氨基酸序列空间中蛋白质系统的蒙特卡罗模拟。

IF 3.1 2区化学 Q3 CHEMISTRY, PHYSICAL

Journal of Chemical Physics Pub Date : 2025-03-21 DOI:10.1063/5.0240764

Yuko Okamoto

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引用次数: 0

摘要

在本文中，我们提出了研究氨基酸序列依赖于蛋白质结构的策略。为此，在氨基酸序列空间中执行Metropolis蒙特卡罗模拟是必要的。我们希望使用具有精确势能函数的粗粒度蛋白质模型。介绍了一种基于蛋白质结构数据库protein Data Bank的势能参数优化方法。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Toward a Monte Carlo simulation of protein systems in amino-acid sequence space.

In this article, we present our strategy for studying amino-acid sequence dependences on protein structures. For this purpose, performing Metropolis Monte Carlo simulations in the amino-acid sequence space is necessary. We want to use a coarse-grained protein model with an accurate potential energy function. We introduce a method for optimizing potential-energy parameters based on the native protein structure database, Protein Data Bank.

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来源期刊

Journal of Chemical Physics 物理-物理：原子、分子和化学物理

CiteScore

7.40

自引率

15.90%

发文量

1615

审稿时长

2 months

期刊介绍： The Journal of Chemical Physics publishes quantitative and rigorous science of long-lasting value in methods and applications of chemical physics. The Journal also publishes brief Communications of significant new findings, Perspectives on the latest advances in the field, and Special Topic issues. The Journal focuses on innovative research in experimental and theoretical areas of chemical physics, including spectroscopy, dynamics, kinetics, statistical mechanics, and quantum mechanics. In addition, topical areas such as polymers, soft matter, materials, surfaces/interfaces, and systems of biological relevance are of increasing importance. Topical coverage includes: Theoretical Methods and Algorithms Advanced Experimental Techniques Atoms, Molecules, and Clusters Liquids, Glasses, and Crystals Surfaces, Interfaces, and Materials Polymers and Soft Matter Biological Molecules and Networks.