cine magnetic resonance imaging (CMR) remains a promising complementary research tool for investigating the molecular mechanisms of the disease. Diastolic function is reported to vary linearly with age in normal persons, decreasing by 0.16 cm/s each year. Diastolic function in diabetes and the metabolic syndrome is determined by cardiovascular risk factors that alter myocardial stiffness and myocardial energy availability/bioenergetics. The latter is corroborated by the improvement in diastolic function with improvement in metabolic control of diabetes by specific medical therapy or lifestyle modification. Accordingly, diastolic dysfunction reflects the structural and metabolic milieu in the myocardium, and may allow targeted therapeutic interventions to modulate cardiac metabolism to prevent heart failure in insulin resistance and diabetes