5,042 research outputs found
Two-State Folding, Folding through Intermediates, and Metastability in a Minimalistic Hydrophobic-Polar Model for Proteins
Within the frame of an effective, coarse-grained hydrophobic-polar protein
model, we employ multicanonical Monte Carlo simulations to investigate
free-energy landscapes and folding channels of exemplified heteropolymer
sequences, which are permutations of each other. Despite the simplicity of the
model, the knowledge of the free-energy landscape in dependence of a suitable
system order parameter enables us to reveal complex folding characteristics
known from real bioproteins and synthetic peptides, such as two-state folding,
folding through weakly stable intermediates, and glassy metastability.Comment: 10 pages, 1 figur
Geometry and symmetry presculpt the free-energy landscape of proteins
We present a simple physical model which 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.Comment: 23 pages, 5 figure
Frustration in Biomolecules
Biomolecules are the prime information processing elements of living matter.
Most of these inanimate systems are polymers that compute their structures and
dynamics using as input seemingly random character strings of their sequence,
following which they coalesce and perform integrated cellular functions. In
large computational systems with a finite interaction-codes, the appearance of
conflicting goals is inevitable. Simple conflicting forces can lead to quite
complex structures and behaviors, leading to the concept of "frustration" in
condensed matter. We present here some basic ideas about frustration in
biomolecules and how the frustration concept leads to a better appreciation of
many aspects of the architecture of biomolecules, and how structure connects to
function. These ideas are simultaneously both seductively simple and perilously
subtle to grasp completely. The energy landscape theory of protein folding
provides a framework for quantifying frustration in large systems and has been
implemented at many levels of description. We first review the notion of
frustration from the areas of abstract logic and its uses in simple condensed
matter systems. We discuss then how the frustration concept applies
specifically to heteropolymers, testing folding landscape theory in computer
simulations of protein models and in experimentally accessible systems.
Studying the aspects of frustration averaged over many proteins provides ways
to infer energy functions useful for reliable structure prediction. We discuss
how frustration affects folding, how a large part of the biological functions
of proteins are related to subtle local frustration effects and how frustration
influences the appearance of metastable states, the nature of binding
processes, catalysis and allosteric transitions. We hope to illustrate how
Frustration is a fundamental concept in relating function to structural
biology.Comment: 97 pages, 30 figure
Protein multi-scale organization through graph partitioning and robustness analysis: Application to the myosin-myosin light chain interaction
Despite the recognized importance of the multi-scale spatio-temporal
organization of proteins, most computational tools can only access a limited
spectrum of time and spatial scales, thereby ignoring the effects on protein
behavior of the intricate coupling between the different scales. Starting from
a physico-chemical atomistic network of interactions that encodes the structure
of the protein, we introduce a methodology based on multi-scale graph
partitioning that can uncover partitions and levels of organization of proteins
that span the whole range of scales, revealing biological features occurring at
different levels of organization and tracking their effect across scales.
Additionally, we introduce a measure of robustness to quantify the relevance of
the partitions through the generation of biochemically-motivated surrogate
random graph models. We apply the method to four distinct conformations of
myosin tail interacting protein, a protein from the molecular motor of the
malaria parasite, and study properties that have been experimentally addressed
such as the closing mechanism, the presence of conserved clusters, and the
identification through computational mutational analysis of key residues for
binding.Comment: 13 pages, 7 Postscript figure
Allo-network drugs: Extension of the allosteric drug concept to protein-protein interaction and signaling networks
Allosteric drugs are usually more specific and have fewer side effects than orthosteric drugs targeting the same
protein. Here, we overview the current knowledge on allosteric signal transmission from the network point of view, and show that most intra-protein conformational changes may be dynamically transmitted across protein-protein interaction and signaling networks of the cell. Allo-network drugs influence the pharmacological target protein indirectly using specific inter-protein network pathways. We show that allo-network drugs may have a higher efficiency to change the networks of human cells than those of other organisms, and can be designed to have specific effects on cells in a diseased state. Finally, we summarize possible methods to identify allo-network drug targets and sites, which may develop to a promising new area of systems-based drug design
Buried and accessible surface area control intrinsic protein flexibility
Proteins experience a wide variety of conformational dynamics that can be
crucial for facilitating their diverse functions. How is the intrinsic
flexibility required for these motions encoded in their three-dimensional
structures? Here, the overall flexibility of a protein is demonstrated to be
tightly coupled to the total amount of surface area buried within its fold. A
simple proxy for this, the relative solvent accessible surface area (Arel),
therefore shows excellent agreement with independent measures of global protein
flexibility derived from various experimental and computational methods.
Application of Arel on a large scale demonstrates its utility by revealing
unique sequence and structural properties associated with intrinsic
flexibility. In particular, flexibility as measured by Arel shows little
correspondence with intrinsic disorder, but instead tends to be associated with
multiple domains and increased {\alpha}- helical structure. Furthermore, the
apparent flexibility of monomeric proteins is found to be useful for
identifying quaternary structure errors in published crystal structures. There
is also a strong tendency for the crystal structures of more flexible proteins
to be solved to lower resolutions. Finally, local solvent accessibility is
shown to be a primary determinant of local residue flexibility. Overall this
work provides both fundamental mechanistic insight into the origin of protein
flexibility and a simple, practical method for predicting flexibility from
protein structures.Comment: 36 pages, 11 figures, author's manuscript, accepted for publication
in Journal of Molecular Biolog
Role of Proteome Physical Chemistry in Cell Behavior.
We review how major cell behaviors, such as bacterial growth laws, are derived from the physical chemistry of the cell's proteins. On one hand, cell actions depend on the individual biological functionalities of their many genes and proteins. On the other hand, the common physics among proteins can be as important as the unique biology that distinguishes them. For example, bacterial growth rates depend strongly on temperature. This dependence can be explained by the folding stabilities across a cell's proteome. Such modeling explains how thermophilic and mesophilic organisms differ, and how oxidative damage of highly charged proteins can lead to unfolding and aggregation in aging cells. Cells have characteristic time scales. For example, E. coli can duplicate as fast as 2-3 times per hour. These time scales can be explained by protein dynamics (the rates of synthesis and degradation, folding, and diffusional transport). It rationalizes how bacterial growth is slowed down by added salt. In the same way that the behaviors of inanimate materials can be expressed in terms of the statistical distributions of atoms and molecules, some cell behaviors can be expressed in terms of distributions of protein properties, giving insights into the microscopic basis of growth laws in simple cells
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