Engineering Protein Dynamics through Mutational Energy Landscape Traps.

IF 5.6 2区 化学 Q1 CHEMISTRY, MEDICINAL
Lucas de Almeida Machado, João Sartori, Paula Fernandes da Costa Franklin, Mauricio G S Costa, Ana Carolina Ramos Guimarães
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引用次数: 0

Abstract

Protein dynamics is essential for various biological processes, influencing functions such as enzyme activity, molecular recognition, and signal transduction. However, traditional protein engineering methods often focus on static structures, lacking tools to precisely manipulate dynamic behaviors. Here, we developed Mutational Energy Landscape Trap (MELT), a novel method designed to control protein dynamics by combining Normal Mode Analysis (NMA) and in silico mutagenesis. MELT works by displacing protein structures along low-frequency normal modes and introducing mutations to either lock proteins in these conformations or increase dynamics along the chosen normal modes. We tested MELT using hen-egg lysozyme as a model system. The method was validated by monitoring relevant collective coordinates during molecular dynamics simulations and evaluation of the collective movements of each construct. Our experiments showed that MELT was able to consistently create new protein sequences with the desired dynamical behavior in simulations. It demonstrates its potential for applications in the field of protein engineering, being an unprecedented way of manipulating protein features.

通过突变能量景观陷阱的工程蛋白质动力学。
蛋白质动力学对各种生物过程至关重要,影响酶活性、分子识别和信号转导等功能。然而,传统的蛋白质工程方法往往侧重于静态结构,缺乏精确操纵动态行为的工具。在这里,我们开发了突变能量景观陷阱(MELT),这是一种通过结合正常模式分析(NMA)和硅诱变来控制蛋白质动力学的新方法。MELT的工作原理是沿着低频正常模式取代蛋白质结构,并引入突变,要么将蛋白质锁定在这些构象中,要么增加沿着所选正常模式的动态。我们使用鸡蛋溶菌酶作为模型系统来测试MELT。通过在分子动力学模拟过程中监测相关的集体坐标并评估每个结构的集体运动,验证了该方法的有效性。我们的实验表明,MELT能够在模拟中始终如一地创建具有所需动态行为的新蛋白质序列。它是一种前所未有的操纵蛋白质特征的方法,在蛋白质工程领域具有广阔的应用前景。
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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来源期刊
CiteScore
9.80
自引率
10.70%
发文量
529
审稿时长
1.4 months
期刊介绍: The Journal of Chemical Information and Modeling publishes papers reporting new methodology and/or important applications in the fields of chemical informatics and molecular modeling. Specific topics include the representation and computer-based searching of chemical databases, molecular modeling, computer-aided molecular design of new materials, catalysts, or ligands, development of new computational methods or efficient algorithms for chemical software, and biopharmaceutical chemistry including analyses of biological activity and other issues related to drug discovery. Astute chemists, computer scientists, and information specialists look to this monthly’s insightful research studies, programming innovations, and software reviews to keep current with advances in this integral, multidisciplinary field. As a subscriber you’ll stay abreast of database search systems, use of graph theory in chemical problems, substructure search systems, pattern recognition and clustering, analysis of chemical and physical data, molecular modeling, graphics and natural language interfaces, bibliometric and citation analysis, and synthesis design and reactions databases.
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