286 research outputs found
Oxidative protein folding in the mitochondrial intermembrane space
Disulfide bond formation is a crucial step for oxidative folding and necessary for the acquisition of a protein's native conformation. Introduction of disulfide bonds is catalyzed in specialized subcellular compartments and requires the coordinated action of specific enzymes. The intermembrane space of mitochondria has recently been found to harbor a dedicated machinery that promotes the oxidative folding of substrate proteins by shuttling disulfide bonds. The newly identified oxidative pathway consists of the redox-regulated receptor Mia40 and the sulfhydryl oxidase Erv1. Proteins destined to the intermembrane space are trapped by a disulfide relay mechanism that involves an electron cascade from the incoming substrate to Mia40, then on to Erv1, and finally to molecular oxygen via cytochrome c. This thiolβdisulfide exchange mechanism is essential for the import and for maintaining the structural stability of the incoming precursors. In this review we describe the mechanistic parameters that define the interaction and oxidation of the substrate proteins in light of the recent publications in the mitochondrial oxidative folding field
Protein disulfide-isomerase interacts with a substrate protein at all stages along its folding pathway
In contrast to molecular chaperones that couple protein folding to ATP hydrolysis, protein disulfide-isomerase (PDI) catalyzes protein folding coupled to formation of disulfide bonds (oxidative folding). However, we do not know how PDI distinguishes folded, partly-folded and unfolded protein substrates. As a model intermediate in an oxidative folding pathway, we prepared a two-disulfide mutant of basic pancreatic trypsin inhibitor (BPTI) and showed by NMR that it is partly-folded and highly dynamic. NMR studies show that it binds to PDI at the same site that binds peptide ligands, with rapid binding and dissociation kinetics; surface plasmon resonance shows its interaction with PDI has a Kd of ca. 10β5 M. For comparison, we characterized the interactions of PDI with native BPTI and fully-unfolded BPTI. Interestingly, PDI does bind native BPTI, but binding is quantitatively weaker than with partly-folded and unfolded BPTI. Hence PDI recognizes and binds substrates via permanently or transiently unfolded regions. This is the first study of PDI's interaction with a partly-folded protein, and the first to analyze this folding catalyst's changing interactions with substrates along an oxidative folding pathway. We have identified key features that make PDI an effective catalyst of oxidative protein folding β differential affinity, rapid ligand exchange and conformational flexibility
Potentials of Mean Force for Protein Structure Prediction Vindicated, Formalized and Generalized
Understanding protein structure is of crucial importance in science, medicine
and biotechnology. For about two decades, knowledge based potentials based on
pairwise distances -- so-called "potentials of mean force" (PMFs) -- have been
center stage in the prediction and design of protein structure and the
simulation of protein folding. However, the validity, scope and limitations of
these potentials are still vigorously debated and disputed, and the optimal
choice of the reference state -- a necessary component of these potentials --
is an unsolved problem. PMFs are loosely justified by analogy to the reversible
work theorem in statistical physics, or by a statistical argument based on a
likelihood function. Both justifications are insightful but leave many
questions unanswered. Here, we show for the first time that PMFs can be seen as
approximations to quantities that do have a rigorous probabilistic
justification: they naturally arise when probability distributions over
different features of proteins need to be combined. We call these quantities
reference ratio distributions deriving from the application of the reference
ratio method. This new view is not only of theoretical relevance, but leads to
many insights that are of direct practical use: the reference state is uniquely
defined and does not require external physical insights; the approach can be
generalized beyond pairwise distances to arbitrary features of protein
structure; and it becomes clear for which purposes the use of these quantities
is justified. We illustrate these insights with two applications, involving the
radius of gyration and hydrogen bonding. In the latter case, we also show how
the reference ratio method can be iteratively applied to sculpt an energy
funnel. Our results considerably increase the understanding and scope of energy
functions derived from known biomolecular structures
A hybrid approach to protein folding problem integrating constraint programming with local search
<p>Abstract</p> <p>Background</p> <p>The protein folding problem remains one of the most challenging open problems in computational biology. Simplified models in terms of lattice structure and energy function have been proposed to ease the computational hardness of this optimization problem. Heuristic search algorithms and constraint programming are two common techniques to approach this problem. The present study introduces a novel hybrid approach to simulate the protein folding problem using constraint programming technique integrated within local search.</p> <p>Results</p> <p>Using the face-centered-cubic lattice model and 20 amino acid pairwise interactions energy function for the protein folding problem, a constraint programming technique has been applied to generate the neighbourhood conformations that are to be used in generic local search procedure. Experiments have been conducted for a few small and medium sized proteins. Results have been compared with both pure constraint programming approach and local search using well-established local move set. Substantial improvements have been observed in terms of final energy values within acceptable runtime using the hybrid approach.</p> <p>Conclusion</p> <p>Constraint programming approaches usually provide optimal results but become slow as the problem size grows. Local search approaches are usually faster but do not guarantee optimal solutions and tend to stuck in local minima. The encouraging results obtained on the small proteins show that these two approaches can be combined efficiently to obtain better quality solutions within acceptable time. It also encourages future researchers on adopting hybrid techniques to solve other hard optimization problems.</p
Equivalent glycemic load (EGL): a method for quantifying the glycemic responses elicited by low carbohydrate foods
BACKGROUND: Glycemic load (GL) is used to quantify the glycemic impact of high-carbohydrate (CHO) foods, but cannot be used for low-CHO foods. Therefore, we evaluated the accuracy of equivalent-glycemic-load (EGL), a measure of the glycemic impact of low-CHO foods defined as the amount of CHO from white-bread (WB) with the same glycemic impact as one serving of food. METHODS: Several randomized, cross-over trials were performed by a contract research organization using overnight-fasted healthy subjects drawn from a pool of 63 recruited from the general population by newspaper advertisement. Incremental blood-glucose response area-under-the-curve (AUC) elicited by 0, 5, 10, 20, 35 and 50 g CHO portions of WB (WB-CHO) and 3, 5, 10 and 20 g glucose were measured. EGL values of the different doses of glucose and WB and 4 low-CHO foods were determined as: EGL = (F-B)/M, where F is AUC after food and B is y-intercept and M slope of the regression of AUC on grams WB-CHO. The dose-response curves of WB and glucose were used to derive an equation to estimate GL from EGL, and the resulting values compared to GL calculated from the glucose dose-response curve. The accuracy of EGL was assessed by comparing the GL (estimated from EGL) values of the 4 doses of oral-glucose with the amounts actually consumed. RESULTS: Over 0β50 g WB-CHO (n = 10), the dose-response curve was non-linear, but over the range 0β20 g the curve was indistinguishable from linear, with AUC after 0, 5, 10 and 20 g WB-CHO, 10 Β± 1, 28 Β± 2, 58 Β± 5 and 100 Β± 6 mmol Γ min/L, differing significantly from each other (n = 48). The difference between GL values estimated from EGL and those calculated from the dose-response curve was 0 g (95% confidence-interval, Β± 0.5 g). The difference between the GL values of the 4 doses of glucose estimated from EGL, and the amounts of glucose actually consumed was 0.2 g (95% confidence-interval, Β± 1 g). CONCLUSION: EGL, a measure of the glycemic impact of low-carbohydrate foods, is valid across the range of 0β20 g CHO, accurate to within 1 g, and at least sensitive enough to detect a glycemic response equivalent to that produced by 3 g oral-glucose in 10 subjects
Inferring stabilizing mutations from protein phylogenies : application to influenza hemagglutinin
One selection pressure shaping sequence evolution is the requirement that a protein fold with sufficient stability to perform its biological functions. We present a conceptual framework that explains how this requirement causes the probability that a particular amino acid mutation is fixed during evolution to depend on its effect on protein stability. We mathematically formalize this framework to develop a Bayesian approach for inferring the stability effects of individual mutations from homologous protein sequences of known phylogeny. This approach is able to predict published experimentally measured mutational stability effects (ΞΞG values) with an accuracy that exceeds both a state-of-the-art physicochemical modeling program and the sequence-based consensus approach. As a further test, we use our phylogenetic inference approach to predict stabilizing mutations to influenza hemagglutinin. We introduce these mutations into a temperature-sensitive influenza virus with a defect in its hemagglutinin gene and experimentally demonstrate that some of the mutations allow the virus to grow at higher temperatures. Our work therefore describes a powerful new approach for predicting stabilizing mutations that can be successfully applied even to large, complex proteins such as hemagglutinin. This approach also makes a mathematical link between phylogenetics and experimentally measurable protein properties, potentially paving the way for more accurate analyses of molecular evolution
Static and dynamic characteristics of protein contact networks
The principles underlying protein folding remains one of Nature's puzzles
with important practical consequences for Life. An approach that has gathered
momentum since the late 1990's, looks at protein hetero-polymers and their
folding process through the lens of complex network analysis. Consequently,
there is now a body of empirical studies describing topological characteristics
of protein macro-molecules through their contact networks and linking these
topological characteristics to protein folding. The present paper is primarily
a review of this rich area. But it delves deeper into certain aspects by
emphasizing short-range and long-range links, and suggests unconventional
places where "power-laws" may be lurking within protein contact networks.
Further, it considers the dynamical view of protein contact networks. This
closer scrutiny of protein contact networks raises new questions for further
research, and identifies new regularities which may be useful to parameterize a
network approach to protein folding. Preliminary experiments with such a model
confirm that the regularities we identified cannot be easily reproduced through
random effects. Indeed, the grand challenge of protein folding is to elucidate
the process(es) which not only generates the specific and diverse linkage
patterns of protein contact networks, but also reproduces the dynamic behavior
of proteins as they fold. Keywords: network analysis, protein contact networks,
protein foldingComment: Added Appendix
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