1,721,233 research outputs found
Generic nature of the condensed states of proteins
No full textProteins undergoing liquid–liquid phase separation are being discovered at an increasing rate. Since at the high concentrations present in the cell most proteins would be expected to form a liquid condensed state, this state should be considered to be a fundamental state of proteins along with the native state and the amyloid state. Here we discuss the generic nature of the liquid-like and solid-like condensed states, and describe a wide variety of biological functions conferred by these condensed states
Correlation between mRNA expression levels and protein aggregation propensities in subcellular localisations
No full textWe investigate the relationship between mRNA expression levels and protein aggregation propensities at the proteomic level, and find that these quantities exhibit a significant correlation when they are averaged across subcellular localisations. In order to investigate this phenomenon, we study the dependence of mRNA expression levels and protein aggregation propensities on the volume of the corresponding subcellular localisations, finding that proteins tend to be increasingly more abundant and more soluble with decreasing volumes of their subcellular localisations. These results indicate that the maintenance of protein solubility plays an even greater role than previously thought in sustaining protein homeostasis. © 2009 The Royal Society of Chemistry
A mean field study of the temperature dependence of the layer magnetizations in a semi-infinite Ising model
No full textMagnetic phase transitions of Ising surfaces with modified surface-bulk coupling: a Monte Carlo study
No full textHot sandpiles
No full textA temperature-like parameter is introduced in ordinary sandpiles models. A temperature-dependent probability distribution is assigned for the sand toppling on sites of any height. In mean-field theory criticality is obtained for all the values of temperature and no characteristic avalanche size appears. Numerical simulations support the existence of criticality at any temperature with apparently continuously varying critical exponents
The Zyggregator method for predicting protein aggregation propensities
No full textProtein aggregation causes many devastating neurological and systemic diseases and represents a major problem in the preparation of recombinant proteins in biotechnology. Major advances in understanding the causes of this phenomenon have been made through the realisation that the analysis of the physico-chemical characteristics of the amino acids can provide accurate predictions about the rates of growth of the misfolded assemblies and the specific regions of the sequences that promote aggregation. More recently it has also been shown that the toxicity in vivo of protein aggregates can be predicted by estimating the propensity of polypeptide chains to form protofibrillar assemblies. In this tutorial review we describe the development of these predictions made through the Zyggregator method and the applications that have been explored so far. © The Royal Society of Chemistry
Proteome-Level Interplay between Folding and Aggregation Propensities of Proteins
No full textWith the advent of proteomics, there is an increasing need of tools for predicting the properties of large numbers of proteins by using the information provided by their amino acid sequences, even in the absence of the knowledge of their structures. One of the most important types of predictions concerns whether proteins will fold or aggregate. Here, we study the competition between these two processes by analyzing the relationship between the folding and aggregation propensity profiles for the human and Escherichia coli proteomes. These profiles are calculated, respectively, using the CamFold method, which we introduce in this work, and the Zyggregator method. Our results indicate that the kinetic behavior of proteins is, to a large extent, determined by the interplay between regions of low folding and high aggregation propensities. © 2010
Sequence-Based Prediction of Protein Behavior
No full textThis chapter contains sections titled: Introduction The Strategy of the Zyggregator Predictions Aggregation Under Other Conditions Prediction of the Cellular Toxicity of Protein Aggregates Relationship to Other Methods of Predicting Protein Aggregation Propensities Competition between Folding and Aggregation of Proteins Prediction of Protein Solubility from the Competition between Folding and Aggregation Sequence‐Based Prediction of Protein Interactions with Molecular Chaperones Summary Reference
A Condensation-Ordering Mechanism in Nanoparticle-Catalyzed Peptide Aggregation
Full text linkNanoparticles introduced in living cells are capable of strongly promoting the aggregation of peptides and proteins. We use here molecular dynamics simulations to characterise in detail the process by which nanoparticle surfaces catalyse the self-assembly of peptides into fibrillar structures. The simulation of a system of hundreds of peptides over the millisecond timescale enables us to show that the mechanism of aggregation involves a first phase in which small structurally disordered oligomers assemble onto the nanoparticle and a second phase in which they evolve into highly ordered as their size increases
Small-world view of the amino acids that play a key role in protein folding
No full textWe use geometrical considerations to provide a different perspective on the fact that a few selected amino acids, the so-called key residues, act as nucleation centers for protein folding. By constructing graphs corresponding to protein structures we show that they have the small-world feature of having a limited set of vertices with large connectivity. These vertices correspond to the key residues that play the role of hubs in the network of interactions that stabilize the structure of the transition state
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