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We present a geometrical analysis of the protrusion statistics of side chains in more than 4,000 high-resolution protein structures. We employ a coarse-grained representation of the protein backbone viewed as a linear chain of C{\alpha}…

Soft Condensed Matter · Physics 2024-01-29 Tatjana Škrbić , Achille Giacometti , Trinh X. Hoang , Amos Maritan , Jayanth R. Banavar

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…

Biomolecules · Quantitative Biology 2007-05-23 Erzsebet Ravasz , S. Gnanakaran , Zoltan Toroczkai

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…

Statistical Mechanics · Physics 2009-10-31 Chao Tang

We describe the results obtained from an improved model for protein folding. We find that a good agreement with the native structure of a 46 residue long, five-letter protein segment is obtained by carefully tuning the parameters of the…

Biomolecules · Quantitative Biology 2009-11-11 Andrea Nobile , Federico Rapuano

We present a model, based on symmetry and geometry, for proteins. Using elementary ideas from mathematics and physics, we derive the geometries of discrete helices and sheets. We postulate a compatible solvent-mediated emergent pairwise…

Soft Condensed Matter · Physics 2023-06-21 Jayanth R. Banavar , Achille Giacometti , Trinh X. Hoang , Amos Maritan , Tatjana Škrbić

In this study, the distributions of protein structure classes (or folding types) of experimentally determined structures from a legacy dataset and a comprehensive database (SCOP) are modeled precisely with geometric constructs such as…

Biomolecules · Quantitative Biology 2025-10-21 Boryeu Mao

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…

Biomolecules · Quantitative Biology 2025-05-26 Ezequiel A. Galpern , Federico Caamaño , Diego U. Ferreiro

Learning effective protein representations is critical in a variety of tasks in biology such as predicting protein function or structure. Existing approaches usually pretrain protein language models on a large number of unlabeled amino acid…

Machine Learning · Computer Science 2023-01-31 Zuobai Zhang , Minghao Xu , Arian Jamasb , Vijil Chenthamarakshan , Aurelie Lozano , Payel Das , Jian Tang

Inverse folding models have proven to be highly effective zero-shot predictors of protein stability. Despite this success, the link between the amino acid preferences of an inverse folding model and the free-energy considerations underlying…

The architecture of eukaryotic coding genes allows the production of several different protein isoforms by genes. Current gene phylogeny reconstruction methods make use of a single protein product per gene, ignoring information on…

Data Structures and Algorithms · Computer Science 2017-07-05 Esaie Kuitche , Manuel Lafond , Aïda Ouangraoua

Computational protein design has a wide variety of applications. Despite its remarkable success, designing a protein for a given structure and function is still a challenging task. On the other hand, the number of solved protein structures…

Quantitative Methods · Quantitative Biology 2018-04-26 Jingxue Wang , Huali Cao , John Z. H. Zhang , Yifei Qi

While DeepMind has tentatively solved protein folding, its inverse problem -- protein design which predicts protein sequences from their 3D structures -- still faces significant challenges. Particularly, the lack of large-scale standardized…

Quantitative Methods · Quantitative Biology 2022-02-15 Zhangyang Gao , Cheng Tan , Stan Z. Li

A phenomenological model hamiltonian to describe the folding of a protein with any given sequence is proposed. The protein is thought of as a collection of pieces of helices; as a consequence its configuration space increases with the…

Soft Condensed Matter · Physics 2009-10-30 Pierpaolo Bruscolini

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…

Biological Physics · Physics 2018-11-26 Walter A. Simmons

The analysis of the three-dimensional structure of proteins is an important topic in molecular biochemistry. Structure plays a critical role in defining the function of proteins and is more strongly conserved than amino acid sequence over…

Applications · Statistics 2015-01-19 Abel Rodriguez , Scott C. Schmidler

Proteins are large biomolecules that regulate all living organisms and consist of one or several chains. The primary structure of a protein chain is a sequence of amino acid residues whose three main atoms (alpha-carbon, nitrogen, and…

Computational Geometry · Computer Science 2025-12-30 Olga Anosova , Alexey Gorelov , William Jeffcott , Ziqiu Jiang , Vitaliy Kurlin

The mechanisms by which a protein's 3D structure can be determined based on its amino acid sequence have long been one of the key mysteries of biophysics. Often simplistic models, such as those derived from geometric constraints, capture…

Biological Physics · Physics 2023-01-02 Nora Molkenthin , J. J. Güven , Steffen Mühle , Antonia S. J. S. Mey

Making use of a simplified model for protein folding, it can be shown that conformations which are particularly stable when their energy is minimized with respect to amino acid sequence (in the sense that they display a large energy gap to…

Soft Condensed Matter · Physics 2007-05-23 R. A. Broglia , G. Tiana , H. E. Roman

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…

Disordered Systems and Neural Networks · Physics 2008-02-03 T. Garel , H. Orland , E. Pitard

Matrix inversion problems are often encountered in experimental physics, and in particular in high-energy particle physics, under the name of unfolding. The true spectrum of a physical quantity is deformed by the presence of a detector,…

Machine Learning · Statistics 2020-09-08 Pietro Vischia
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