Inorganic carbon acquisition in potentially toxic and non-toxic diatoms: the effect of pH-induced changes in seawater carbonate chemistry.

The effects of pH-induced changes in seawater carbonate chemistry on inorganic carbon (C(i)) acquisition and domoic acid (DA) production were studied in two potentially toxic diatom species, Pseudo-nitzschia multiseries and Nitzschia navis-varingica, and the non-toxic Stellarima stellaris. In vivo activities of carbonic anhydrase (CA), photosynthetic O(2) evolution and CO(2) and HCO(3)(-) uptake rates were measured by membrane inlet MS in cells acclimated to low (7.9) and high pH (8.

Protein conformational flexibility prediction using machine learning.

Using a data set of 16 proteins, a neural network has been trained to predict backbone 15N generalized order parameters from the three-dimensional structures of proteins. The final network parameterization contains six input features. The average prediction accuracy, as measured by the Pearson's correlation coefficient between experimental and predicted values of the square of the generalized order parameter is >0.

NMR structure of the peptidyl-tRNA hydrolase domain from Pseudomonas syringae expands the structural coverage of the hydrolysis domains of class 1 peptide chain release factors.

The NMR structure of the peptidyl-tRNA hydrolase (PTH) domain from ( PTH domain) was solved by using recently devised protocol for high throughput protein structure determination. The PTH domain belongs to a large Pfam family PF00472, which consists of at least 1549 proteins annotated as ‘hydrolysis domains of peptidyl-tRNA’. The structure of PTH domain expands the ‘structural coverage’ of the PFam family.

Critical assessment of methods of protein structure prediction-Round VII.

This paper is an introduction to the supplemental issue of the journal PROTEINS, dedicated to the seventh CASP experiment to assess the state of the art in protein structure prediction. The paper describes the conduct of the experiment, the categories of prediction included, and outlines the evaluation and assessment procedures. Highlights are improvements in model accuracy relative to that obtainable from knowledge of a single best template structure; convergence of the accuracy of models produced by automatic servers toward that produced by human modeling teams; the emergence of methods for predicting the quality of models; and rapidly increasing practical applications of the methods.

A defect in the ionotropic glutamate receptor 6 gene (GRIK2) is associated with autosomal recessive mental retardation.

Nonsyndromic mental retardation is one of the most important unresolved problems in genetic health care. Autosomal forms are far more common than X-linked forms, but, in contrast to the latter, they are still largely unexplored. Here, we report a complex mutation in the ionotropic glutamate receptor 6 gene (GRIK2, also called "GLUR6") that cosegregates with moderate-to-severe nonsyndromic autosomal recessive mental retardation in a large, consanguineous Iranian family.

Natively unstructured regions in proteins identified from contact predictions.

Motivation: Natively unstructured (also dubbed intrinsically disordered) regions in proteins lack a defined 3D structure under physiological conditions and often adopt regular structures under particular conditions. Proteins with such regions are overly abundant in eukaryotes, they may increase functional complexity of organisms and they usually evade structure determination in the unbound form. Low propensity for the formation of internal residue contacts has been previously used to predict natively unstructured regions.

Natively unstructured loops differ from other loops.

Natively unstructured or disordered protein regions may increase the functional complexity of an organism; they are particularly abundant in eukaryotes and often evade structure determination. Many computational methods predict unstructured regions by training on outliers in otherwise well-ordered structures. Here, we introduce an approach that uses a neural network in a very different and novel way.

Prediction of DNA-binding residues from sequence.

Motivation: Thousands of proteins are known to bind to DNA; for most of them the mechanism of action and the residues that bind to DNA, i.e. the binding sites, are yet unknown.

Protein-protein interaction hotspots carved into sequences.

Protein-protein interactions, a key to almost any biological process, are mediated by molecular mechanisms that are not entirely clear. The study of these mechanisms often focuses on all residues at protein-protein interfaces. However, only a small subset of all interface residues is actually essential for recognition or binding.

SNAP: predict effect of non-synonymous polymorphisms on function.

Many genetic variations are single nucleotide polymorphisms (SNPs). Non-synonymous SNPs are 'neutral' if the resulting point-mutated protein is not functionally discernible from the wild type and 'non-neutral' otherwise. The ability to identify non-neutral substitutions could significantly aid targeting disease causing detrimental mutations, as well as SNPs that increase the fitness of particular phenotypes.

Consensus sequences improve PSI-BLAST through mimicking profile-profile alignments.

Sequence alignments may be the most fundamental computational resource for molecular biology. The best methods that identify sequence relatedness through profile-profile comparisons are much slower and more complex than sequence-sequence and sequence-profile comparisons such as, respectively, BLAST and PSI-BLAST. Families of related genes and gene products (proteins) can be represented by consensus sequences that list the nucleic/amino acid most frequent at each sequence position in that family.

Membrane protein prediction methods.

We survey computational approaches that tackle membrane protein structure and function prediction. While describing the main ideas that have led to the development of the most relevant and novel methods, we also discuss pitfalls, provide practical hints and highlight the challenges that remain. The methods covered include: sequence alignment, motif search, functional residue identification, transmembrane segment and protein topology predictions, homology and ab initio modeling.

ISIS: interaction sites identified from sequence.

Motivation: Large-scale experiments reveal pairs of interacting proteins but leave the residues involved in the interactions unknown. These interface residues are essential for understanding the mechanism of interaction and are often desired drug targets. Reliable identification of residues that reside in protein-protein interface typically requires analysis of protein structure.

Arthritis-induced increase in cholecystokinin release in the rat anterior cingulate cortex is reversed by diclofenac.

Given a hypothesised role for CCK in the anterior cingulate cortex (ACC) for the sensation of pain, the aim of the present study was to investigate whether the increased CCK release could be affected by two different analgesic drugs, morphine and the non-selective cyclooxygenase inhibitor diclofenac. Since opioids stimulate CCK release in other CNS regions we have also studied the effect of morphine by itself on the CCK-LI release in the ACC of non-arthritic rats. Three to seven hours after intraarticular carrageenan injection, at the time when the animals are known to show pain-related behaviour, in vivo microdialysis in awake rats revealed increased CCK-LI release in the ACC.

Inorganic carbon acquisition in red tide dinoflagellates.

Carbon acquisition was investigated in three marine bloom-forming dinollagellates-Prorocentrum minimum, Heterocapsa triquetra and Ceratium lineatum. In vivo activities of extracellular and intracellular carbonic anhydrase (CA), photosynthetic O2 evolution, CO2 and HCO3- uptake rates were measured by membrane inlet mass spectrometry (MIMS) in cells acclimated to low pH (8.0) and high pH (8.

Identifying cysteines and histidines in transition-metal-binding sites using support vector machines and neural networks.

Accurate predictions of metal-binding sites in proteins by using sequence as the only source of information can significantly help in the prediction of protein structure and function, genome annotation, and in the experimental determination of protein structure. Here, we introduce a method for identifying histidines and cysteines that participate in binding of several transition metals and iron complexes. The method predicts histidines as being in either of two states (free or metal bound) and cysteines in either of three states (free, metal bound, or in disulfide bridges).

Create and assess protein networks through molecular characteristics of individual proteins.

Motivation: The study of biological systems, pathways and processes relies increasingly on analyses of networks. Most often, such analyses focus on network topology, thereby treating all proteins or genes as identical, featureless nodes. Integrating molecular data and insights about the qualities of individual proteins into the analysis may enhance our ability to decipher biological pathways and processes.

Protein-protein interactions more conserved within species than across species.

Experimental high-throughput studies of protein-protein interactions are beginning to provide enough data for comprehensive computational studies. Today, about ten large data sets, each with thousands of interacting pairs, coarsely sample the interactions in fly, human, worm, and yeast. Another about 55,000 pairs of interacting proteins have been identified by more careful, detailed biochemical experiments.

PROFtmb: a web server for predicting bacterial transmembrane beta barrel proteins.

PROFtmb predicts transmembrane beta-barrel (TMB) proteins in Gram-negative bacteria. For each query protein, PROFtmb provides both a Z-value indicating that the protein actually contains a membrane barrel, and a four-state per-residue labeling of upward- and downward-facing strands, periplasmic hairpins and extracellular loops. While most users submit individual proteins known to contain TMBs, some groups submit entire proteomes to screen for potential TMBs.

Cation channels of the transient receptor potential superfamily: their role in physiological and pathophysiological processes of smooth muscle cells.

Smooth muscle cells (SMC) are essential components of many tissues of the body. Ion channels regulate their membrane potential, the intracellular Ca(2+) concentration ([Ca(2+)](i)) and their contractility. Among the ion channels expressed in SMC cation channels of the transient receptor potential (TRP) superfamily allow the entry of Na(+), Ca(2+) and Mg(2+).