21 research outputs found
Effect of Hydrophobic Interactions on the Folding Mechanism of β‑Hairpins
Hydrophobic interactions are essential
in stabilizing protein structures.
How they affect the folding pathway and kinetics, however, is less
clear. We used time-resolved infrared spectroscopy to study the dynamics
of hydrophobic interactions of β-hairpin variants of the sequence
Trpzip2 (SWTWÂENGKWÂTWK-NH2) that is stabilized by two cross-strand
Trp–Trp pairs. The hydrophobicity strength was varied by substituting
the tryptophans pairwise by either tyrosines or valines. Relaxation
dynamics were induced by a laser-excited temperature jump, which separately
probed for the loss of the cross-strand β-hairpin interaction
and the rise of the disordered structure. All substitutions tested
result in reduced thermal stability, lower transition temperatures,
and faster dynamics compared to Trpzip2. However, the changes in folding
dynamics depend on the amino acid substituted for Trp. The aromatic
substitution of Tyr for Trp results in the same kinetics for the unfolding
of sheet and growth of disorder, with similar activation energies,
independent of the substitution position. Substitution of Trp with
a solely hydrophobic Val results in even faster kinetics than substitution
with Tyr but is additionally site-dependent. If the hairpin has a
Val pair close to its termini, the rate constants for loss of sheet
and gain of disorder are the same, but if the pair is close to the
turn, the sheet and disorder components show different relaxation
kinetics. The Trp → Val substitutions reveal that hydrophobic
interactions alone weakly stabilize the hairpin structure, but adding
edge-to-face aromatic interaction strengthens it, and both modify
the complex folding process
L'Écho : grand quotidien d'information du Centre Ouest
12 février 19361936/02/12 (A65).Appartient à l’ensemble documentaire : PoitouCh
Global Food Demand Scenarios for the 21<i><sup>st</sup></i> Century
<div><p>Long-term food demand scenarios are an important tool for studying global food security and for analysing the environmental impacts of agriculture. We provide a simple and transparent method to create scenarios for future plant-based and animal-based calorie demand, using time-dependent regression models between calorie demand and income. The scenarios can be customized to a specific storyline by using different input data for gross domestic product (GDP) and population projections and by assuming different functional forms of the regressions. Our results confirm that total calorie demand increases with income, but we also found a non-income related positive time-trend. The share of animal-based calories is estimated to rise strongly with income for low-income groups. For high income groups, two ambiguous relations between income and the share of animal-based products are consistent with historical data: First, a positive relation with a strong negative time-trend and second a negative relation with a slight negative time-trend. The fits of our regressions are highly significant and our results compare well to other food demand estimates. The method is exemplarily used to construct four food demand scenarios until the year 2100 based on the storylines of the IPCC Special Report on Emissions Scenarios (SRES). We find in all scenarios a strong increase of global food demand until 2050 with an increasing share of animal-based products, especially in developing countries.</p></div
Regression parameters with linear time dependence for total calories for formulation <i>g</i><sub><i>A</i></sub> (Eq 3).
<p>Significance levels for <i>p</i>-values are denoted by (***): < 0.001, (**): ∈ [0.001, 0.01), (*): ∈ [0.01, 0.05), (.): ∈ [0.05, 0.1).</p
Statistical properties of regression models on total calorie demand (<i>C</i><sub><i>T</i></sub>) and animal-based calorie share (<i>C</i><sub><i>LS</i></sub>).
<p>Significance levels for <i>p</i>-values are denoted by (***): < 0.001, (**): ∈ [0.001, 0.01), (*): ∈ [0.01, 0.05), (.): ∈ [0.05, 0.1).</p
pH-Jump Induced Leucine Zipper Folding beyond the Diffusion Limit
The folding of a pH-sensitive leucine
zipper, that is, a GCN4 mutant
containing eight glutamic acid residues, has been investigated. A
pH-jump induced by a caged proton (<i>o</i>-nitrobenzaldehyde,
oNBA) is employed to initiate the process, and time-resolved IR spectroscopy
of the amide I band is used to probe it. The experiment has been carefully
designed to minimize the buffer capacity of the sample solution so
that a large pH jump can be achieved, leading to a transition from
a completely unfolded to a completely folded state with a single laser
shot. In order to eliminate the otherwise rate-limiting diffusion-controlled
step of the association of two peptides, they have been covalently
linked. The results for the folding kinetics of the cross-linked peptide
are compared with those of an unlinked peptide, which reveals a detailed
picture of the folding mechanism. That is, folding occurs in two steps,
one on an ∼1–2 μs time scale leading to a partially
folded α-helix even in the monomeric case and a second one leading
to the final coiled-coil structure on distinctively different time
scales of ∼30 μs for the cross-linked peptide and ∼200
μs for the unlinked peptide. By varying the initial pH, it is
found that the folding mechanism is consistent with a thermodynamic
two-state model, despite the fact that a transient intermediate is
observed in the kinetic experiment
Regression parameters for animal-based calorie share <i>h</i><sub><i>B</i></sub> (Eq 8).
<p>Significance levels for <i>p</i>-values are denoted by (***): < 0.001, (**): ∈ [0.001, 0.01), (*): ∈ [0.01, 0.05), (.): ∈ [0.05, 0.1).</p
Global Food Demand Scenarios for the 21<sup>st</sup> - Fig 2 Century
<p>Model estimation for total calorie demand <i>C</i><sub><i>T</i></sub> with formulations <i>g</i><sub><i>A</i></sub> (red colors) and <i>g</i><sub><i>B</i></sub> (blue colors). Predictions for years 1961, 1980, 2000, 2050 and 2100 (lines) as well as reported data for 1961, 1980 and 2000 (dots) with a) linear axes scale and b) logarithmic axes scale.</p
Data sources.
<p>ItC: Item code, EC: Element code, IC: Indicator code. Download of FAO data from <a href="http://faostat.fao.org" target="_blank">http://faostat.fao.org</a> on 27.10.2010 and from Worldbank from <a href="http://data.worldbank.org" target="_blank">http://data.worldbank.org</a> on 13.09.2011.</p
Significant trends (values only shown for p < 0.05) for total calorie demand (kcal capita<sup>−1</sup> d<sup>−1</sup> a<sup>−1</sup>) between 1988 and 2007 for FAO data and between 1990 and 2010 for all scenarios estimated using the Mann-Kendall test.
<p>Significant trends (values only shown for p < 0.05) for total calorie demand (kcal capita<sup>−1</sup> d<sup>−1</sup> a<sup>−1</sup>) between 1988 and 2007 for FAO data and between 1990 and 2010 for all scenarios estimated using the Mann-Kendall test.</p