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相关论文: Lymphotactin: how a protein can adopt two folds

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Proteins must fold quickly to acquire their biologically functional three-dimensional native structures. Hence, these are mainly stabilized by local contacts, while intricate topologies such as knots are rare. Here, we reveal the existence…

生物大分子 · 定量生物学 2019-06-20 Marco Baiesi , Enzo Orlandini , Flavio Seno , Antonio Trovato

Native protein folds often have a high degree of symmetry. We study the relationship between the symmetries of native proteins, and their designabilities -- how many different sequences encode a given native structure. Using a…

统计力学 · 物理学 2009-10-31 Tairan Wang , Jonathan Miller , Ned S. Wingreen , Chao Tang , Ken A. Dill

Globular proteins are expected to assume folds with fixed secondary structures, alpha-helices and beta-sheets. Fold-switching proteins challenge this expectation by remodeling their secondary and/or tertiary structures in response to…

生物大分子 · 定量生物学 2025-07-16 Devlina Chakravarty , Lauren L. Porter

Models of protein energetics which neglect interactions between amino acids that are not adjacent in the native state, such as the Go model, encode or underlie many influential ideas on protein folding. Implicit in this simplification is a…

生物大分子 · 定量生物学 2009-10-08 Brian C. Gin , Juan P. Garrahan , Phillip L. Geissler

These lectures will address two questions. Is there a simple variational principle underlying the existence of secondary motifs in the native state of proteins? Is there a general approach which can qualitatively capture the salient…

统计力学 · 物理学 2007-05-23 Jay Banavar , Amos Maritan , Cristian Micheletti , Flavio Seno

Mechanical unfolding of several domains of calmodulin and titin is studied using a Go-like model with a realistic contact map and Lennard-Jones contact interactions. It is shown that this simple model captures the experimentally observed…

生物大分子 · 定量生物学 2009-11-10 Marek Cieplak

The folding dynamics of small single-domain proteins is a current focus of simulations and experiments. Many of these proteins are 'two-state folders', i.e. proteins that fold rather directly from the denatured state to the native state,…

生物大分子 · 定量生物学 2020-01-08 Thomas R. Weikl

Single-molecule atomic force spectroscopy probes elastic properties of titin, ubiquitin and other relevant proteins. We explain bioprotein folding dynamics under both length- and force-clamp by modeling polyprotein modules as particles in a…

统计力学 · 物理学 2016-11-17 L. L. Bonilla , A. Carpio , A. Prados

Protein folding cooperativity is defined by the nature of the finite-size thermodynamic transition exhibited upon folding: two-state transitions show a free energy barrier between the folded and unfolded ensembles, while downhill folding is…

生物大分子 · 定量生物学 2017-08-23 Tristan Bereau , Michael Bachmann , Markus Deserno

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…

软凝聚态物质 · 物理学 2010-07-20 D. Thirumalai , Edward P. O'Brien , Greg Morrison , Changbong Hyeon

Experiments have revealed that membrane proteins can form two-dimensional clusters with regular translational and orientational protein arrangements, which may allow cells to modulate protein function. However, the physical mechanisms…

生物大分子 · 定量生物学 2016-11-04 Osman Kahraman , Peter D. Koch , William S. Klug , Christoph A. Haselwandter

With the help of lattice Monte Carlo modelling of heteropolymers, we show that the necessary condition for a protein to fold on short call is to proceed through partially folded intermediates. These elementary structures are formed at an…

凝聚态物理 · 物理学 2007-05-23 R. A. Broglia , G. Tiana

Proteins with nontrivial topology, containing knots and slipknots, have the ability to fold to their native states without any additional external forces invoked. A mechanism is suggested for folding of these proteins, such as YibK and…

生物大分子 · 定量生物学 2010-01-06 Joanna I. Sułkowska , Piotr Sułkowski , José N. Onuchic

A protein's function depends critically on its conformational ensemble, a collection of energy weighted structures whose balance depends on temperature and environment. Though recent deep learning (DL) methods have substantially advanced…

生物大分子 · 定量生物学 2026-01-09 Myeongsang Lee , Lauren L. Porter

Protein folding, peptide aggregation and crystallization, as well as adsorption of molecules on soft or solid substrates have an essential feature in common: In all these processes, structure formation is guided by a collective, cooperative…

统计力学 · 物理学 2009-02-12 Michael Bachmann , Wolfhard Janke

Protein structures are a very special class among all possible structures. It was suggested that a ``designability principle'' plays a crucial role in nature's selection of protein sequences and structures. Here we provide a theoretical…

统计力学 · 物理学 2009-10-30 Hao Li , Chao Tang , Ned S. Wingreen

One of the most puzzling and unsolved challenges in molecular biology is understanding how proteins fold. Despite having advanced predictive tools that can accurately estimate the native structures of proteins, we still lack a comprehensive…

生物大分子 · 定量生物学 2026-01-13 Jorge Vila

Model off-lattice sequences in two dimensions are constructed so that their native states are close to an on-lattice target. The Hamiltonian involves the Lennard-Jones and harmonic interactions. The native states of these sequences are…

软凝聚态物质 · 物理学 2009-10-31 Mai Suan Li , Marek Cieplak

Simple two-state folding kinetics of many small single-domain proteins are characterized by chevron plots with linear folding and unfolding arms consistent with a two-state description of equilibrium thermodynamics. This phenomenon is…

软凝聚态物质 · 物理学 2007-05-23 Huseyin Kaya , Hue Sun Chan

In this work, we discovered a fundamental connection between selection for protein stability and emergence of preferred structures of proteins. Using standard exact 3-dimensional lattice model we evolve sequences starting from random ones…

基因组学 · 定量生物学 2007-05-23 Konstantin B. Zeldovich , Igor N. Berezovsky , Eugene I. Sha
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