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The conformational dynamics of a single protein molecule in a shear flow is investigated using Brownian dynamics simulations. A structure-based coarse grained model of a protein is used. We consider two proteins, ubiquitin and integrin, and…

生物大分子 · 定量生物学 2009-11-13 P. Szymczak , Marek Cieplak

Molecular dynamics simulations of folding in an off-lattice protein model reveal a nucleation scenario, in which a few well-defined contacts are formed with high probability in the transition state ensemble of conformations. Their…

We formulate and characterize a model to describe the dynamics of semiflexible polymers in the presence of activity due to motor proteins attached irreversibly to a substrate, and a transverse pulling force acting on one end of the…

生物物理 · 物理学 2016-02-12 Abhishek Chaudhuri , Debasish Chaudhuri

In spite of decades of research, much remains to be discovered about folding: the detailed structure of the initial (unfolded) state, vestigial folding instructions remaining only in the unfolded state, the interaction of the molecule with…

生物物理 · 物理学 2018-11-26 Walter A. Simmons

Natural protein sequences contain a record of their history. A common constraint in a given protein family is the ability to fold to specific structures, and it has been shown possible to infer the main native ensemble by analyzing…

生物大分子 · 定量生物学 2017-03-16 Rocío Espada , R. Gonzalo Parra , Thierry Mora , Aleksandra M. Walczak , Diego U. Ferreiro

This work examines the conformational ensemble involved in $\beta$-hairpin folding by means of advanced molecular dynamics simulations and dimensionality reduction. A fully atomistic description of the protein and the surrounding solvent…

化学物理 · 物理学 2023-06-16 Albert Ardevol , Gareth A. Tribello , Michele Ceriotti , Michele Parrinello

In single-molecule force spectroscopy experiments, the dependence of the mean unfolding force on the loading rate is used for obtaining information about the energetic and dynamic properties of the system under study. However, it is crucial…

生物物理 · 物理学 2020-03-10 Rafayel Petrosyan

The response of proteins to chemical reactions or impulsive excitation that occurs within the molecule has fascinated chemists for decades. In recent years ultrafast X-ray studies have provided ever more detailed information about the…

生物物理 · 物理学 2018-05-11 David M. Leitner , Takahisa Yamato

A central goal of protein-folding theory is to predict the stochastic dynamics of transition paths --- the rare trajectories that transit between the folded and unfolded ensembles --- using only thermodynamic information, such as a…

生物大分子 · 定量生物学 2018-08-09 William M. Jacobs , Eugene I. Shakhnovich

Protein folding is the intricate process by which a linear sequence of amino acids self-assembles into a unique three-dimensional structure. Protein folding kinetics is the study of pathways and time-dependent mechanisms a protein undergoes…

机器学习 · 计算机科学 2023-09-19 Vijay Arvind. R , Haribharathi Sivakumar , Brindha. R

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

We present a statistical mechanics approach to the protein folding problem. We first review some of the basic properties of proteins, and introduce some physical models to describe their thermodynamics. These models rely on a random…

无序系统与神经网络 · 物理学 2008-02-03 T. Garel , H. Orland , E. Pitard

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

Understanding the principles of protein folding is a cornerstone of computational biology, with implications for drug design, bioengineering, and the understanding of fundamental biological processes. Lattice protein folding models offer a…

无序系统与神经网络 · 物理学 2025-08-08 Shoummo Ahsan Khandoker , Estelle M. Inack , Mohamed Hibat-Allah

We report studies of the equilibrium and the dynamics of a general set of lattice models which capture the essence of the force-induced or mechanical DNA unzipping transition. Besides yielding the whole equilibrium phase diagram in the…

软凝聚态物质 · 物理学 2009-11-07 D. Marenduzzo , S. M. Bhattacharjee , A. Maritan , E. Orlandini , F. Seno

We review some of our recent results obtained within the scope of simple lattice models and Monte Carlo simulations that illustrate the role of native geometry in the folding kinetics of two state folders.

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

DNA hairpin molecules with periodic base sequences can be expected to exhibit a regular coarse-grained free energy landscape (FEL) as function of the number of open base pairs and applied mechanical force. Using a commonly employed model,…

生物物理 · 物理学 2013-12-17 Sandra Nostheide , Viktor Holubec , Petr Chvosta , Philipp Maass

A statistical mechanical description of flexible and semi-flexible polymer chains in a poor solvent is developed in the constant force and constant distance ensembles. We predict the existence of many intermediate states at low temperatures…

软凝聚态物质 · 物理学 2007-05-23 Sanjay Kumar , Iwan Jensen , Jesper L. Jacobsen , Anthony J. Guttmann

The thermodynamics of proteins indicate that folding/unfolding takes place either through stable intermediates or through a two-state process without intermediates. The rather short folding times of the two-state process indicate that…

凝聚态物理 · 物理学 2016-08-31 Audun Bakk , Johan S. Hoye , Alex Hansen , Kim Sneppen , Mogens Hogh Jensen

Extensive Monte Carlo folding simulations for four proteins of various structural classes are carried out, using a single atomistic potential. In all cases, collapse occurs at a very early stage, and proteins fold into their native-like…

统计力学 · 物理学 2009-11-10 Seung-Yeon Kim , Julian Lee , Jooyoung Lee