9,988 research outputs found
Dissecting Ubiquitin Folding Using the Self-Organized Polymer Model
Folding of Ubiquitin (Ub) is investigated at low and neutral pH at different
temperatures using simulations of the coarse-grained Self-Organized-Polymer
model with side chains. The calculated radius of gyration, showing dramatic
variations with pH, is in excellent agreement with scattering experiments. At
Ub folds in a two-state manner at low and neutral pH. Clustering analysis
of the conformations sampled in equilibrium folding trajectories at , with
multiple transitions between the folded and unfolded states, show a network of
metastable states connecting the native and unfolded states. At low and neutral
pH, Ub folds with high probability through a preferred set of conformations
resulting in a pH-dependent dominant folding pathway. Folding kinetics reveal
that Ub assembly at low pH occurs by multiple pathways involving a combination
of nucleation-collapse and diffusion collision mechanism. The mechanism by
which Ub folds is dictated by the stability of the key secondary structural
elements responsible for establishing long range contacts and collapse of Ub.
Nucleation collapse mechanism holds if the stability of these elements are
marginal, as would be the case at elevated temperatures. If the lifetimes
associated with these structured microdomains are on the order of hundreds of
then Ub folding follows the diffusion-collision mechanism with
intermediates many of which coincide with those found in equilibrium. Folding
at neutral pH is a sequential process with a populated intermediate resembling
that sampled at equilibrium. The transition state structures, obtained using a
analysis, are homogeneous and globular with most of the secondary
and tertiary structures being native-like. Many of our findings are not only in
agreement with experiments but also provide missing details not resolvable in
standard experiments
Assessing the effect of dynamics on the closed-loop protein-folding hypothesis
The closed-loop (loop-n-lock) hypothesis of protein folding suggests that loops of about 25 residues, closed through interactions between the loop ends (locks), play an important role in protein structure. Coarse-grain elastic network simulations, and examination of loop lengths in a diverse set of proteins, each supports a bias towards loops of close to 25 residues in length between residues of high stability. Previous studies have established a correlation between total contact distance (TCD), a metric of sequence distances between contacting residues (cf. contact order), and the log-folding rate of a protein. In a set of 43 proteins, we identify an improved correlation (
r
2
= 0.76), when the metric is restricted to residues contacting the locks, compared to the equivalent result when all residues are considered (
r
2
= 0.65). This provides qualified support for the hypothesis, albeit with an increased emphasis upon the importance of a much larger set of residues surrounding the locks. Evidence of a similar-sized protein core/extended nucleus (with significant overlap) was obtained from TCD calculations in which residues were successively eliminated according to their hydrophobicity and connectivity, and from molecular dynamics simulations. Our results suggest that while folding is determined by a subset of residues that can be predicted by application of the closed-loop hypothesis, the original hypothesis is too simplistic; efficient protein folding is dependent on a considerably larger subset of residues than those involved in lock formation.
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Quantitative principles of cis-translational control by general mRNA sequence features in eukaryotes.
BackgroundGeneral translational cis-elements are present in the mRNAs of all genes and affect the recruitment, assembly, and progress of preinitiation complexes and the ribosome under many physiological states. These elements include mRNA folding, upstream open reading frames, specific nucleotides flanking the initiating AUG codon, protein coding sequence length, and codon usage. The quantitative contributions of these sequence features and how and why they coordinate to control translation rates are not well understood.ResultsHere, we show that these sequence features specify 42-81% of the variance in translation rates in Saccharomyces cerevisiae, Schizosaccharomyces pombe, Arabidopsis thaliana, Mus musculus, and Homo sapiens. We establish that control by RNA secondary structure is chiefly mediated by highly folded 25-60 nucleotide segments within mRNA 5' regions, that changes in tri-nucleotide frequencies between highly and poorly translated 5' regions are correlated between all species, and that control by distinct biochemical processes is extensively correlated as is regulation by a single process acting in different parts of the same mRNA.ConclusionsOur work shows that general features control a much larger fraction of the variance in translation rates than previously realized. We provide a more detailed and accurate understanding of the aspects of RNA structure that directs translation in diverse eukaryotes. In addition, we note that the strongly correlated regulation between and within cis-control features will cause more even densities of translational complexes along each mRNA and therefore more efficient use of the translation machinery by the cell
Protein secondary structure: Entropy, correlations and prediction
Is protein secondary structure primarily determined by local interactions
between residues closely spaced along the amino acid backbone, or by non-local
tertiary interactions? To answer this question we have measured the entropy
densities of primary structure and secondary structure sequences, and the local
inter-sequence mutual information density. We find that the important
inter-sequence interactions are short ranged, that correlations between
neighboring amino acids are essentially uninformative, and that only 1/4 of the
total information needed to determine the secondary structure is available from
local inter-sequence correlations. Since the remaining information must come
from non-local interactions, this observation supports the view that the
majority of most proteins fold via a cooperative process where secondary and
tertiary structure form concurrently. To provide a more direct comparison to
existing secondary structure prediction methods, we construct a simple hidden
Markov model (HMM) of the sequences. This HMM achieves a prediction accuracy
comparable to other single sequence secondary structure prediction algorithms,
and can extract almost all of the inter-sequence mutual information. This
suggests that these algorithms are almost optimal, and that we should not
expect a dramatic improvement in prediction accuracy. However, local
correlations between secondary and primary structure are probably of
under-appreciated importance in many tertiary structure prediction methods,
such as threading.Comment: 8 pages, 5 figure
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