15,682 research outputs found
Topological thermal instability and length of proteins
We present an analysis of the effects of global topology on the structural
stability of folded proteins in thermal equilibrium with a heat bath. For a
large class of single domain proteins, we computed the harmonic spectrum within
the Gaussian Network Model (GNM) and determined the spectral dimension, a
parameter describing the low frequency behaviour of the density of modes. We
find a surprisingly strong correlation between the spectral dimension and the
number of amino acids of the protein. Considering that larger spectral
dimension value relate to more topologically compact folded state, our results
indicate that for a given temperature and length of the protein, the folded
structure corresponds to the less compact folding compatible with thermodynamic
stability.Comment: 15 pages, 6 eps figures, 2 table
A topological approach for protein classification
Protein function and dynamics are closely related to its sequence and
structure. However prediction of protein function and dynamics from its
sequence and structure is still a fundamental challenge in molecular biology.
Protein classification, which is typically done through measuring the
similarity be- tween proteins based on protein sequence or physical
information, serves as a crucial step toward the understanding of protein
function and dynamics. Persistent homology is a new branch of algebraic
topology that has found its success in the topological data analysis in a
variety of disciplines, including molecular biology. The present work explores
the potential of using persistent homology as an indepen- dent tool for protein
classification. To this end, we propose a molecular topological fingerprint
based support vector machine (MTF-SVM) classifier. Specifically, we construct
machine learning feature vectors solely from protein topological fingerprints,
which are topological invariants generated during the filtration process. To
validate the present MTF-SVM approach, we consider four types of problems.
First, we study protein-drug binding by using the M2 channel protein of
influenza A virus. We achieve 96% accuracy in discriminating drug bound and
unbound M2 channels. Additionally, we examine the use of MTF-SVM for the
classification of hemoglobin molecules in their relaxed and taut forms and
obtain about 80% accuracy. The identification of all alpha, all beta, and
alpha-beta protein domains is carried out in our next study using 900 proteins.
We have found a 85% success in this identifica- tion. Finally, we apply the
present technique to 55 classification tasks of protein superfamilies over 1357
samples. An average accuracy of 82% is attained. The present study establishes
computational topology as an independent and effective alternative for protein
classification
The Energy Landscape, Folding Pathways and the Kinetics of a Knotted Protein
The folding pathway and rate coefficients of the folding of a knotted protein
are calculated for a potential energy function with minimal energetic
frustration. A kinetic transition network is constructed using the discrete
path sampling approach, and the resulting potential energy surface is
visualized by constructing disconnectivity graphs. Owing to topological
constraints, the low-lying portion of the landscape consists of three distinct
regions, corresponding to the native knotted state and to configurations where
either the N- or C-terminus is not yet folded into the knot. The fastest
folding pathways from denatured states exhibit early formation of the
N-terminus portion of the knot and a rate-determining step where the C-terminus
is incorporated. The low-lying minima with the N-terminus knotted and the
C-terminus free therefore constitute an off-pathway intermediate for this
model. The insertion of both the N- and C-termini into the knot occur late in
the folding process, creating large energy barriers that are the rate limiting
steps in the folding process. When compared to other protein folding proteins
of a similar length, this system folds over six orders of magnitude more
slowly.Comment: 19 page
Native geometry and the dynamics of protein folding
In this paper we investigate the role of native geometry on the kinetics of
protein folding based on simple lattice models and Monte Carlo simulations.
Results obtained within the scope of the Miyazawa-Jernigan indicate the
existence of two dynamical folding regimes depending on the protein chain
length. For chains larger than 80 amino acids the folding performance is
sensitive to the native state's conformation. Smaller chains, with less than 80
amino acids, fold via two-state kinetics and exhibit a significant correlation
between the contact order parameter and the logarithmic folding times. In
particular, chains with N=48 amino acids were found to belong to two broad
classes of folding, characterized by different cooperativity, depending on the
contact order parameter. Preliminary results based on the G\={o} model show
that the effect of long range contact interaction strength in the folding
kinetics is largely dependent on the native state's geometry.Comment: Proceedings of the BIFI 2004 - I International Conference, Zaragoza
(Spain) Biology after the genome: a physical view. To appear in Biophysical
Chemistr
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