354 research outputs found
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
Lower objectively measured physical activity is linked with perceived risk of hypoglycemia in type 1 diabetes
Aims
Compare physical activity (PA) levels in adults with and without type 1 diabetes and identify diabetes-specific barriers to PA.
Methods
Forty-four individuals with type 1 diabetes and 77 non-diabetic controls in the Coronary Artery Calcification in Type 1 Diabetes study wore an accelerometer for 2 weeks. Moderate-to-vigorous physical activity (MVPA) was compared by diabetes status using multiple linear regression. The Barriers to Physical Activity in Type 1 Diabetes questionnaire measured diabetes-specific barriers to PA, and the Clarke hypoglycemia awareness questionnaire measured hypoglycemia frequency.
Results
Individuals with type 1 diabetes engaged in less MVPA, fewer bouts of MVPA, and spent less time in MVPA bouts per week than individuals without diabetes (all p 0.05). The most common diabetes-specific barrier to PA was risk of hypoglycemia. Individuals with diabetes reporting barriers spent less time in MVPA bouts per week than those not reporting barriers (p = 0.047).
Conclusions
Individuals with type 1 diabetes engage in less MVPA than those without diabetes despite similar self-reported levels, with the main barrier being perceived risk of hypoglycemia. Adults with type 1 diabetes require guidance to meet current PA guidelines and reduce cardiovascular risk
The crust in the pamir: Insights from receiver functions
The Cenozoic convergence between India and Asia has created Earth's thickest crust in the Pamir‐Tibet Plateau by extreme crustal shortening. Here we study the crustal structure of the Pamir and western Tian Shan, the adjacent margins of the Tajik, Tarim, and Ferghana Basins, and the Hindu Kush, using data collected by temporary seismic experiments. We derive, compare, and combine independent observations from P and S receiver functions. The obtained Moho depth varies from ~40 km below the basins to a double‐normal thickness of 65–75 km underneath the Pamir and Hindu Kush. A Moho doublet—with the deeper interface down to a depth of ~90 km—coincides with the arc of intermediate‐depth seismicity underneath the Pamir, where Asian continental lower crust delaminates and rolls back. The crust beneath most of the Central and South Pamir has a low Vp/Vs ratio (<1.70), suggesting a dominantly felsic composition, probably a result of delamination/foundering of the mafic rocks of the lower crust. Beneath the Cenozoic gneiss domes of the Central and South Pamir, which represent extensional core complexes, the Vp/Vs ratios are moderate to high (~1.75), consistent with the previously observed, midcrustal low‐velocity zones, implying the presence of crustal partial melts. Even higher crustal average Vp/Vs ratios up to 1.90 are found in the sedimentary basins and along the Main Pamir Thrust. The ratios along the latter—the active thrust front of the Pamir—may reflect fluid accumulations within a strongly fractured fault system
Multi-Overlap Simulations for Transitions between Reference Configurations
We introduce a new procedure to construct weight factors, which flatten the
probability density of the overlap with respect to some pre-defined reference
configuration. This allows one to overcome free energy barriers in the overlap
variable. Subsequently, we generalize the approach to deal with the overlaps
with respect to two reference configurations so that transitions between them
are induced. We illustrate our approach by simulations of the brainpeptide
Met-enkephalin with the ECEPP/2 energy function using the global-energy-minimum
and the second lowest-energy states as reference configurations. The free
energy is obtained as functions of the dihedral and the root-mean-square
distances from these two configurations. The latter allows one to identify the
transition state and to estimate its associated free energy barrier.Comment: 12 pages, (RevTeX), 14 figures, Phys. Rev. E, submitte
Metropolis simulations of Met-Enkephalin with solvent-accessible area parameterizations
We investigate the solvent-accessible area method by means of Metropolis
simulations of the brain peptide Met-Enkephalin at 300. For the energy
function ECEPP/2 nine atomic solvation parameter (ASP) sets are studied. The
simulations are compared with one another, with simulations with a distance
dependent electrostatic permittivity , and with vacuum
simulations (). Parallel tempering and the biased Metropolis
techniques RM are employed and their performance is evaluated. The measured
observables include energy and dihedral probability densities (pds), integrated
autocorrelation times, and acceptance rates. Two of the ASP sets turn out to be
unsuitable for these simulations. For all other systems selected configurations
are minimized in search of the global energy minima, which are found for the
vacuum and the system, but for none of the ASP models. Other
observables show a remarkable dependence on the ASPs. In particular, we find
three ASP sets for which the autocorrelations at 300K are considerably
smaller than for vacuum simulations.Comment: 10 pages and 8 figure
Knowledge-based energy functions for computational studies of proteins
This chapter discusses theoretical framework and methods for developing
knowledge-based potential functions essential for protein structure prediction,
protein-protein interaction, and protein sequence design. We discuss in some
details about the Miyazawa-Jernigan contact statistical potential,
distance-dependent statistical potentials, as well as geometric statistical
potentials. We also describe a geometric model for developing both linear and
non-linear potential functions by optimization. Applications of knowledge-based
potential functions in protein-decoy discrimination, in protein-protein
interactions, and in protein design are then described. Several issues of
knowledge-based potential functions are finally discussed.Comment: 57 pages, 6 figures. To be published in a book by Springe
Partition Function Zeros and Finite Size Scaling of Helix-Coil Transitions in a Polypeptide
We report on multicanonical simulations of the helix-coil transition of a
polypeptide. The nature of this transition was studied by calculating partition
function zeros and the finite-size scaling of various quantities. Estimates for
critical exponents are presented.Comment: RevTex, 4 eps-files; to appear in Phys. Rev. Le
A combinatorial TIR1/AFB–Aux/IAA co-receptor system for differential sensing of auxin
The plant hormone auxin regulates virtually every aspect of plant growth and development. Auxin acts by binding the F-box protein transport inhibitor response 1 (TIR1) and promotes the degradation of the AUXIN/INDOLE-3-ACETIC ACID (Aux/IAA) transcriptional repressors. Here we show that efficient auxin binding requires assembly of an auxin co-receptor complex consisting of TIR1 and an Aux/IAA protein. Heterologous experiments in yeast and quantitative IAA binding assays using purified proteins showed that different combinations of TIR1 and Aux/IAA proteins form co-receptor complexes with a wide range of auxin-binding affinities. Auxin affinity seems to be largely determined by the Aux/IAA. As there are 6 TIR1/AUXIN SIGNALING F-BOX proteins (AFBs) and 29 Aux/IAA proteins in Arabidopsis thaliana, combinatorial interactions may result in many co-receptors with distinct auxin-sensing properties. We also demonstrate that the AFB5–Aux/IAA co-receptor selectively binds the auxinic herbicide picloram. This co-receptor system broadens the effective concentration range of the hormone and may contribute to the complexity of auxin response
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