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相关论文: Protein folding dynamics via quantification of kin…

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We study folding in 16-monomer heteropolymers on the square lattice. For a given sequence, thermodynamic properties and stability of the native state are unique. However, the kinetics of folding depends on the model of dynamics adopted for…

统计力学 · 物理学 2009-10-31 Trinh Xuan Hoang , Marek Cieplak

The understanding, and even the description of protein folding is impeded by the complexity of the process. Much of this complexity can be described and understood by taking a statistical approach to the energetics of protein conformation,…

chem-ph · 物理学 2008-02-03 J. D. Bryngelson , J. N. Onuchic , N. D. Socci , P. G. Wolynes

We study the geometric properties of the energy landscape of coarse-grained, off-lattice models of polymers by endowing the configuration space with a suitable metric, depending on the potential energy function, such that the dynamical…

统计力学 · 物理学 2007-05-23 Lorenzo N. Mazzoni , Lapo Casetti

Using a simple three-dimensional lattice copolymer model and Monte Carlo dynamics, we study the collapse and folding of protein-like heteropolymers. The polymers are 27 monomers long and consist of two monomer types. Although these chains…

凝聚态物理 · 物理学 2009-10-22 Nicholas D. Socci , Jose' Nelson Onuchic

In the framework of a lattice-model study of protein folding, we investigate the interplay between designability, thermodynamic stability, and kinetics. To be ``protein-like'', heteropolymers must be thermodynamically stable, stable against…

统计力学 · 物理学 2009-10-31 Régis Mélin , Hao Li , Ned S. Wingreen , Chao Tang

The folding kinetics of a number of sequences for off-lattice continuum model of proteins is studied using Langevin simulations at two values of the friction coefficient. We show that there is a remarkable correlation between folding times,…

统计力学 · 物理学 2008-02-03 T. Veitshans , D. K. Klimov , D. Thirumalai

Natural protein sequences somehow encode the structural forms that these molecules adopt. Recent developments in structure-prediction are agnostic to the mechanisms by which proteins fold and represent them as static objects. However, the…

生物大分子 · 定量生物学 2025-05-26 Ezequiel A. Galpern , Federico Caamaño , Diego U. Ferreiro

We use a three dimensional cubic lattice model of proteins to study their properties that determine folding to the native state. The protein chain is modeled as a sequence of $N$ beads. The interactions between beads are taken from a…

凝聚态物理 · 物理学 2007-05-23 D. K. Klimov , D. Thirumalai

A geometric analysis of the global properties of the energy landscape of a minimalistic model of a polypeptide is presented, which is based on the relation between dynamical trajectories and geodesics of a suitable manifold, whose metric is…

统计力学 · 物理学 2009-11-13 Lorenzo N. Mazzoni , Lapo Casetti

The folding of naturally occurring, single domain proteins is usually well-described as a simple, single exponential process lacking significant trapped states. Here we further explore the hypothesis that the smooth energy landscape this…

生物大分子 · 定量生物学 2007-05-23 P. F. N. Faisca , K. W. Plaxco

The energy landscapes of proteins have evolved to be different from most random heteropolymers. Many studies have concluded that evolutionary selection for rapid and reliable folding to a given structure that is stable at biological…

无序系统与神经网络 · 物理学 2009-11-10 Steven S. Plotkin , Peter G. Wolynes

Folding kinetics of a lattice model of protein is studied. It uses the Random Energy Model for the intrachain couplings and a temperature dependent free energy of solvation derived from a realistic hydration model of apolar solutes. The…

统计力学 · 物理学 2008-11-06 Olivier Collet

A theoretical framework is developed to study the dynamics of protein folding. The key insight is that the search for the native protein conformation is influenced by the rate r at which external parameters, such as temperature, chemical…

生物大分子 · 定量生物学 2009-11-13 Gregg Lois , Jerzy Blawzdziewicz , Corey S. O'Hern

Monte Carlo simulations of a simple lattice model of protein folding show two distinct regimes depending on the chain length. The first regime well describes the folding of small protein sequences and its kinetic counterpart appears to be…

软凝聚态物质 · 物理学 2007-05-23 P. F. N. Faisca , R. C. Ball

Physical mechanisms underlying the empirical correlation between relative contact order (CO) and folding rate among naturally-occurring small single-domain proteins are investigated by evaluating postulated interaction schemes for a set of…

统计力学 · 物理学 2007-05-23 Huseyin Kaya , Hue Sun Chan

The classical approach to protein folding inspired by statistical mechanics avoids the high dimensional structure of the conformation space by using effective coordinates. Here we introduce a network approach to capture the statistical…

生物大分子 · 定量生物学 2007-05-23 Erzsebet Ravasz , S. Gnanakaran , Zoltan Toroczkai

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…

生物大分子 · 定量生物学 2007-05-23 P. F. N. Faisca , M. M. Telo da Gama

The dynamics of two 12-monomer heteropolymers on the square lattice is studied exactly within the master equation approach. The time evolution of the occupancy of the native state is determined. At low temperatures, the median folding time…

统计力学 · 物理学 2009-09-25 Marek Cieplak , Malte Henkel , Jayanth R. Banavar

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…

生物大分子 · 定量生物学 2010-07-05 Michael C. Prentiss , David J. Wales , Peter G. Wolynes

We investigate the folding behavior of protein sequences by numerically studying all sequences with maximally compact lattice model through exhaustive enumeration. We get the prion-like behavior of protein folding. Individual proteins…

生物大分子 · 定量生物学 2014-11-18 Yong-Yun Ji , You-Quan Li , Jun-Wen Mao , Xiao-Wei Tang
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