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Local protein structure analysis is informative to protein structure analysis and has been used successfully in protein structure prediction and others. Proteins have recurring structural features, such as helix caps and beta turns, which…

组合数学 · 数学 2007-10-26 Naoto Morikawa

In nature the three-dimensional structure of a protein is encoded in the corresponding gene. In this paper we describe a new method for encoding the three-dimensional structure of a protein into a binary sequence. The feature of the method…

组合数学 · 数学 2007-05-23 Naoto Morikawa

This paper proposes a new mathematical framework that can be applied to biological problems such as analysis of the structures of proteins and protein complexes. In particular, it gives a new method for encoding the three-dimensional…

组合数学 · 数学 2007-05-23 Naoto Morikawa

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…

机器学习 · 计算机科学 2023-01-31 Zuobai Zhang , Minghao Xu , Arian Jamasb , Vijil Chenthamarakshan , Aurelie Lozano , Payel Das , Jian Tang

While all the information required for the folding of a protein is contained in its amino acid sequence, one has not yet learnt how to extract this information so as to predict the detailed, biological active, three-dimensional structure of…

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

Three-dimensional protein structures usually contain regions of local order, called secondary structure, such as $\alpha$-helices and $\beta$-sheets. Secondary structure is characterized by the local rotational state of the protein…

生物大分子 · 定量生物学 2016-08-10 Ranjan V. Mannige , Joyjit Kundu , Stephen Whitelam

This work reports a new methodology aimed at describing characteristics of protein structural shapes, and suggests a framework in which to resolve or classify automatically such structures into known families. This new approach to protein…

We seek to understand the interplay between amino acid sequence and local structure in proteins. Are some amino acids unique in their ability to fit harmoniously into certain local structures? What is the role of sequence in sculpting the…

生物大分子 · 定量生物学 2021-01-29 Tatjana Škrbić , Amos Maritan , Achille Giacometti , Jayanth R. Banavar

Simple hidden Markov models are proposed for predicting secondary structure of a protein from its amino acid sequence. Since the length of protein conformation segments varies in a narrow range, we ignore the duration effect of length…

生物物理 · 物理学 2007-05-23 Wei-Mou Zheng

Predicting protein structure from amino acid sequence is one of the most important unsolved problems of molecular biology and biophysics.Not only would a successful prediction algorithm be a tremendous advance in the understanding of the…

计算工程、金融与科学 · 计算机科学 2010-06-15 K. K Senapati , G. Sahoo , D. Bhaumik

The intricate three-dimensional geometries of protein tertiary structures underlie protein function and emerge through a folding process from one-dimensional chains of amino acids. The exact spatial sequence and configuration of amino…

生物大分子 · 定量生物学 2021-02-24 Nora Molkenthin , Steffen Mühle , Antonia S J S Mey , Marc Timme

The correct prediction of protein secondary structures is one of the key issues in predicting the correct protein folded shape, which is used for determining gene function. Existing methods make use of amino acids properties as indices to…

定量方法 · 定量生物学 2017-05-01 Jian-Jun Shu , Kian-Yan Yong

Proteins have regular tertiary structures but irregular amino acid sequences. This made it very difficult to decode the structural information in the protein sequences. Here we demonstrate that many small alpha protein domains have hidden…

生物大分子 · 定量生物学 2007-05-23 Ruizhen Xu , Yanzhao Huang , Mingfen Li , Hanlin Chen , Yi Xiao

Novel numerical techniques, validated by an analysis of barnase and chymotrypsin inhibitor, are used to elucidate the paramount role played by the geometry of the protein backbone in steering the folding to the correct native state. It is…

统计力学 · 物理学 2009-10-31 Cristian Micheletti , Jayanth R. Banavar , Amos Maritan , Flavio Seno

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

This paper deepens into the analysis of the protein secondary structure using Frenet frame to describe the curvature and torsion of the discrete curve formed by the protein $\alpha$-carbons. We show how a simple criterion based on the…

生物物理 · 物理学 2025-12-08 M. Prados , M. D. Hernández de la Torre , F. de Soto

Representation learning and \emph{de novo} generation of proteins are pivotal computational biology tasks. Whilst natural language processing (NLP) techniques have proven highly effective for protein sequence modelling, structure modelling…

定量方法 · 定量生物学 2025-01-08 Benoit Gaujac , Jérémie Donà , Liviu Copoiu , Timothy Atkinson , Thomas Pierrot , Thomas D. Barrett

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

Protein one-dimensional (1D) structures such as secondary structure and contact number provide intuitive pictures to understand how the native three-dimensional (3D) structure of a protein is encoded in the amino acid sequence. However, it…

生物大分子 · 定量生物学 2007-05-23 Akira R. Kinjo , Ken Nishikawa

We present a novel technique of sampling the configurations of helical proteins. Assuming knowledge of native secondary structure, we employ assembly rules gathered from a database of existing structures to enumerate the geometrically…

软凝聚态物质 · 物理学 2009-09-25 Boris Fain , Michael Levitt
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