22,198 research outputs found
Protein secondary structure: Entropy, correlations and prediction
Is protein secondary structure primarily determined by local interactions
between residues closely spaced along the amino acid backbone, or by non-local
tertiary interactions? To answer this question we have measured the entropy
densities of primary structure and secondary structure sequences, and the local
inter-sequence mutual information density. We find that the important
inter-sequence interactions are short ranged, that correlations between
neighboring amino acids are essentially uninformative, and that only 1/4 of the
total information needed to determine the secondary structure is available from
local inter-sequence correlations. Since the remaining information must come
from non-local interactions, this observation supports the view that the
majority of most proteins fold via a cooperative process where secondary and
tertiary structure form concurrently. To provide a more direct comparison to
existing secondary structure prediction methods, we construct a simple hidden
Markov model (HMM) of the sequences. This HMM achieves a prediction accuracy
comparable to other single sequence secondary structure prediction algorithms,
and can extract almost all of the inter-sequence mutual information. This
suggests that these algorithms are almost optimal, and that we should not
expect a dramatic improvement in prediction accuracy. However, local
correlations between secondary and primary structure are probably of
under-appreciated importance in many tertiary structure prediction methods,
such as threading.Comment: 8 pages, 5 figure
A Robust Solver for a Second Order Mixed Finite Element Method for the Cahn-Hilliard Equation
We develop a robust solver for a second order mixed finite element splitting
scheme for the Cahn-Hilliard equation. This work is an extension of our
previous work in which we developed a robust solver for a first order mixed
finite element splitting scheme for the Cahn-Hilliard equaion. The key
ingredient of the solver is a preconditioned minimal residual algorithm (with a
multigrid preconditioner) whose performance is independent of the spacial mesh
size and the time step size for a given interfacial width parameter. The
dependence on the interfacial width parameter is also mild.Comment: 17 pages, 3 figures, 4 tables. arXiv admin note: substantial text
overlap with arXiv:1709.0400
SCOPe: Structural Classification of Proteins--extended, integrating SCOP and ASTRAL data and classification of new structures.
Structural Classification of Proteins-extended (SCOPe, http://scop.berkeley.edu) is a database of protein structural relationships that extends the SCOP database. SCOP is a manually curated ordering of domains from the majority of proteins of known structure in a hierarchy according to structural and evolutionary relationships. Development of the SCOP 1.x series concluded with SCOP 1.75. The ASTRAL compendium provides several databases and tools to aid in the analysis of the protein structures classified in SCOP, particularly through the use of their sequences. SCOPe extends version 1.75 of the SCOP database, using automated curation methods to classify many structures released since SCOP 1.75. We have rigorously benchmarked our automated methods to ensure that they are as accurate as manual curation, though there are many proteins to which our methods cannot be applied. SCOPe is also partially manually curated to correct some errors in SCOP. SCOPe aims to be backward compatible with SCOP, providing the same parseable files and a history of changes between all stable SCOP and SCOPe releases. SCOPe also incorporates and updates the ASTRAL database. The latest release of SCOPe, 2.03, contains 59 514 Protein Data Bank (PDB) entries, increasing the number of structures classified in SCOP by 55% and including more than 65% of the protein structures in the PDB
SIFTER search: a web server for accurate phylogeny-based protein function prediction.
We are awash in proteins discovered through high-throughput sequencing projects. As only a minuscule fraction of these have been experimentally characterized, computational methods are widely used for automated annotation. Here, we introduce a user-friendly web interface for accurate protein function prediction using the SIFTER algorithm. SIFTER is a state-of-the-art sequence-based gene molecular function prediction algorithm that uses a statistical model of function evolution to incorporate annotations throughout the phylogenetic tree. Due to the resources needed by the SIFTER algorithm, running SIFTER locally is not trivial for most users, especially for large-scale problems. The SIFTER web server thus provides access to precomputed predictions on 16 863 537 proteins from 232 403 species. Users can explore SIFTER predictions with queries for proteins, species, functions, and homologs of sequences not in the precomputed prediction set. The SIFTER web server is accessible at http://sifter.berkeley.edu/ and the source code can be downloaded
Theoretical value of the recommended expanded European Standard Set of STR loci for the identification of human remains
We have undertaken a series of simulations to assess the effectiveness of commercially available sets of STR loci, including the loci recommended for inclusion in the expanded European Standard Set, for the purpose of human identification. A total of 9200 genotype simulations were performed using DNA · VIEW. The software was used to calculate likelihood ratios (LRs) for 23 groups of relatives, and to determine the probability of identification given scenarios that ranged between 10 and 250,000 victims. The additional loci included in the recommended expanded European Standard Set, when used in conjunction with the Identifiler® kit, significantly improved the typical LRs for tested scenarios and the likely success of providing correct identifications
Developmental and functional effects of steroid hormones on the neuroendocrine axis and spinal cord
This review highlights the principal effects of steroid hormones at central and peripheral levels in the neuroendocrine axis. The data discussed highlight the principal role of oestrogens and testosterone in hormonal programming in relation to sexual orientation, reproductive and metabolic programming, and the neuroendocrine mechanism involved in the development of polycystic ovary syndrome phenotype. Moreover, consistent with the wide range of processes in which steroid hormones take part, we discuss the protective effects of progesterone on neurodegenerative disease and the signalling mechanism involved in the genesis of oestrogen-induced pituitary prolactinomas.Fil: Zubeldia Brenner, Lautaro. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Biología y Medicina Experimental. Fundación de Instituto de Biología y Medicina Experimental. Instituto de Biología y Medicina Experimental; ArgentinaFil: Roselli, C. E.. Oregon Health and Science University Portland; Estados UnidosFil: Recabarren, S. E.. Universidad de Concepción; ChileFil: Gonzalez Deniselle, Maria Claudia. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Biología y Medicina Experimental. Fundación de Instituto de Biología y Medicina Experimental. Instituto de Biología y Medicina Experimental; ArgentinaFil: Lara, H. E.. Universidad de Chile; Chil
Physical and geometric constraints explain the labyrinth-like shape of the nasal cavity
The nasal cavity is a vital component of the respiratory system that heats
and humidifies inhaled air in all vertebrates. Despite this common function,
the shapes of nasal cavities vary widely across animals. To understand this
variability, we here connect nasal geometry to its function by theoretically
studying the airflow and the associated scalar exchange that describes heating
and humidification. We find that optimal geometries, which have minimal
resistance for a given exchange efficiency, have a constant gap width between
their side walls, but their overall shape is restricted only by the geometry of
the head. Our theory explains the geometric variations of natural nasal
cavities quantitatively and we hypothesize that the trade-off between high
exchange efficiency and low resistance to airflow is the main driving force
shaping the nasal cavity. Our model further explains why humans, whose nasal
cavities evolved to be smaller than expected for their size, become obligate
oral breathers in aerobically challenging situations.Comment: 7 pages, 4 figure
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