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This paper deals with the relations among structural, topological, and chemical properties of the E.Coli proteome from the vantage point of the solubility/aggregation propensity of proteins. Each E.Coli protein is initially represented…

数据分析、统计与概率 · 物理学 2015-11-17 Lorenzo Livi , Alessandro Giuliani , Alireza Sadeghian

Aggregates of misfolded proteins are a hallmark of many age-related diseases. Recently, they have been linked to aging of Escherichia coli (E. coli) where protein aggregates accumulate at the old pole region of the aging bacterium. Because…

The protein folding problem has attracted an increasing attention from physicists. The problem has a flavor of statistical mechanics, but possesses the most common feature of most biological problems -- the profound effects of evolution. I…

统计力学 · 物理学 2009-10-31 Chao Tang

Folding and aggregation of proteins, the interaction between proteins and membranes, as well as the adsorption of organic soft matter to inorganic solid substrates belong to the most interesting challenges in understanding structure and…

软凝聚态物质 · 物理学 2007-12-06 Michael Bachmann , Wolfhard Janke

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

Proteins are inherently multiscale physical systems whose functional properties emerge from coordinated structural organization across multiple spatial resolutions, ranging from atomic interactions to global fold topology. However, existing…

机器学习 · 计算机科学 2026-05-13 Viet Thanh Duy Nguyen , John K. Johnstone , Truong-Son Hy

A reduced model, which can fold both helix and sheet structures, is proposed to study the problem of protein folding. The goal of this model is to find an unbiased effective potential that has included the effects of water and at the same…

软凝聚态物质 · 物理学 2007-05-23 Nan-yow Chen

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

A comparative classification scheme provides a good basis for several approaches to understand proteins, including prediction of relations between their structure and biological function. But it remains a challenge to combine a…

生物大分子 · 定量生物学 2015-05-20 Shuangwei Hu , Andrei Krokhotin , Antti J. Niemi , Xubiao Peng

Protein representation and potential function are essential ingredients for studying proteins folding and protein prediction. We introduce a novel geometric representation of contact interactions using the edge simplices from alpha shape of…

生物物理 · 物理学 2007-05-23 Xiang Li , Changyu Hu , Jie Liang

A microscopic theory of the free energy barriers and folding routes for minimally frustrated proteins is presented, greatly expanding on the presentation of the variational approach outlined previously [J. J. Portman, S. Takada, P. G.…

软凝聚态物质 · 物理学 2009-10-31 John J. Portman , Shoji Takada , Peter G. Wolynes

Background:Prediction of protein three-dimensional structures from amino acid sequences is a long-standing goal in computational/molecular biology. The successful discrimination of protein folds would help to improve the accuracy of protein…

生物大分子 · 定量生物学 2007-05-23 Y-h. Taguchi , M. Michael Gromiha

Biological diversity has evolved despite the essentially infinite complexity of protein sequence space. We present a hierarchical approach to the efficient searching of this space and quantify the evolutionary potential of our approach with…

统计力学 · 物理学 2009-10-31 Leonard D. Bogarad , Michael W. Deem

Protein sequences serve as a natural record of the evolutionary constraints that shape their functional structures. We show that it is possible to use only sequence information to go beyond predicting native structures and global stability…

生物大分子 · 定量生物学 2025-07-02 Ezequiel A. Galpern , Ernesto A. Roman , Diego U. Ferreiro

A coarse-grained variational model is used to investigate the polymer dynamics of barrier crossing for a diverse set of two-state folding proteins. The model gives reliable folding rate predictions provided excluded volume terms that induce…

生物大分子 · 定量生物学 2009-11-13 Xianghong Qi , John J. Portman

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

We propose an application of molecular information theory to analyze the folding of single domain proteins. We analyze results from various areas of protein science, such as sequence-based potentials, reduced amino acid alphabets, backbone…

生物大分子 · 定量生物学 2022-06-30 Ignacio E. Sánchez , Ezequiel A. Galpern , Martín M. Garibaldi , Diego U. Ferreiro

Proteins fold using a two-state or multi-state kinetic mechanisms, but up to now there isn't a first-principle model to explain this different behaviour. We exploit the network properties of protein structures by introducing novel…

分子网络 · 定量生物学 2015-12-04 Giulia Menichetti , Piero Fariselli , Daniel Remondini

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

Small-molecule foundation models are typically pretrained on standalone molecular data, unlike vision and language models that often benefit from cross-modal or relational supervision. Protein-ligand co-folding provides a molecular analogue…

生物大分子 · 定量生物学 2026-05-25 Hyosoon Jang , Hyunjin Seo , Honghui Kim , Seonghyun Park , Taewon Kim , Yunhui Jang , Sungsoo Ahn
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