189 research outputs found
An Analytical Approach to the Protein Designability Problem
We present an analytical method for determining the designability of protein
structures. We apply our method to the case of two-dimensional lattice
structures, and give a systematic solution for the spectrum of any structure.
Using this spectrum, the designability of a structure can be estimated. We
outline a heirarchy of structures, from most to least designable, and show that
this heirarchy depends on the potential that is used.Comment: 16 pages 4 figure
Regulatory control and the costs and benefits of biochemical noise
Experiments in recent years have vividly demonstrated that gene expression
can be highly stochastic. How protein concentration fluctuations affect the
growth rate of a population of cells, is, however, a wide open question. We
present a mathematical model that makes it possible to quantify the effect of
protein concentration fluctuations on the growth rate of a population of
genetically identical cells. The model predicts that the population's growth
rate depends on how the growth rate of a single cell varies with protein
concentration, the variance of the protein concentration fluctuations, and the
correlation time of these fluctuations. The model also predicts that when the
average concentration of a protein is close to the value that maximizes the
growth rate, fluctuations in its concentration always reduce the growth rate.
However, when the average protein concentration deviates sufficiently from the
optimal level, fluctuations can enhance the growth rate of the population, even
when the growth rate of a cell depends linearly on the protein concentration.
The model also shows that the ensemble or population average of a quantity,
such as the average protein expression level or its variance, is in general not
equal to its time average as obtained from tracing a single cell and its
descendants. We apply our model to perform a cost-benefit analysis of gene
regulatory control. Our analysis predicts that the optimal expression level of
a gene regulatory protein is determined by the trade-off between the cost of
synthesizing the regulatory protein and the benefit of minimizing the
fluctuations in the expression of its target gene. We discuss possible
experiments that could test our predictions.Comment: Revised manuscript;35 pages, 4 figures, REVTeX4; to appear in PLoS
Computational Biolog
Simulation, Experiment, and Evolution: Understanding Nucleation in Protein S6 Folding
In this study, we explore nucleation and the transition state ensemble of the
ribosomal protein S6 using a Monte Carlo Go model in conjunction with
restraints from experiment. The results are analyzed in the context of
extensive experimental and evolutionary data. The roles of individual residues
in the folding nucleus are identified and the order of events in the S6 folding
mechanism is explored in detail. Interpretation of our results agrees with, and
extends the utility of, experiments that shift f-values by modulating
denaturant concentration and presents strong evidence for the realism of the
mechanistic details in our Monte Carlo Go model and the structural
interpretation of experimental f-values. We also observe plasticity in the
contacts of the hydrophobic core that support the specific nucleus. For S6,
which binds to RNA and protein after folding, this plasticity may result from
the conformational flexibility required to achieve biological function. These
results present a theoretical and conceptual picture that is relevant in
understanding the mechanism of nucleation in protein folding.Comment: PNAS in pres
Statistical mechanics of RNA folding: importance of alphabet size
We construct a minimalist model of RNA secondary-structure formation and use
it to study the mapping from sequence to structure. There are strong,
qualitative differences between two-letter and four or six-letter alphabets.
With only two kinds of bases, there are many alternate folding configurations,
yielding thermodynamically stable ground-states only for a small set of
structures of high designability, i.e., total number of associated sequences.
In contrast, sequences made from four bases, as found in nature, or six bases
have far fewer competing folding configurations, resulting in a much greater
average stability of the ground state.Comment: 7 figures; uses revtex
Anisotropic coarse-grained statistical potentials improve the ability to identify native-like protein structures
We present a new method to extract distance and orientation dependent
potentials between amino acid side chains using a database of protein
structures and the standard Boltzmann device. The importance of orientation
dependent interactions is first established by computing orientational order
parameters for proteins with alpha-helical and beta-sheet architecture.
Extraction of the anisotropic interactions requires defining local reference
frames for each amino acid that uniquely determine the coordinates of the
neighboring residues. Using the local reference frames and histograms of the
radial and angular correlation functions for a standard set of non-homologue
protein structures, we construct the anisotropic pair potentials. The
performance of the orientation dependent potentials was studied using a large
database of decoy proteins. The results demonstrate that the new distance and
orientation dependent residue-residue potentials present a significantly
improved ability to recognize native folds from a set of native and decoy
protein structures.Comment: Submitted to "The Journal of Chemical Physics
The Value of Information for Populations in Varying Environments
The notion of information pervades informal descriptions of biological
systems, but formal treatments face the problem of defining a quantitative
measure of information rooted in a concept of fitness, which is itself an
elusive notion. Here, we present a model of population dynamics where this
problem is amenable to a mathematical analysis. In the limit where any
information about future environmental variations is common to the members of
the population, our model is equivalent to known models of financial
investment. In this case, the population can be interpreted as a portfolio of
financial assets and previous analyses have shown that a key quantity of
Shannon's communication theory, the mutual information, sets a fundamental
limit on the value of information. We show that this bound can be violated when
accounting for features that are irrelevant in finance but inherent to
biological systems, such as the stochasticity present at the individual level.
This leads us to generalize the measures of uncertainty and information usually
encountered in information theory
A Genome-Wide Analysis of Promoter-Mediated Phenotypic Noise in Escherichia coli
Gene expression is subject to random perturbations that lead to fluctuations in the rate of protein production. As a consequence, for any given protein, genetically identical organisms living in a constant environment will contain different amounts of that particular protein, resulting in different phenotypes. This phenomenon is known as “phenotypic noise.” In bacterial systems, previous studies have shown that, for specific genes, both transcriptional and translational processes affect phenotypic noise. Here, we focus on how the promoter regions of genes affect noise and ask whether levels of promoter-mediated noise are correlated with genes' functional attributes, using data for over 60% of all promoters in Escherichia coli. We find that essential genes and genes with a high degree of evolutionary conservation have promoters that confer low levels of noise. We also find that the level of noise cannot be attributed to the evolutionary time that different genes have spent in the genome of E. coli. In contrast to previous results in eukaryotes, we find no association between promoter-mediated noise and gene expression plasticity. These results are consistent with the hypothesis that, in bacteria, natural selection can act to reduce gene expression noise and that some of this noise is controlled through the sequence of the promoter region alon
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