703 research outputs found
Predicting Secondary Structures, Contact Numbers, and Residue-wise Contact Orders of Native Protein Structure from Amino Acid Sequence by Critical Random Networks
Prediction of one-dimensional protein structures such as secondary structures
and contact numbers is useful for the three-dimensional structure prediction
and important for the understanding of sequence-structure relationship. Here we
present a new machine-learning method, critical random networks (CRNs), for
predicting one-dimensional structures, and apply it, with position-specific
scoring matrices, to the prediction of secondary structures (SS), contact
numbers (CN), and residue-wise contact orders (RWCO). The present method
achieves, on average, accuracy of 77.8% for SS, correlation coefficients
of 0.726 and 0.601 for CN and RWCO, respectively. The accuracy of the SS
prediction is comparable to other state-of-the-art methods, and that of the CN
prediction is a significant improvement over previous methods. We give a
detailed formulation of critical random networks-based prediction scheme, and
examine the context-dependence of prediction accuracies. In order to study the
nonlinear and multi-body effects, we compare the CRNs-based method with a
purely linear method based on position-specific scoring matrices. Although not
superior to the CRNs-based method, the surprisingly good accuracy achieved by
the linear method highlights the difficulty in extracting structural features
of higher order from amino acid sequence beyond that provided by the
position-specific scoring matrices.Comment: 20 pages, 1 figure, 5 tables; minor revision; accepted for
publication in BIOPHYSIC
Unique Interplay between Sugar and Lipid in Determining the Antigenic Potency of Bacterial Antigens for NKT Cells
Structural and biophysical studies reveal the induced-fit mechanism underlying the stringent specificity of invariant natural killer T cells for unique glycolipid antigens from the pathogen Streptococcus pneumoniae
Composite structural motifs of binding sites for delineating biological functions of proteins
Most biological processes are described as a series of interactions between
proteins and other molecules, and interactions are in turn described in terms
of atomic structures. To annotate protein functions as sets of interaction
states at atomic resolution, and thereby to better understand the relation
between protein interactions and biological functions, we conducted exhaustive
all-against-all atomic structure comparisons of all known binding sites for
ligands including small molecules, proteins and nucleic acids, and identified
recurring elementary motifs. By integrating the elementary motifs associated
with each subunit, we defined composite motifs which represent
context-dependent combinations of elementary motifs. It is demonstrated that
function similarity can be better inferred from composite motif similarity
compared to the similarity of protein sequences or of individual binding sites.
By integrating the composite motifs associated with each protein function, we
define meta-composite motifs each of which is regarded as a time-independent
diagrammatic representation of a biological process. It is shown that
meta-composite motifs provide richer annotations of biological processes than
sequence clusters. The present results serve as a basis for bridging atomic
structures to higher-order biological phenomena by classification and
integration of binding site structures.Comment: 34 pages, 7 figure
Airborne lipid antigens mobilize resident intravascular NKT cells to induce allergic airway inflammation
Resident intravascular NKT cells exacerbate airway hyperreactivity in mice dependent on dendritic cell co-presentation of glycolipid and peptide antigens
Development of a field measurement system for the Bulk HTSC SAU
11th International Conference on Synchrotron Radiation Instrumentation (SRI 2012)To realize a short-period strong-field undulator, we proposed a high temperature superconducting bulk staggered array undulator (Bulk HTSC SAU) and proceeded proof of principle experiments and numerical studies. We have succeeded to generate periodic transverse magnetic fields whose strength was controlled by an external solenoid field. At the same time, we revealed a problem; at both ends of undulator, field distribution is substantially distorted. We proposed several approaches of field correction. To verify the effectiveness of these field correction methods, it is necessary to measure the magnetic field distribution precisely, not only inside of the undulator but also both ends. For this purpose, we developed a rotary measurement system to measure the magnetic field distribution at the end of the undulator. Multiple Hall sensors are placed on a circuit board at equal intervals from the centre of the board. By rotating and moving the board, the probe can measure axial field in 3D space on the undulator ends. In this paper, we deliver specifics of the system
Congou tea drinking and oesophageal cancer in South China
The study from a large hospital-based caseβcontrol for 1248 cases with oesophageal cancer and the same number of controls in South China showed that Congou, a grade of Chinese black tea, may protect against cancers of the oesophagus and reduce the risk of a combination of alcohol drinking and smoking (especially smoking), regardless of temperature when drinking
Influences of Excluded Volume of Molecules on Signaling Processes on Biomembrane
We investigate the influences of the excluded volume of molecules on
biochemical reaction processes on 2-dimensional surfaces using a model of
signal transduction processes on biomembranes. We perform simulations of the
2-dimensional cell-based model, which describes the reactions and diffusion of
the receptors, signaling proteins, target proteins, and crowders on the cell
membrane. The signaling proteins are activated by receptors, and these
activated signaling proteins activate target proteins that bind autonomously
from the cytoplasm to the membrane, and unbind from the membrane if activated.
If the target proteins bind frequently, the volume fraction of molecules on the
membrane becomes so large that the excluded volume of the molecules for the
reaction and diffusion dynamics cannot be negligible. We find that such
excluded volume effects of the molecules induce non-trivial variations of the
signal flow, defined as the activation frequency of target proteins, as
follows. With an increase in the binding rate of target proteins, the signal
flow varies by i) monotonically increasing; ii) increasing then decreasing in a
bell-shaped curve; or iii) increasing, decreasing, then increasing in an
S-shaped curve. We further demonstrate that the excluded volume of molecules
influences the hierarchical molecular distributions throughout the reaction
processes. In particular, when the system exhibits a large signal flow, the
signaling proteins tend to surround the receptors to form receptor-signaling
protein clusters, and the target proteins tend to become distributed around
such clusters. To explain these phenomena, we analyze the stochastic model of
the local motions of molecules around the receptor.Comment: 31 pages, 10 figure
- β¦