280 research outputs found
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
Alcohol prevention at sporting events: study protocol for a quasi-experimental control group study
Survival endpoints in colorectal cancer and the effect of second primary other cancer on disease free survival
<p>Abstract</p> <p>Background</p> <p>In cancer research the selection and definitions of survival endpoints are important and yet they are not used consistently. The aim of this study was to compare different survival endpoints in patients with primary colorectal cancer (CRC) and to understand the effect of second primary other cancer on disease-free survival (DFS) calculations.</p> <p>Methods</p> <p>A population-based cohort of 415 patients with CRC, 332 of whom were treated with curative intention between the years 2000-2003, was analysed. Events such as locoregional recurrence, distant metastases, second primary cancers, death, cause of death and loss to follow-up were recorded. Different survival endpoints, including DFS, overall survival, cancer-specific survival, relapse-free survival, time to treatment failure and time to recurrence were compared and DFS was calculated with and without inclusion of second primary other cancers.</p> <p>Results</p> <p>The events that occurred most often in patients treated with curative intention were non-cancer-related death (n = 74), distant metastases (n = 66) and death from CRC (n = 59). DFS was the survival endpoint with most events (n = 170) followed by overall survival (n = 144) and relapse-free survival (n = 139). Fewer events were seen for time to treatment failure (n = 80), time to recurrence (n = 68) and cancer-specific survival (n = 59). Second primary other cancer occurred in 26 patients and its inclusion as an event in DFS calculations had a detrimental effect on the survival. The DFS for patients with stage I-III disease was 62% after 5 years if second primary other cancer was not included as an event, compared with 58% if it was. However, the difference was larger for stage II (68 vs 60%) than for stage III (49 vs 47%).</p> <p>Conclusions</p> <p>The inclusion of second primary other cancer as an endpoint in DFS analyses significantly alters the DFS for patients with CRC. Researchers and journals must clearly define survival endpoints in all trial protocols and published manuscripts.</p
The regions within the N-terminus critical for human glucagon like peptide-1 receptor (hGLP-1R) cell Surface expression
The hGLP-1R is a target for the treatment of type 2 diabetes and belongs to the class B family of GPCRs. Like other class B GPCRs, the GLP-1R contains an N-terminal signal peptide (SP) and undergoes N-linked glycosylation, which are important for its trafficking and maturation. This study analysed the role of the SP, the hydrophobic region after the SP (HRASP), glycosylation and the conserved residues within the N-terminus in GLP-1R trafficking. HGLP-1R targeted to the cell surface showed no SP, and the SP deleted mutant, but not the mutants defective in SP cleavage, showed cell surface expression, demonstrating the importance of SP cleavage for hGLP-1R cell surface expression. The N-terminal deletions of hGLP-1R revealed that the HRASP, not the SP, is essential for cell surface expression of GLP-1R. Further, inhibition of hGLP-1R glycosylation prevented cell surface expression of the receptor. Mutation of Trp39, Tyr69 and Tyr88, which are required for agonist binding, in the GLP-1R abolished cell surface expression of the receptor independent of the SP cleavage or N-linked glycosylation. In conclusion, the N-terminus of hGLP-1R regulates receptor trafficking and maturation. Therefore this study provides insight into the role of hGLP-1R N-terminus on the receptor cell surface expression
A structural annotation resource for the selection of putative target proteins in the malaria parasite
<p>Abstract</p> <p>Background</p> <p>Protein structure plays a pivotal role in elucidating mechanisms of parasite functioning and drug resistance. Moreover, protein structure aids the determination of protein function, which can together with the structure be used to identify novel drug targets in the parasite. However, various structural features in <it>Plasmodium falciparum </it>proteins complicate the experimental determination of protein structures. Limited similarity to proteins in the Protein Data Bank and the shortage of solved protein structures in the malaria parasite necessitate genome-scale structural annotation of <it>P. falciparum </it>proteins. Additionally, the annotation of a range of structural features facilitates the identification of suitable targets for experimental and computational studies.</p> <p>Methods</p> <p>An integrated structural annotation system was developed and applied to <it>P. falciparum</it>, <it>Plasmodium vivax </it>and <it>Plasmodium yoelii</it>. The annotation included searches for sequence similarity, patterns and domains in addition to the following predictions: secondary structure, transmembrane helices, protein disorder, low complexity, coiled-coils and small molecule interactions. Subsequently, candidate proteins for further structural studies were identified based on the annotated structural features.</p> <p>Results</p> <p>The annotation results are accessible through a web interface, enabling users to select groups of proteins which fulfil multiple criteria pertaining to structural and functional features <abbrgrp><abbr bid="B1">1</abbr></abbrgrp>. Analysis of features in the <it>P. falciparum </it>proteome showed that protein-interacting proteins contained a higher percentage of predicted disordered residues than non-interacting proteins. Proteins interacting with 10 or more proteins have a disordered content concentrated in the range of 60–100%, while the disorder distribution for proteins having only one interacting partner, was more evenly spread.</p> <p>Conclusion</p> <p>A series of <it>P. falciparum </it>protein targets for experimental structure determination, comparative modelling and <it>in silico </it>docking studies were putatively identified. The system is available for public use, where researchers may identify proteins by querying with multiple physico-chemical, sequence similarity and interaction features.</p
In-Silico Patterning of Vascular Mesenchymal Cells in Three Dimensions
Cells organize in complex three-dimensional patterns by interacting with proteins along with the surrounding extracellular matrix. This organization provides the mechanical and chemical cues that ultimately influence a cell's differentiation and function. Here, we computationally investigate the pattern formation process of vascular mesenchymal cells arising from their interaction with Bone Morphogenic Protein-2 (BMP-2) and its inhibitor, Matrix Gla Protein (MGP). Using a first-principles approach, we derive a reaction-diffusion model based on the biochemical interactions of BMP-2, MGP and cells. Simulations of the model exhibit a wide variety of three-dimensional patterns not observed in a two-dimensional analysis. We demonstrate the emergence of three types of patterns: spheres, tubes, and sheets, and show that the patterns can be tuned by modifying parameters in the model such as the degradation rates of proteins and chemotactic coefficient of cells. Our model may be useful for improved engineering of three-dimensional tissue structures as well as for understanding three dimensional microenvironments in developmental processes.National Institutes of Health (U.S.) (GM69811)United States. Dept. of Energy (DOE CSGF fellowship
The Pioneer Anomaly
Radio-metric Doppler tracking data received from the Pioneer 10 and 11
spacecraft from heliocentric distances of 20-70 AU has consistently indicated
the presence of a small, anomalous, blue-shifted frequency drift uniformly
changing with a rate of ~6 x 10^{-9} Hz/s. Ultimately, the drift was
interpreted as a constant sunward deceleration of each particular spacecraft at
the level of a_P = (8.74 +/- 1.33) x 10^{-10} m/s^2. This apparent violation of
the Newton's gravitational inverse-square law has become known as the Pioneer
anomaly; the nature of this anomaly remains unexplained. In this review, we
summarize the current knowledge of the physical properties of the anomaly and
the conditions that led to its detection and characterization. We review
various mechanisms proposed to explain the anomaly and discuss the current
state of efforts to determine its nature. A comprehensive new investigation of
the anomalous behavior of the two Pioneers has begun recently. The new efforts
rely on the much-extended set of radio-metric Doppler data for both spacecraft
in conjunction with the newly available complete record of their telemetry
files and a large archive of original project documentation. As the new study
is yet to report its findings, this review provides the necessary background
for the new results to appear in the near future. In particular, we provide a
significant amount of information on the design, operations and behavior of the
two Pioneers during their entire missions, including descriptions of various
data formats and techniques used for their navigation and radio-science data
analysis. As most of this information was recovered relatively recently, it was
not used in the previous studies of the Pioneer anomaly, but it is critical for
the new investigation.Comment: 165 pages, 40 figures, 16 tables; accepted for publication in Living
Reviews in Relativit
A haplotype of polymorphisms in ASE-1, RAI and ERCC1 and the effects of tobacco smoking and alcohol consumption on risk of colorectal cancer: a danish prospective case-cohort study
<p>Abstract</p> <p>Background</p> <p>Single nucleotide polymorphisms (SNPs) are the most frequent type of genetic variation in the human genome, and are of interest for the study of susceptibility to and protection from diseases. The haplotype at chromosome 19q13.2-3 encompassing the three SNPs <it>ASE-1 </it>G-21A, <it>RAI </it>IVS1 A4364G and <it>ERCC1 </it>Asn118Asn have been associated with risk of breast cancer and lung cancer. Haplotype carriers are defined as the homozygous carriers of <it>RAI </it>IVS1 A4364G<sup>A</sup>, <it>ERCC1 </it>Asn118Asn<sup>T </sup>and <it>ASE-1 </it>G-21A<sup>G</sup>. We aimed to evaluate whether the three polymorphisms and the haplotype are associated to risk of colorectal cancer, and investigated gene-environment associations between the polymorphisms and the haplotype and smoking status at enrolment, smoking duration, average smoking intensity and alcohol consumption, respectively, in relation to risk of colorectal cancer.</p> <p>Methods</p> <p>Associations between the three individual polymorphisms, the haplotype and risk of colorectal cancer were examined, as well as gene-environment interaction, in a Danish case-cohort study including 405 cases and a comparison group of 810 persons. Incidence rate ratio (IRR) were estimated by the Cox proportional hazards model stratified according to gender, and two-sided 95% confidence intervals (CI) and p-values were calculated based on robust estimates of the variance-covariance matrix and Wald's test of the Cox regression parameter.</p> <p>Results</p> <p>No consistent associations between the three individual polymorphisms, the haplotype and risk of colorectal cancer were found. No statistically significant interactions between the genotypes and the lifestyle exposures smoking or alcohol consumption were observed.</p> <p>Conclusion</p> <p>Our results suggest that the <it>ASE-1 </it>G-21A, <it>RAI </it>IVS1 A4364G and <it>ERCC1 </it>Asn118Asn polymorphisms and the previously identified haplotype are not associated with risk of colorectal cancer. We found no evidence of gene-environment interaction between the three polymorphisms and the haplotype and smoking intensity and alcohol consumption, respectively, in relation to the risk of colorectal cancer.</p
Identification of Extracellular Segments by Mass Spectrometry Improves Topology Prediction of Transmembrane Proteins
Transmembrane proteins play crucial role in signaling, ion transport, nutrient uptake, as well as in maintaining the dynamic equilibrium between the internal and external environment of cells. Despite their important biological functions and abundance, less than 2% of all determined structures are transmembrane proteins. Given the persisting technical difficulties associated with high resolution structure determination of transmembrane proteins, additional methods, including computational and experimental techniques remain vital in promoting our understanding of their topologies, 3D structures, functions and interactions. Here we report a method for the high-throughput determination of extracellular segments of transmembrane proteins based on the identification of surface labeled and biotin captured peptide fragments by LC/MS/MS. We show that reliable identification of extracellular protein segments increases the accuracy and reliability of existing topology prediction algorithms. Using the experimental topology data as constraints, our improved prediction tool provides accurate and reliable topology models for hundreds of human transmembrane proteins
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