971 resultados para Protein Structure


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A series of mutant human and yeast copper-zinc superoxide dismutases has been prepared, with mutations corresponding to those found in familial amyotrophic lateral sclerosis (ALS; also known as Lou Gehrig's disease). These proteins have been characterized with respect to their metal-binding characteristics and their redox reactivities. Replacement of Zn2+ ion in the zinc sites of several of these proteins with either Cu2+ or Co2+ gave metal-substituted derivatives with spectroscopic properties different from those of the analogous derivative of the wild-type proteins, indicating that the geometries of binding of these metal ions to the zinc site were affected by the mutations. Several of the ALS-associated mutant copper-zinc superoxide dismutases were also found to be reduced by ascorbate at significantly greater rate than the wild-type proteins. We conclude that similar alterations in the properties of the zinc binding site can be caused by mutations scattered throughout the protein structure. This finding may help to explain what is perhaps the most perplexing question in copper-zinc superoxide dismutase-associated familial ALS-i.e., how such a diverse set of mutations can result in the same gain of function that causes the disease.

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We present new methods for identifying and analyzing statistically significant residue clusters that occur in three-dimensional (3D) protein structures. Residue clusters of different kinds occur in many contexts. They often feature the active site (e.g., in substrate binding), the interface between polypeptide units of protein complexes, regions of protein-protein and protein-nucleic acid interactions, or regions of metal ion coordination. The methods are illustrated with 3D clusters centering on four themes. (i) Acidic or histidine-acidic clusters associated with metal ions. (ii) Cysteine clusters including coordination of metals such as zinc or iron-sulfur structures, cysteine knots prominent in growth factors, multiple sets of buried disulfide pairings that putatively nucleate the hydrophobic core, or cysteine clusters of mostly exposed disulfide bridges. (iii) Iron-sulfur proteins and charge clusters. (iv) 3D environments of multiple histidine residues. Study of diverse 3D residue clusters offers a new perspective on protein structure and function. The algorithms can aid in rapid identification of distinctive sites, suggest correlations among protein structures, and serve as a tool in the analysis of new structures.

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Statistically significant charge clusters (basic, acidic, or of mixed charge) in tertiary protein structures are identified by new methods from a large representative collection of protein structures. About 10% of protein structures show at least one charge cluster, mostly of mixed type involving about equally anionic and cationic residues. Positive charge clusters are very rare. Negative (or histidine-acidic) charge clusters often coordinate calcium, or magnesium or zinc ions [e.g., thermolysin (PDB code: 3tln), mannose-binding protein (2msb), aminopeptidase (1amp)]. Mixed-charge clusters are prominent at interchain contacts where they stabilize quaternary protein formation [e.g., glutathione S-transferase (2gst), catalase (8act), and fructose-1,6-bisphosphate aldolase (1fba)]. They are also involved in protein-protein interaction and in substrate binding. For example, the mixed-charge cluster of aspartate carbamoyl-transferase (8atc) envelops the aspartate carbonyl substrate in a flexible manner (alternating tense and relaxed states) where charge associations can vary from weak to strong. Other proteins with charge clusters include the P450 cytochrome family (BM-3, Terp, Cam), several flavocytochromes, neuraminidase, hemagglutinin, the photosynthetic reaction center, and annexin. In each case in Table 2 we discuss the possible role of the charge clusters with respect to protein structure and function.

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Local protein structure prediction efforts have consistently failed to exceed approximately 70% accuracy. We characterize the degeneracy of the mapping from local sequence to local structure responsible for this failure by investigating the extent to which similar sequence segments found in different proteins adopt similar three-dimensional structures. Sequence segments 3-15 residues in length from 154 different protein families are partitioned into neighborhoods containing segments with similar sequences using cluster analysis. The consistency of the sequence-to-structure mapping is assessed by comparing the local structures adopted by sequence segments in the same neighborhood in proteins of known structure. In the 154 families, 45% and 28% of the positions occur in neighborhoods in which one and two local structures predominate, respectively. The sequence patterns that characterize the neighborhoods in the first class probably include virtually all of the short sequence motifs in proteins that consistently occur in a particular local structure. These patterns, many of which occur in transitions between secondary structural elements, are an interesting combination of previously studied and novel motifs. The identification of sequence patterns that consistently occur in one or a small number of local structures in proteins should contribute to the prediction of protein structure from sequence.

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The three-dimensional structure of murine mitochondrial carbonic anhydrase V has been determined and refined at 2.45-A resolution (crystallographic R factor = 0.187). Significant structural differences unique to the active site of carbonic anhydrase V are responsible for differences in the mechanism of catalytic proton transfer as compared with other carbonic anhydrase isozymes. In the prototypical isozyme, carbonic anhydrase II, catalytic proton transfer occurs via the shuttle group His-64; carbonic anhydrase V has Tyr-64, which is not an efficient proton shuttle due in part to the bulky adjacent side chain of Phe-65. Based on analysis of the structure of carbonic anhydrase V, we speculate that Tyr-131 may participate in proton transfer due to its proximity to zinc-bound solvent, its solvent accessibility, and its electrostatic environment in the protein structure. Finally, the design of isozyme-specific inhibitors is discussed in view of the complex between carbonic anhydrase V and acetazolamide, a transition-state analogue. Such inhibitors may be physiologically important in the regulation of blood glucose levels.

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The measurement of dipolar contributions to the splitting of 15N resonances of 1H-15N amide pairs in multidimensional high-field NMR spectra of field-oriented cyanometmyoglobin is reported. The splittings appear as small field-dependent perturbations of normal scalar couplings. Assignment of more than 90 resonances to specific sequential sites in the protein allows correlation of the dipolar contributions with predictions based on the known susceptibility and known structure of the protein. Implications as an additional source of information for protein structure determination in solution are discussed.

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In vertebrate species, the innate immune system down-regulates protein translation in response to viral infection through the action of the double-stranded RNA (dsRNA)-activated protein kinase (PKR). In some teleost species another protein kinase, Z-DNA-dependent protein kinase (PKZ), plays a similar role but instead of dsRNA binding domains, PKZ has Zα domains. These domains recognize the left-handed conformer of dsDNA and dsRNA known as Z-DNA/Z-RNA. Cyprinid herpesvirus 3 infects common and koi carp, which have PKZ, and encodes the ORF112 protein that itself bears a Zα domain, a putative competitive inhibitor of PKZ. Here we present the crystal structure of ORF112-Zα in complex with an 18-bp CpG DNA repeat, at 1.5 Å. We demonstrate that the bound DNA is in the left-handed conformation and identify key interactions for the specificity of ORF112. Localization of ORF112 protein in stress granules induced in Cyprinid herpesvirus 3-infected fish cells suggests a functional behavior similar to that of Zα domains of the interferon-regulated, nucleic acid surveillance proteins ADAR1 and DAI.

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We describe a new method for using neural networks to predict residue contact pairs in a protein. The main inputs to the neural network are a set of 25 measures of correlated mutation between all pairs of residues in two windows of size 5 centered on the residues of interest. While the individual pair-wise correlations are a relatively weak predictor of contact, by training the network on windows of correlation the accuracy of prediction is significantly improved. The neural network is trained on a set of 100 proteins and then tested on a disjoint set of 1033 proteins of known structure. An average predictive accuracy of 21.7% is obtained taking the best L/2 predictions for each protein, where L is the sequence length. Taking the best L/10 predictions gives an average accuracy of 30.7%. The predictor is also tested on a set of 59 proteins from the CASP5 experiment. The accuracy is found to be relatively consistent across different sequence lengths, but to vary widely according to the secondary structure. Predictive accuracy is also found to improve by using multiple sequence alignments containing many sequences to calculate the correlations. (C) 2004 Wiley-Liss, Inc.

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Potato type II serine proteinase inhibitors are proteins that consist of multiple sequence repeats, and exhibit a multidomain structure. The structural domains are circular permutations of the repeat sequence.. as a result or intramolecular domain swapping. Structural studies give indications for the origins of this folding behaviour, and the evolution of the inhibitor family.

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The solution structure of one of the first members of the cyclotide family of macrocyclic peptides to be discovered, circulin B has been determined and compared with that of circulin A and related cyclotides. Cyclotides are mini-proteins derived from plants that have the characteristic features of a head-to-tail cyclised peptide backbone and a knotted arrangement of their three disulfide bonds. First discovered because of their uterotonic or anti-HIV activity, they have also been reported to have activity against a range of Gram positive and Gram negative bacteria as well as fungi. The aim of the current study was to develop structure-activity relationships to rationalise this antimicrobial activity. Comparison of cyclotide structures and activities suggests that the presence and location of cationic residues may be a requirement for activity against Gram negative bacteria. Understanding the topological differences associated with the antimicrobial activity of the cyclotides is of significant interest and potentially may be harnessed for pharmaceutical applications.

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Ketol-acid reductoisomerase (KARI; EC 1.1.1.86) catalyzes two steps in the biosynthesis of branched-chain amino acids. Amino acid sequence comparisons across species reveal that there are two types of this enzyme: a short form (Class 1) found in fungi and most bacteria, and a long form (Class 11) typical of plants. Crystal structures of each have been reported previously. However, some bacteria such as Escherichia coli possess a long form, where the amino acid sequence differs appreciably from that found in plants. Here, we report the crystal structure of the E. coli enzyme at 2.6 A resolution, the first three-dimensional structure of any bacterial Class 11 KARI. The enzyme consists of two domains, one with mixed alpha/beta structure, which is similar to that found in other pyridine nucleotide-dependent dehydrogenases. The second domain is mainly alpha-helical and shows strong evidence of internal duplication. Comparison of the active sites between KARI of E. coli, Pseudomonas aeruginosa, and spinach shows that most residues occupy conserved positions in the active site. E. coli KARI was crystallized as a tetramer, the likely biologically active unit. This contrasts with P. aeruginosa KARI, which forms a dodecamer, and spinach KARI, a dimer. In the E. coli KARI tetramer, a novel subunit-to-subunit interacting surface is formed by a symmetrical pair of bulbous protrusions.

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To ensure signalling fidelity, kinases must act only on a defined subset of cellular targets. Appreciating the basis for this substrate specificity is essential for understanding the role of an individual protein kinase in a particular cellular process. The specificity in the cell is determined by a combination of peptide specificity of the kinase (the molecular recognition of the sequence surrounding the phosphorylation site), substrate recruitment and phosphatase activity. Peptide specificity plays a crucial role and depends on the complementarity between the kinase and the substrate and therefore on their three-dimensional structures. Methods for experimental identification of kinase substrates and characterization of specificity are expensive and laborious, therefore, computational approaches are being developed to reduce the amount of experimental work required in substrate identification. We discuss the structural basis of substrate specificity of protein kinases and review the experimental and computational methods used to obtain specificity information. (c) 2005 Elsevier B.V. All rights reserved.

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Bacterial chaperonin, GroEL, together with its co-chaperonin, GroES, facilitates the folding of a variety of polypeptides. Experiments suggest that GroEL stimulates protein folding by multiple cycles of binding and release. Misfolded proteins first bind to an exposed hydrophobic surface on GroEL. GroES then encapsulates the substrate and triggers its release into the central cavity of the GroEL/ES complex for folding. In this work, we investigate the possibility to facilitate protein folding in molecular dynamics simulations by mimicking the effects of GroEL/ES namely, repeated binding and release, together with spatial confinement. During the binding stage, the (metastable) partially folded proteins are allowed to attach spontaneously to a hydrophobic surface within the simulation box. This destabilizes the structures, which are then transferred into a spatially confined cavity for folding. The approach has been tested by attempting to refine protein structural models generated using the ROSETTA procedure for ab initio structure prediction. Dramatic improvements in regard to the deviation of protein models from the corresponding experimental structures were observed. The results suggest that the primary effects of the GroEL/ES system can be mimicked in a simple coarse-grained manner and be used to facilitate protein folding in molecular dynamics simulations. Furthermore, the results Sur port the assumption that the spatial confinement in GroEL/ES assists the folding of encapsulated proteins.

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Protein structure prediction is a cornerstone of bioinformatics research. Membrane proteins require their own prediction methods due to their intrinsically different composition. A variety of tools exist for topology prediction of membrane proteins, many of them available on the Internet. The server described in this paper, BPROMPT (Bayesian PRediction Of Membrane Protein Topology), uses a Bayesian Belief Network to combine the results of other prediction methods, providing a more accurate consensus prediction. Topology predictions with accuracies of 70% for prokaryotes and 53% for eukaryotes were achieved. BPROMPT can be accessed at http://www.jenner.ac.uk/BPROMPT.

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Motivation: Within bioinformatics, the textual alignment of amino acid sequences has long dominated the determination of similarity between proteins, with all that implies for shared structure, function, and evolutionary descent. Despite the relative success of modern-day sequence alignment algorithms, so-called alignment-free approaches offer a complementary means of determining and expressing similarity, with potential benefits in certain key applications, such as regression analysis of protein structure-function studies, where alignment-base similarity has performed poorly. Results: Here, we offer a fresh, statistical physics-based perspective focusing on the question of alignment-free comparison, in the process adapting results from “first passage probability distribution” to summarize statistics of ensemble averaged amino acid propensity values. In this paper, we introduce and elaborate this approach.