4,894 research outputs found
Physics of thick polymers
We present the results of analytic calculations and numerical simulations of
the behaviour of a new class of chain molecules which we call thick polymers.
The concept of the thickness of such a polymer, viewed as a tube, is
encapsulated by a special three body interaction and impacts on the behaviour
both locally and non-locally. When thick polymers undergo compaction due to an
attractive self-interaction, we find a new type of phase transition between a
compact phase and a swollen phase at zero temperature on increasing the
thickness. In the vicinity of this transition, short tubes form space filling
helices and sheets as observed in protein native state structures. Upon
increasing the chain length, or the number of chains, we numerically find a
crossover from secondary structure motifs to a quite distinct class of
structures akin to the semi-crystalline phase of polymers or amyloid fibers in
polypeptides.Comment: 41 pages, 20 figures. Accepted for publication in J. Pol. Sci.
Mechanical response of random heteropolymers
We present an analytical theory for heteropolymer deformation, as exemplified
experimentally by stretching of single protein molecules. Using a mean-field
replica theory, we determine phase diagrams for stress-induced unfolding of
typical random sequences. This transition is sharp in the limit of infinitely
long chain molecules. But for chain lengths relevant to biological
macromolecules, partially unfolded conformations prevail over an intermediate
range of stress. These necklace-like structures, comprised of alternating
compact and extended subunits, are stabilized by quenched variations in the
composition of finite chain segments. The most stable arrangements of these
subunits are largely determined by preferential extension of segments rich in
solvophilic monomers. This predicted significance of necklace structures
explains recent observations in protein stretching experiments. We examine the
statistical features of select sequences that give rise to mechanical strength
and may thus have guided the evolution of proteins that carry out mechanical
functions in living cells.Comment: 10 pages, 6 figure
Deciphering the folding kinetics of transmembrane helical proteins
Nearly a quarter of genomic sequences and almost half of all receptors that
are likely to be targets for drug design are integral membrane proteins.
Understanding the detailed mechanisms of the folding of membrane proteins is a
largely unsolved, key problem in structural biology. Here, we introduce a
general model and use computer simulations to study the equilibrium properties
and the folding kinetics of a -based two helix bundle fragment
(comprised of 66 amino-acids) of Bacteriorhodopsin. Various intermediates are
identified and their free energy are calculated toghether with the free energy
barrier between them. In 40% of folding trajectories, the folding rate is
considerably increased by the presence of non-obligatory intermediates acting
as traps. In all cases, a substantial portion of the helices is rapidly formed.
This initial stage is followed by a long period of consolidation of the helices
accompanied by their correct packing within the membrane. Our results provide
the framework for understanding the variety of folding pathways of helical
transmembrane proteins
Theoretical Perspectives on Protein Folding
Understanding how monomeric proteins fold under in vitro conditions is
crucial to describing their functions in the cellular context. Significant
advances both in theory and experiments have resulted in a conceptual framework
for describing the folding mechanisms of globular proteins. The experimental
data and theoretical methods have revealed the multifaceted character of
proteins. Proteins exhibit universal features that can be determined using only
the number of amino acid residues (N) and polymer concepts. The sizes of
proteins in the denatured and folded states, cooperativity of the folding
transition, dispersions in the melting temperatures at the residue level, and
time scales of folding are to a large extent determined by N. The consequences
of finite N especially on how individual residues order upon folding depends on
the topology of the folded states. Such intricate details can be predicted
using the Molecular Transfer Model that combines simulations with measured
transfer free energies of protein building blocks from water to the desired
concentration of the denaturant. By watching one molecule fold at a time, using
single molecule methods, the validity of the theoretically anticipated
heterogeneity in the folding routes, and the N-dependent time scales for the
three stages in the approach to the native state have been established. Despite
the successes of theory, of which only a few examples are documented here, we
conclude that much remains to be done to solve the "protein folding problem" in
the broadest sense.Comment: 48 pages, 9 figure
Polycation-Ï€ Interactions Are a Driving Force for Molecular Recognition by an Intrinsically Disordered Oncoprotein Family
Molecular recognition by intrinsically disordered proteins (IDPs) commonly involves specific localized contacts and target-induced disorder to order transitions. However, some IDPs remain disordered in the bound state, a phenomenon coined "fuzziness", often characterized by IDP polyvalency, sequence-insensitivity and a dynamic ensemble of disordered bound-state conformations. Besides the above general features, specific biophysical models for fuzzy interactions are mostly lacking. The transcriptional activation domain of the Ewing's Sarcoma oncoprotein family (EAD) is an IDP that exhibits many features of fuzziness, with multiple EAD aromatic side chains driving molecular recognition. Considering the prevalent role of cation-π interactions at various protein-protein interfaces, we hypothesized that EAD-target binding involves polycation- π contacts between a disordered EAD and basic residues on the target. Herein we evaluated the polycation-π hypothesis via functional and theoretical interrogation of EAD variants. The experimental effects of a range of EAD sequence variations, including aromatic number, aromatic density and charge perturbations, all support the cation-π model. Moreover, the activity trends observed are well captured by a coarse-grained EAD chain model and a corresponding analytical model based on interaction between EAD aromatics and surface cations of a generic globular target. EAD-target binding, in the context of pathological Ewing's Sarcoma oncoproteins, is thus seen to be driven by a balance between EAD conformational entropy and favorable EAD-target cation-π contacts. Such a highly versatile mode of molecular recognition offers a general conceptual framework for promiscuous target recognition by polyvalent IDPs. © 2013 Song et al
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
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