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相关论文: A Deterministic Approach to the Protein Design Pro…

200 篇论文

We study the designability of all compact 3x3x3 and 6x6 lattice-protein structures using the Miyazawa-Jernigan (MJ) matrix. The designability of a structure is the number of sequences that design the structure, i.e. sequences that have that…

统计力学 · 物理学 2007-05-23 Hao Li , Chao Tang , Ned Wingreen

Here we present an approximate analytical theory for the relationship between a protein structure's contact matrix and the shape of its energy spectrum in amino acid sequence space. We demonstrate a dependence of the number of sequences of…

软凝聚态物质 · 物理学 2009-11-07 Jeremy L. England , Eugene I. Shakhnovich

This chapter discusses theoretical framework and methods for developing knowledge-based potential functions essential for protein structure prediction, protein-protein interaction, and protein sequence design. We discuss in some details…

生物大分子 · 定量生物学 2015-06-26 Xiang Li , Jie Liang

We show that the hydrophobicity of sequences is the leading term in Miyazawa-Jernigan interactions. Being the source of additive (solvation) terms in pair-contact interactions, they were used to reduce the energy parameters while resulting…

生物大分子 · 定量生物学 2007-05-23 N. Hamedani Radja , R. R. Farzami , M. R. Ejtehadi

Based on the concept of energy landscape a picture of the mismatch between the reduced interaction matrix of residues and the matrix of statistical contact potentials is presented. For the Miyazawa and Jernigan (MJ) matrix, rational…

软凝聚态物质 · 物理学 2007-05-23 Jun Wang , Wei Wang

We present a detailed study of the performance and reliability of design procedures based on energy minimization. The analysis is carried out for model proteins where exact results can be obtained through exhaustive enumeration. The…

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

We propose and discuss a novel strategy for protein design. The method is based on recent theoretical advancements which showed the importance to treat carefully the conformational free energy of designed sequences. In this work we show how…

统计力学 · 物理学 2009-10-31 A. Rossi , A. Maritan , C. Micheletti

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…

软凝聚态物质 · 物理学 2007-05-23 R. A. Broglia , G. Tiana , H. E. Roman

We propose a novel method for the determination of the effective interaction potential between the amino acids of a protein. The strategy is based on the combination of a new optimization procedure and a geometrical argument, which also…

软凝聚态物质 · 物理学 2009-10-31 Jort van Mourik , Cecilia Clementi , Amos Maritan , Flavio Seno , J. R. Banavar

The possibility of deriving the contact potentials between amino acids from their frequencies of occurence in proteins is discussed in evolutionary terms. This approach allows the use of traditional thermodynamics to describe such…

生物大分子 · 定量生物学 2009-11-10 G. Tiana , M. Colombo , D. Provasi , R. A. Broglia

We apply a new approach to the reverse protein folding problem. Our method uses a minimization function in the design process which is different from the energy function used for folding. For a lattice model, we show that this new approach…

凝聚态物理 · 物理学 2009-10-28 J. M. Deutsch , Tanya Kurosky

In a statistical approach to protein structure analysis, Miyazawa and Jernigan (MJ) derived a $20\times 20$ matrix of inter-residue contact energies between different types of amino acids. Using the method of eigenvalue decomposition, we…

统计力学 · 物理学 2009-10-28 Hao Li , Chao Tang , Ned Wingreen

We review the recent progress in computational approaches to protein design which builds on advances in statistical-mechanical protein folding theory. In particular, we evaluate the degeneracy of the protein code (i.e. how many sequences…

凝聚态物理 · 物理学 2007-05-23 E. I. Shakhnovich

We propose an energy-based model (EBM) of protein conformations that operates at atomic scale. The model is trained solely on crystallized protein data. By contrast, existing approaches for scoring conformations use energy functions that…

机器学习 · 计算机科学 2020-04-29 Yilun Du , Joshua Meier , Jerry Ma , Rob Fergus , Alexander Rives

We analytically derive the lower bound of the total conformational energy of a protein structure by assuming that the total conformational energy is well approximated by the sum of sequence-dependent pairwise contact energies. The condition…

生物大分子 · 定量生物学 2008-01-03 Akira R. Kinjo , Sanzo Miyazawa

Protein structure prediction is considered as one of the most challenging and computationally intractable combinatorial problem. Thus, the efficient modeling of convoluted search space, the clever use of energy functions, and more…

神经与进化计算 · 计算机科学 2016-07-22 Mahmood A. Rashid , Sumaiya Iqbal , Firas Khatib , Md Tamjidul Hoque , Abdul Sattar

The simplest approximation of interaction potential between amino-acids in proteins is the contact potential, which defines the effective free energy of a protein conformation by a set of amino acid contacts formed in this conformation.…

生物大分子 · 定量生物学 2007-05-23 Jainab Kahtun , Sagar D. Khare , Nikolay V. Dokholyan

We present an analytical method for determining the designability of protein structures. We apply our method to the case of two-dimensional lattice structures, and give a systematic solution for the spectrum of any structure. Using this…

软凝聚态物质 · 物理学 2009-10-31 Edo L. Kussell , Eugene I. Shakhnovich

Predicting protein structure from the amino acid sequence has been a challenge with theoretical and practical significance in biophysics. Despite the recent progresses elicited by improved residue-residue contact prediction, contact-based…

生物大分子 · 定量生物学 2019-12-19 Wenze Ding , Haipeng Gong

In this study, we propose an analytic statistical mechanics approach to solve a fundamental problem in biological physics called protein design. Protein design is an inverse problem of protein structure prediction, and its solution is the…

统计力学 · 物理学 2022-10-26 Tomoei Takahashi , George Chikenji , Kei Tokita
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