1,721,023 research outputs found
Recognition of coarse-grained protein tertiary structure
No full textA model of the protein backbone is considered in which each residue is characterized by the location of its C-alpha atom and one of a discrete set of conformal (phi, psi) states. We investigate the key differences between a description that offers a locally precise fit to known backbone structures and one that provides a globally accurate fit to protein structures. Using a statistical scoring scheme and threading, a protein's local best-fit conformation is highly recognizable, but its global structure cannot be directly determined from an amino acid sequence. The incorporation of information about the conformal states of neighboring residues along the chain allows one to accurately translate the local structure into a global structure. We present a two-step algorithm, which recognizes up to 95% of the tested protein native-state structures to within a 2.5 Angstrom root mean square deviation
Inverse problem for multivariate time series using dynamical latent variables
No full textFactor analysis is a well known statistical method to describe the variability among
observed variables in terms of a smaller number of unobserved latent variables called
factors. While dealing with multivariate time series, the temporal correlation structure
of data may be modeled by including correlations in latent factors, but a crucial choice
is the covariance function to be implemented. We show that analyzing multivariate time
series in terms of latent Gaussian processes, which are mutually independent but with
each of them being characterized by exponentially decaying temporal correlations, leads
to an efficient implementation of the expectation–maximization algorithm for the maximum
likelihood estimation of parameters, due to the properties of block-tridiagonal matrices.
The proposed approach solves an ambiguity known as the identifiability problem, which
renders the solution of factor analysis determined only up to an orthogonal transformation.
Samples with just two temporal points are sufficient for the parameter estimation: hence
the proposed approach may be applied even in the absence of prior information about the
correlation structure of latent variables by fitting the model to pairs of points with varying
time delay. Our modeling allows one to make predictions of the future values of time series
and we illustrate our method by applying it to an analysis of published gene expression data
from cell culture HeLa
System size expansion for systems with an absorbing state
No full textThe well-known van Kampen system size expansion, while of rather general applicability, is shown to fail to reproduce some qualitative features of the time evolution for systems with an absorbing state, apart from a transient initial time interval. We generalize the van Kampen ansatz by introducing a new prescription leading to non-Gaussian fluctuations around the absorbing state. The two expansion predictions are explicitly compared for the infinite range voter model with speciation as a paradigmatic model with an absorbing state. The new expansion, both for a finite size system in the large time limit and at finite time in the large size limit, converges to the exact solution as obtained in a numerical implementation using the Gillespie algorithm. Furthermore, the predicted lifetime distribution is shown to have the correct asymptotic behavior. © 2011 American Physical Society
Local sequence-structure relationships in proteins
No full textWe seek to understand the interplay between amino acid sequence and local structure in proteins. Are some amino acids unique in their ability to fit harmoniously into certain local structures? What is the role of sequence in sculpting the putative native state folds from myriad possible conformations? In order to address these questions, we represent the local structure of each Cα atom of a protein by just two angles, θ and μ, and we analyze a set of more than 4,000 protein structures from the PDB. We use a hierarchical clustering scheme to divide the 20 amino acids into six distinct groups based on their similarity to each other in fitting local structural space. We present the results of a detailed analysis of patterns of amino acid specificity in adopting local structural conformations and show that the sequence-structure correlation is not very strong compared with a random assignment of sequence to structure. Yet, our analysis may be useful to determine an effective scoring rubric for quantifying the match of an amino acid to its putative local structure
Network allometry
No full textWe derive a new allometric scaling law for loopless networks, which we confirm with studies on rivers, exact network results and computer simulations. We provide evidence suggesting that ensemble averaging of the allometric property (where individual realizations are different networks) leads to results in excellent accord with the known limit scaling of efficient and compact networks with remarkably little scatter. Our results complement recent work suggesting that network-related allometric scaling in living organisms is regulated by metabolic supply-demand balance, because we show that scaling features are robust to geometrical fluctuations of network properties
Absence of many-body effects in interactions between charged colloidal particles
No full textThe effects of confining walls and many-body forces on charge-stabilized colloidal suspension are calculated using ab initio density functional theory. A Derjaguin-Landau-Verweg-Overbeek pair-potential interaction describes the results quantitatively, with small adjustments to the parameters. We find no evidence for three-body effects or any attraction between colloidal particles with like charges
Geometry and symmetry presculpt the free-energy landscape of proteins
Full text linkWe present a simple physical model that demonstrates that the native-state folds of proteins can emerge on the basis of considerations of geometry and symmetry. We show that the inherent anisotropy of a chain molecule, the geometrical and energetic constraints placed by the hydrogen bonds and sterics, and hydrophobicity are sufficient to yield a free-energy landscape with broad minima even for a homopolymer. These minima correspond to marginally compact structures comprising the menu of folds that proteins choose from to house their native states in. Our results provide a general framework for understanding the common characteristics of globular proteins
Stationary self-organized fractal structures in an open, dissipative electrical system
No full textWe study the stationary state of a Poisson problem for a system of N perfectly conducting metal balls driven by electric forces to move within a medium of very low electrical conductivity onto which charges are sprayed from outside. When grounded at a confining boundary, the system of metal balls is experimentally known to self-organize into stable fractal aggregates. We simulate the dynamical conditions leading to the formation of such aggregated patterns and analyse the fractal properties. From our results and those obtained for steady-state systems that obey minimum total energy dissipation (and potential energy of the system as a whole), we suggest a possible dynamical rule for the emergence of scale-free structures in nature
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