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PubMed1981

Acetylcholinesterase in the platelet-megakaryocyte system. II. Structural localization in megakaryocytes of the rat, mouse, and cat.

Acetylcholinesterase (AchE) activity (EC 3.7.1.7) was demonstrated cytochemically in the megakaryocyte (MK) line of differentiation in the red bone marrow of rat, mouse, and cat. Activity was detected in the Golgi complexes of cells considered to be committed MK precursor cells, and was found in Golgi cisterns through all subsequent stages of MK maturation. In the early, basophilic stage of differentiation some MK showed AchE activity in the perinuclear cistern and in a few profiles of the granular endoplasmic reticulum, but reaction was absent from this location at later maturation stages. Concomitantly with the development of the demarcation membrane system, another membrane system appeared; this system consisted of smooth-surfaced, tortuous tubules and narrow cisterns, and it displayed AchE activity through cytoplasmic maturation. In thrombocytogenic MK, the smooth AchE-reacting membranes (SAM) became the AchE-reacting dense tubular system (DTS) of released MK cytoplasm. The MK of the species studied also contained a varying number of AchE-reacting granules (mouse greater than cat greater than rat) which were distinct from alpha-granules.

Acetylcholinesterase↗
PubMed1977

[Changes in the structural localization of glycogen during glucose resorption].

Quantitative changes in the glycogen granula contents of the dog's small intestinal mucosa were investigated with light microscopy using Best-carmin dying. In fasting animals the glycogen could be detected in a patchy arrangement in the supranuclear cytoplasmic region of the enterocytes. During glucose abasorption glycogen appeared in continually increasing quantities also in the lamina propria. Injecting Glucagon (50-100 microgram/15') into the artery of the intestinal loop during glucose absorption, glycogen totally disappeared from the enterocytes, while it remained unchanged in the cells of the lamina propria.

Animals↗
PubMed2005

A structural alphabet for local protein structures: improved prediction methods.

Three-dimensional protein structures can be described with a library of 3D fragments that define a structural alphabet. We have previously proposed such an alphabet, composed of 16 patterns of five consecutive amino acids, called Protein Blocks (PBs). These PBs have been used to describe protein backbones and to predict local structures from protein sequences. The Q16 prediction rate reaches 40.7% with an optimization procedure. This article examines two aspects of PBs. First, we determine the effect of the enlargement of databanks on their definition. The results show that the geometrical features of the different PBs are preserved (local RMSD value equal to 0.41 A on average) and sequence-structure specificities reinforced when databanks are enlarged. Second, we improve the methods for optimizing PB predictions from sequences, revisiting the optimization procedure and exploring different local prediction strategies. Use of a statistical optimization procedure for the sequence-local structure relation improves prediction accuracy by 8% (Q16 = 48.7%). Better recognition of repetitive structures occurs without losing the prediction efficiency of the other local folds. Adding secondary structure prediction improved the accuracy of Q16 by only 1%. An entropy index (Neq), strongly related to the RMSD value of the difference between predicted PBs and true local structures, is proposed to estimate prediction quality. The Neq is linearly correlated with the Q16 prediction rate distributions, computed for a large set of proteins. An "expected" prediction rate QE16 is deduced with a mean error of 5%.

Amino Acid Sequence↗
PubMed2006

Structural refinement of protein segments containing secondary structure elements: Local sampling, knowledge-based potentials, and clustering.

In this article, we present an iterative, modular optimization (IMO) protocol for the local structure refinement of protein segments containing secondary structure elements (SSEs). The protocol is based on three modules: a torsion-space local sampling algorithm, a knowledge-based potential, and a conformational clustering algorithm. Alternative methods are tested for each module in the protocol. For each segment, random initial conformations were constructed by perturbing the native dihedral angles of loops (and SSEs) of the segment to be refined while keeping the protein body fixed. Two refinement procedures based on molecular mechanics force fields - using either energy minimization or molecular dynamics - were also tested but were found to be less successful than the IMO protocol. We found that DFIRE is a particularly effective knowledge-based potential and that clustering algorithms that are biased by the DFIRE energies improve the overall results. Results were further improved by adding an energy minimization step to the conformations generated with the IMO procedure, suggesting that hybrid strategies that combine both knowledge-based and physical effective energy functions may prove to be particularly effective in future applications.

Algorithms↗
PubMed2002

Structure, chromosomal localization and expression of the mouse regulator of G-protein signaling10 gene (mRGS10).

Regulator of G-protein signaling (RGS) proteins negatively regulate signaling pathways involving seven transmembrane receptors and heterotrimeric G proteins. The purpose of this study was to determine the chromosomal localization, structure and expression profile of the gene coding for mouse regulator of G-protein signaling10 (mRGS10). Fluorescence in situ hybridization analysis indicated that mRGS10 maps to band F3-F4 of the mouse chromosome 7. Sequence analysis revealed that the RGS10 gene encompasses six exons spanning more than 40 kb of genomic DNA. The RGS domain is encoded by exons 3-6; alternative splicing of the first exons allows the generation of two isoforms in the mouse system which differ in their N-terminal portion. Thus, mRGS10 encodes two intracellular proteins of 167 and 181 amino-acids which are highly homologous to the human and rat polypeptides. The deduced amino-acid sequences of mouse RGS10 show 92% sequence identity to their orthologues from human. The mRGS10 gene is expressed predominantly in brain and testis but it is also found in heart, lung, bone marrow, lymph node and spleen. Differential display between mature B lymphocytes and marginal zone B cells, as well as reverse transcription-polymerase chain reaction and Northern blot, showed that mRGS10 is differentially transcribed during B-cell differentiation. Finally, mRGS10 protein was detected in plasma cells of secondary lymphoid organs by immunofluorescence.

Amino Acid Sequence↗
PubMed1995

Gene structure, chromosomal localization, and expression of the murine homologue of human proteinase inhibitor 6 (PI-6) suggests divergence of PI-6 from the ovalbumin serpins.

Human proteinase inhibitor 6 (PI-6) is a recently described protein belonging to the serine proteinase inhibitor (serpin) superfamily. Sequence similarity suggests that PI-6 most resembles the ovalbumin (ov) serpins which include plasminogen activator inhibitor-2, the squamous cell carcinoma antigen, monocyte/neutrophil elastase inhibitor, and maspin. Although these proteins are associated with carcinomas and inflammation, they appear to have diverse functions and little is known of their physiological roles. In this study we have characterized cDNA and genomic clones encoding mouse PI-6 in order to analyze the localization, structure, and expression of the gene. The reactive center residues (Arg-Cys) are conserved in the mouse molecule, and recombinant mouse PI-6 was shown to bind thrombin, indicating that it has similar inhibitory properties to its human counterpart. Using reverse transcriptase-polymerase chain reaction assays on RNA isolated from 15-day-old embryos and adult mice, we have shown that mouse PI-6 expression is developmentally regulated, and that, unlike human PI-6, it is absent from the placenta. The mouse homologue of the human PI-6 gene has been designated Spi3 and was mapped to chromosome 13 between the Pl1 and ctla2 alpha genes. It spans 20 kilobases, consists of 7 exons and 6 introns, and contains a TATA motif 24 nucleotides upstream of the transcriptional start site. A 680-base pair DNA fragment containing this motif and 31 nucleotides of the 5'-untranslated region of the structural gene directed transcription of a bacterial cat gene, demonstrating the presence of a functional promoter. The PI-6 gene lacks an intron present in the ovalbumin and PAI-2 genes; otherwise it is identical in terms of the numbers, position, and phasing of the intron/exon boundaries. These results suggest that PI-6 and the ov-serpin genes have diverged and do not belong to the same subgroup.

Amino Acid Sequence↗
PubMed1986

Formation of the local secondary structure of proteins: local sequence or environment.

An analysis of the occurrence of tetrapeptides in 35 globular proteins for alpha-helix, beta-structure and coil was performed. We concluded that: the conformation of a short polypeptide segment cannot be determined on the basis of the knowledge of the amino acid sequence only; local structures of a protein are formed as the result of interactions within the whole structural domain of the protein as well as interactions with the environment.

Amino Acid Sequence↗
PubMed2005

Local atomic structure of partially ordered NiMn in NiMn/NiFe exchange-coupled layers: 2. Electronic structure calculations.

Local electronic and magnetic structure calculations for NiMn exchange bias alloys are reported for clusters containing NiMn in both the chemically disordered face-centered cubic and the chemically and magnetically ordered L1(0) phases. The results of these calculations are consistent with our local structure measurements that point toward the existence of nanometer-scale ordered clusters at the beginning stages of chemical ordering. The spatial dependence of both the local density of states and the magnetization is strongly influenced by the existence of magnetic order on short length scales, giving rise to an inhomogeneous profile for these quantities across the material with the greatest change at the interface that is still small enough within the domain to imply that the magnetization is still highly developed.

Journal Article↗
PubMed2002

Image study summarization of MR brain images by automated localization of relevant structures.

The paper discusses a methodology to objectify the patient presenting condition by automated selection of relevant images from a serial MR study. Structured data entry is used to capture the patient's chief complaint, pertinent history, signs, and symptoms. Expert created rules use this data to arrive at a differential and to identify the affected brain region/structure. Another expert created knowledge base then maps this information to the relevant image type, including image sequence specifics and orientation. A DICOM study reader identifies the relevant imaging sequences from the MR study. The structure localization method involves a search based on principal component analysis. A training set of subimages containing the structure of interest is used to generate a basis set of prototype images called eigenimages. The structure is located in an image by searching the image for a subregion that best matches the basis set. The structure localization was used to locate the lateral ventricles and orbits in nine images that were not part of the training set. The automated localizations were compared to expert localizations and the center of the regions located by the two techniques agreed to within +/- 1.7 mm (average for the nine localizations each of two structures).

Automation↗
PubMed2006

Local protein structure prediction using discriminative models.

BACKGROUND: In recent years protein structure prediction methods using local structure information have shown promising improvements. The quality of new fold predictions has risen significantly and in fold recognition incorporation of local structure predictions led to improvements in the accuracy of results. We developed a local structure prediction method to be integrated into either fold recognition or new fold prediction methods. For each local sequence window of a protein sequence the method predicts probability estimates for the sequence to attain particular local structures from a set of predefined local structure candidates. The first step is to define a set of local structure representatives based on clustering recurrent local structures. In the second step a discriminative model is trained to predict the local structure representative given local sequence information. RESULTS: The step of clustering local structures yields an average RMSD quantization error of 1.19 A for 27 structural representatives (for a fragment length of 7 residues). In the prediction step the area under the ROC curve for detection of the 27 classes ranges from 0.68 to 0.88. CONCLUSION: The described method yields probability estimates for local protein structure candidates, giving signals for all kinds of local structure. These local structure predictions can be incorporated either into fold recognition algorithms to improve alignment quality and the overall prediction accuracy or into new fold prediction methods.

Algorithms↗
PubMed2002

Local structure-based sequence profile database for local and global protein structure predictions.

MOTIVATION: A large body of evidence suggests that protein structural information is frequently encoded in local sequences-sequence-structure relationships derived from local structure/sequence analyses could significantly enhance the capacities of protein structure prediction methods. In this paper, the prediction capacity of a database (LSBSP2) that organizes local sequence-structure relationships encoded in local structures with two consecutive secondary structure elements is tested with two computational procedures for protein structure prediction. The goal is twofold: to test the folding hypothesis that local structures are determined by local sequences, and to enhance our capacity in predicting protein structures from their amino acid sequences. RESULTS: The LSBSP2 database contains a large set of sequence profiles derived from exhaustive pair-wise structural alignments for local structures with two consecutive secondary structure elements. One computational procedure makes use of the PSI-BLAST alignment program to predict local structures for testing sequence fragments by matching the testing sequence fragments onto the sequence profiles in the LSBSP2 database. The results show that 54% of the test sequence fragments were predicted with local structures that match closely with their native local structures. The other computational procedure is a filter system that is capable of removing false positives as possible from a set of PSI-BLAST hits. An assessment with a large set of non-redundant protein structures shows that the PSI-BLAST + filter system improves the prediction specificity by up to two-fold over the prediction specificity of the PSI-BLAST program for distantly related protein pairs. Tests with the two computational procedures above demonstrate that local sequence-structure relationships can indeed enhance our capacity in protein structure prediction. The results also indicate that local sequences encoded with strong local structure propensities play an important role in determining the native state folding topology.

Algorithms↗
PubMed2006

Selection of antisense oligonucleotides based on multiple predicted target mRNA structures.

BACKGROUND: Local structures of target mRNAs play a significant role in determining the efficacies of antisense oligonucleotides (ODNs), but some structure-based target site selection methods are limited by uncertainties in RNA secondary structure prediction. If all the predicted structures of a given mRNA within a certain energy limit could be used simultaneously, target site selection would obviously be improved in both reliability and efficiency. In this study, some key problems in ODN target selection on the basis of multiple predicted target mRNA structures are systematically discussed. RESULTS: Two methods were considered for merging topologically different RNA structures into integrated representations. Several parameters were derived to characterize local target site structures. Statistical analysis on a dataset with 448 ODNs against 28 different mRNAs revealed 9 features quantitatively associated with efficacy. Features of structural consistency seemed to be more highly correlated with efficacy than indices of the proportion of bases in single-stranded or double-stranded regions. The local structures of the target site 5' and 3' termini were also shown to be important in target selection. Neural network efficacy predictors using these features, defined on integrated structures as inputs, performed well in "minus-one-gene" cross-validation experiments. CONCLUSION: Topologically different target mRNA structures can be merged into integrated representations and then used in computer-aided ODN design. The results of this paper imply that some features characterizing multiple predicted target site structures can be used to predict ODN efficacy.

Algorithms↗
PubMed2005

Local atomic structure of partially ordered NiMn in NiMn/NiFe exchange coupled layers: 1. XAFS measurements and structural refinement.

The local atomic structure of the Mn in NiMn/NiFe exchange coupled films was investigated using Mn K-edge extended X-ray absorption fine structure (EXAFS) measurements to elucidate the possible correlation between the coercivity that can occur even in samples that display no signs of NiMn L1(0) ordering in diffraction patterns and such ordering on a length scale below the diffraction limit. Raising the substrate growth temperature from 3 to 200 degrees C increases the extent of L1(0) ordering in the NiMn pinning layer and the associated coercivity. A short-range order parameter (S(SRO)) was derived from EXAFS data for comparison with the long-range order parameter (S(LRO)) obtained from the X-ray diffraction measurements. Analogous to S(LRO), S(SRO) increases in tandem with the pinning layer coercivity, implying the presence of nanometer-scale ordered clusters at the beginning stages of macroscopic L1(0) phase formation that apparently foster antiferromagnetism despite their small size. The behavior of the EXAFS, especially the contributions of the more distant shells, also suggests that the overall structure in materials that are not fully L1(0)-ordered is more accurately described as locally ordered, magnetically ordered, incoherent nanodomains of the L1(0) phase separated by locally disordered, strained, interdomain regions that globally average to the fcc lattice with little or no local fcc structure present. The constraints on the sizes and other characteristics of these domains were explored by examining the diffraction patterns calculated for several two-dimensional analogue structures. These demonstrated that one of the most important structural features in the development of a two-phase diffraction pattern was the presence of dislocations in response to the elastic strain at the interfaces between domains where the accumulated expitaxial mismatch was greater than half of the bond length that rendered the domains incoherent with respect to each other.

Journal Article↗