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The probability distribution of sequences with maximum entropy that satisfies a given amino acid composition at each site and a given pairwise amino acid frequency at each site pair is a Boltzmann distribution with $\exp(-\psi_N)$, where…

种群与进化 · 定量生物学 2017-04-04 Sanzo Miyazawa

Predicting the change in binding free energy ($\Delta \Delta G$) is crucial for understanding and modulating protein-protein interactions, which are critical in drug design. Due to the scarcity of experimental $\Delta \Delta G$ data,…

计算工程、金融与科学 · 计算机科学 2024-10-15 Xiaoran Jiao , Weian Mao , Wengong Jin , Peiyuan Yang , Hao Chen , Chunhua Shen

The common understanding of protein evolution has been that neutral or slightly deleterious mutations are fixed by random drift, and evolutionary rate is determined primarily by the proportion of neutral mutations. However, recent studies…

种群与进化 · 定量生物学 2015-12-31 Sanzo Miyazawa

We investigate the sequence-dependent properties of proteins that determine the dual requirements of stability of the native state and its kinetic accessibility using simple cubic lattice models. Three interaction schemes are used to…

软凝聚态物质 · 物理学 2009-10-31 D. K. Klimov , D. Thirumalai

We derive an analytic expression for site-specific stationary distributions of amino acids from the Structurally Constrained Neutral (SCN) model of protein evolution with conservation of folding stability. The stationary distributions that…

生物大分子 · 定量生物学 2007-05-23 Markus Porto , H. Eduardo Roman , Michele Vendruscolo , Ugo Bastolla

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

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

The number of protein structures is far less than the number of sequences. By imposing simple generic features of proteins (low energy and compaction) on all possible sequences we show that the structure space is sparse compared to the…

软凝聚态物质 · 物理学 2009-10-31 D. Thirumalai , D. K. Klimov

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…

生物大分子 · 定量生物学 2007-05-23 R. Burioni , D. Cassi , F. Cecconi , A. Vulpiani

We present an analysis of the role 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 compute the harmonic spectrum within the Gaussian…

凝聚态物理 · 物理学 2007-05-23 R. Burioni , D. Cassi , F. Cecconi , A. Vulpiani

The process of protein folding from an unfolded state to a biologically active, folded conformation is governed by many parameters e.g the sequence of amino acids, intermolecular interactions, the solvent, temperature and chaperon…

软凝聚态物质 · 物理学 2010-10-19 Pragya Shukla

We propose a general method for predicting potentially good folders from a given number of amino acid sequences. Our approach is based on the calculation of the rate of convergence of each amino acid chain towards the native structure using…

生物物理 · 物理学 2013-02-07 Dmitry K. Gridnev , Pedro Ojeda-May , Martin E. Garcia

We develop a theoretical approach to the protein folding problem based on out-of-equilibrium stochastic dynamics. Within this framework, the computational difficulties related to the existence of large time scale gaps in the protein folding…

定量方法 · 定量生物学 2009-11-13 M. Sega , P. Faccioli , F. Pederiva , G. Garberoglio , H. Orland

We study folding dynamics of protein-like sequences on square lattice using physical move set that exhausts all possible conformational changes. By analytically solving the master equation, we follow the time-dependent probabilities of…

生物大分子 · 定量生物学 2016-08-16 Sëma Kachalo , Hsiao-Mei Lu , Jie Liang

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

As an example of topic where biology and physics meet, we present the issue of protein folding and stability, and the development of thermodynamics-based bioinformatics tools that predict the stability and thermal resistance of proteins and…

生物大分子 · 定量生物学 2016-03-15 Fabrizio Pucci , Marianne Rooman

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

We present a sequence-based probabilistic formalism that directly addresses co-operative effects in networks of interacting positions in proteins, providing significantly improved contact prediction, as well as accurate quantitative…

定量方法 · 定量生物学 2012-07-12 Alan Lapedes , Bertrand Giraud , Christopher Jarzynski

We carry out a theoretical study of the vibrational and relaxation properties of naturally-occurring proteins with the purpose of characterizing both the folding and equilibrium thermodynamics. By means of a suitable model we provide a full…

统计力学 · 物理学 2007-05-23 Cristian Micheletti , Gianluca Lattanzi , Amos Maritan

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
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