Browse
Submit Data
Databases
API
Help

Dataset Information

15 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Structure prediction of polyglutamine disease proteins: comparison of methods.

ABSTRACT: The expansion of polyglutamine (poly-Q) repeats in several unrelated proteins is associated with at least ten neurodegenerative diseases. The length of the poly-Q regions plays an important role in the progression of the diseases. The number of glutamines (Q) is inversely related to the onset age of these polyglutamine diseases, and the expansion of poly-Q repeats has been associated with protein misfolding. However, very little is known about the structural changes induced by the expansion of the repeats. Computational methods can provide an alternative to determine the structure of these poly-Q proteins, but it is important to evaluate their performance before large scale prediction work is done.In this paper, two popular protein structure prediction programs, I-TASSER and Rosetta, have been used to predict the structure of the N-terminal fragment of a protein associated with Huntington's disease with 17 glutamines. Results show that both programs have the ability to find the native structures, but I-TASSER performs better for the overall task.Both I-TASSER and Rosetta can be used for structure prediction of proteins with poly-Q repeats. Knowledge of poly-Q structure may significantly contribute to development of therapeutic strategies for poly-Q diseases.

SUBMITTER: Wen J

PROVIDER: S-EPMC4110737 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Similar Datasets

Ubiquilin-2 differentially regulates polyglutamine disease proteins.

Project description:Divergent protein context helps explain why polyglutamine expansion diseases differ clinically and pathologically. This heterogeneity may also extend to how polyglutamine disease proteins are handled by cellular pathways of proteostasis. Studies suggest, for example, that the ubiquitin-proteasome shuttle protein Ubiquilin-2 (UBQLN2) selectively interacts with specific polyglutamine disease proteins. Here we employ cellular models, primary neurons and mouse models to investigate the potential differential regulation by UBQLN2 of two polyglutamine disease proteins, huntingtin (HTT) and ataxin-3 (ATXN3). In cells, overexpressed UBQLN2 selectively lowered levels of full-length pathogenic HTT but not of HTT exon 1 fragment or full-length ATXN3. Consistent with these results, UBQLN2 specifically reduced accumulation of aggregated mutant HTT but not mutant ATXN3 in mouse models of Huntington's disease (HD) and spinocerebellar ataxia type 3 (SCA3), respectively. Normally a cytoplasmic protein, UBQLN2 translocated to the nuclei of neurons in HD mice but not in SCA3 mice. Remarkably, instead of reducing the accumulation of nuclear mutant ATXN3, UBQLN2 induced an accumulation of cytoplasmic ATXN3 aggregates in neurons of SCA3 mice. Together these results reveal a selective action of UBQLN2 toward polyglutamine disease proteins, indicating that polyglutamine expansion alone is insufficient to promote UBQLN2-mediated clearance of this class of disease proteins. Additional factors, including nuclear translocation of UBQLN2, may facilitate its action to clear intranuclear, aggregated disease proteins like HTT.

| S-EPMC7471500 | biostudies-literature

Methods of protein structure comparison.

Project description:Despite its apparent simplicity, the problem of quantifying the differences between two structures of the same protein or complex is nontrivial and continues evolving. In this chapter, we described several methods routinely used to compare computational models to experimental answers in several modeling assessments. The two major classes of measures, positional distance-based and contact-based, are presented, compared, and analyzed. The most popular measure of the first class, the global RMSD, is shown to be the least representative of the degree of structural similarity because it is dominated by the largest error. Several distance-dependent algorithms designed to attenuate the drawbacks of RMSD are described. Measures of the second class, contact-based, are shown to be more robust and relevant. We also illustrate the importance of using combined measures, utility-based measures, and the role of the distributions derived from the pairs of experimental structures in interpreting the results.

| S-EPMC4321859 | biostudies-literature

Structure prediction of membrane proteins.

Project description:There is a large gap between the number of membrane protein (MP) sequences and that of their decoded 3D structures, especially high-resolution structures, due to difficulties in crystal preparation of MPs. However, detailed knowledge of the 3D structure is required for the fundamental understanding of the function of an MP and the interactions between the protein and its inhibitors or activators. In this paper, some computational approaches that have been used to predict MP structures are discussed and compared.

| S-EPMC5172438 | biostudies-literature

Disease-associated polyglutamine stretches in monomeric huntingtin adopt a compact structure.

Project description:Abnormal polyglutamine (polyQ) tracts are the only common feature in nine proteins that each cause a dominant neurodegenerative disorder. In Huntington's disease, tracts longer than 36 glutamines in the protein huntingtin (htt) cause degeneration. In situ, monoclonal antibody 3B5H10 binds to different htt fragments in neurons in proportion to their toxicity. Here, we determined the structure of 3B5H10 Fab to 1.9 Å resolution by X-ray crystallography. Modeling demonstrates that the paratope forms a groove suitable for binding two ?-rich polyQ strands. Using small-angle X-ray scattering, we confirmed that the polyQ epitope recognized by 3B5H10 is a compact two-stranded hairpin within monomeric htt and is abundant in htt fragments unbound to antibody. Thus, disease-associated polyQ stretches preferentially adopt compact conformations. Since 3B5H10 binding predicts degeneration, this compact polyQ structure may be neurotoxic.

| S-EPMC3358578 | biostudies-literature

Pharmacological induction of heat-shock proteins alleviates polyglutamine-mediated motor neuron disease.

Project description:Spinal and bulbar muscular atrophy (SBMA) is an adult-onset motor neuron disease caused by the expansion of a trinucleotide CAG repeat encoding the polyglutamine tract in the first exon of the androgen receptor gene (AR). The pathogenic, polyglutamine-expanded AR protein accumulates in the cell nucleus in a ligand-dependent manner and inhibits transcription by interfering with transcriptional factors and coactivators. Heat-shock proteins (HSPs) are stress-induced chaperones that facilitate the refolding and, thus, the degradation of abnormal proteins. Geranylgeranylacetone (GGA), a nontoxic antiulcer drug, has been shown to potently induce HSP expression in various tissues, including the central nervous system. In a cell model of SBMA, GGA increased the levels of Hsp70, Hsp90, and Hsp105 and inhibited cell death and the accumulation of pathogenic AR. Oral administration of GGA also up-regulated the expression of HSPs in the central nervous system of SBMA-transgenic mice and suppressed nuclear accumulation of the pathogenic AR protein, resulting in amelioration of polyglutamine-dependent neuromuscular phenotypes. These observations suggest that, although a high dose appears to be needed for clinical effects, oral GGA administration is a safe and promising therapeutic candidate for polyglutamine-mediated neurodegenerative diseases, including SBMA.

| S-EPMC1275598 | biostudies-literature

Empirical comparison of structure-based pathway methods.

Project description:Multiple methods have been proposed to estimate pathway activities from expression profiles, and yet, there is not enough information available about the performance of those methods. This makes selection of a suitable tool for pathway analysis difficult. Although methods based on simple gene lists have remained the most common approach, various methods that also consider pathway structure have emerged. To provide practical insight about the performance of both list-based and structure-based methods, we tested six different approaches to estimate pathway activities in two different case study settings of different characteristics. The first case study setting involved six renal cell cancer data sets, and the differences between expression profiles of case and control samples were relatively big. The second case study setting involved four type 1 diabetes data sets, and the profiles of case and control samples were more similar to each other. In general, there were marked differences in the outcomes of the different pathway tools even with the same input data. In the cancer studies, the results of a tested method were typically consistent across the different data sets, yet different between the methods. In the more challenging diabetes studies, almost all the tested methods detected as significant only few pathways if any.

| S-EPMC4793894 | biostudies-literature

Structure prediction of magnetosome-associated proteins.

Project description:Magnetotactic bacteria (MTB) are Gram-negative bacteria that can navigate along geomagnetic fields. This ability is a result of a unique intracellular organelle, the magnetosome. These organelles are composed of membrane-enclosed magnetite (Fe3O4) or greigite (Fe3S4) crystals ordered into chains along the cell. Magnetosome formation, assembly, and magnetic nano-crystal biomineralization are controlled by magnetosome-associated proteins (MAPs). Most MAP-encoding genes are located in a conserved genomic region - the magnetosome island (MAI). The MAI appears to be conserved in all MTB that were analyzed so far, although the MAI size and organization differs between species. It was shown that MAI deletion leads to a non-magnetic phenotype, further highlighting its important role in magnetosome formation. Today, about 28 proteins are known to be involved in magnetosome formation, but the structures and functions of most MAPs are unknown. To reveal the structure-function relationship of MAPs we used bioinformatics tools in order to build homology models as a way to understand their possible role in magnetosome formation. Here we present a predicted 3D structural models' overview for all known Magnetospirillum gryphiswaldense strain MSR-1 MAPs.

| S-EPMC3905215 | biostudies-literature

Praja1 ubiquitin ligase facilitates degradation of polyglutamine proteins and suppresses polyglutamine-mediated toxicity.

Project description:A network of chaperones and ubiquitin ligases sustain intracellular proteostasis and is integral in preventing aggregation of misfolded proteins associated with various neurodegenerative diseases. Using cell-based studies of polyglutamine (polyQ) diseases, spinocerebellar ataxia type 3 (SCA3) and Huntington's disease (HD), we aimed to identify crucial ubiquitin ligases that protect against polyQ aggregation. We report here that Praja1 (PJA1), a Ring-H2 ubiquitin ligase abundantly expressed in the brain, is diminished when polyQ repeat proteins (ataxin-3/huntingtin) are expressed in cells. PJA1 interacts with polyQ proteins and enhances their degradation, resulting in reduced aggregate formation. Down-regulation of PJA1 in neuronal cells increases polyQ protein levels vis-a-vis their aggregates, rendering the cells vulnerable to cytotoxic stress. Finally, PJA1 suppresses polyQ toxicity in yeast and rescues eye degeneration in a transgenic Drosophila model of SCA3. Thus, our findings establish PJA1 as a robust ubiquitin ligase of polyQ proteins and induction of which might serve as an alternative therapeutic strategy in handling cytotoxic polyQ aggregates.

| S-EPMC8351749 | biostudies-literature

Generalized ensemble methods for de novo structure prediction.

Project description:Current methods for predicting protein structure depend on two interrelated components: (i) an energy function that should have a low value near the correct structure and (ii) a method for searching through different conformations of the polypeptide chain. Identification of the most efficient search methods is essential if we are to be able to apply such methods broadly and with confidence. In addition, efficient search methods provide a rigorous test of existing energy functions, which are generally knowledge-based and contain different terms added together with arbitrary weights. Here, we test different search methods with one of the most accurate and predictive energy functions, namely Rosetta the knowledge-based force-field from Baker's group [Simons K, Kooperberg C, Huang E, Baker D (1997) J Mol Biol 268:209-225]. We use an implementation of a generalized ensemble search method to scale relevant parts of the energy function. This method, known as Hamiltonian Replica Exchange Monte Carlo, outperforms the original Monte Carlo Simulated Annealing used in the Rosetta package in terms of sampling low-energy states. It also outperforms another widely used generalized ensemble search method known as Temperature Replica Exchange Monte Carlo. Our results reveal clear deficiencies in the low-resolution Rosetta energy function in that the lowest energy structures are not necessarily the most native-like. By using a set of nonnative low-energy structures found by our extensive sampling, we discovered that the long-range and short-range backbone hydrogen-bonding energy terms of the Rosetta energy discriminate between the nonnative and native-like structures significantly better than the low-resolution score used in Rosetta.

| S-EPMC2631076 | biostudies-literature

Structure-Leveraged Methods in Breast Cancer Risk Prediction.

Project description:Predicting breast cancer risk has long been a goal of medical research in the pursuit of precision medicine. The goal of this study is to develop novel penalized methods to improve breast cancer risk prediction by leveraging structure information in electronic health records. We conducted a retrospective case-control study, garnering 49 mammography descriptors and 77 high-frequency/low-penetrance single-nucleotide polymorphisms (SNPs) from an existing personalized medicine data repository. Structured mammography reports and breast imaging features have long been part of a standard electronic health record (EHR), and genetic markers likely will be in the near future. Lasso and its variants are widely used approaches to integrated learning and feature selection, and our methodological contribution is to incorporate the dependence structure among the features into these approaches. More specifically, we propose a new methodology by combining group penalty and [Formula: see text] (1 ≤ p ≤ 2) fusion penalty to improve breast cancer risk prediction, taking into account structure information in mammography descriptors and SNPs. We demonstrate that our method provides benefits that are both statistically significant and potentially significant to people's lives.

| S-EPMC5446896 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data