蛋白质中的力分解:方法和一般特性

IF 5.3 2区 化学 Q1 CHEMISTRY, MEDICINAL
Pengbo Song, Qiaojing Huang, Wenyu Li, Maodong Li* and Zhirong Liu*, 
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引用次数: 0

摘要

与生物分子结构的核心作用相比,基于力的补充观点在过去的研究中很少受到关注。在此,我们提出了一种简单的多体相互作用力分解方法,并提供了一些分析和可视化蛋白质中力的一般行为的技术。研究表明,原子力的波动幅度约为 3000 pN,这在细胞生物学中是非常巨大的。值得注意的是,原子力与位移之间的平均标量乘积普遍近似于-3kBT。这比它们波动幅度的简单乘积小了一个数量级,原因是力和位移方向之间的相关性出乎意料地弱。成对作用力高度各向异性,波动椭球呈拉长状。残基-残基力可以是吸引力或排斥力(尽管更可能是吸引力),形成某种由复杂的力网络稳定的张力结构。了解和预测相互作用网络为合理的药物设计和揭示分子识别机制奠定了基础。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Decomposition of Forces in Protein: Methodology and General Properties

Decomposition of Forces in Protein: Methodology and General Properties

In contrast to the central role played by the structure of biomolecules, the complementary force-based view has received little attention in past studies. Here, we proposed a simple method for the force decomposition of multibody interactions and provided some techniques to analyze and visualize the general behavior of forces in proteins. It was shown that atomic forces fluctuate at a magnitude of about 3000 pN, which is huge in the context of cell biology. Remarkably, the average scalar product between atomic force and displacement universally approximates −3kBT. This is smaller by an order of magnitude than the simple product of their fluctuation magnitudes due to the unexpectedly weak correlation between the directions of force and displacement. The pairwise forces are highly anisotropic, with elongated fluctuation ellipsoids. Residue–residue forces can be attractive or repulsive (despite being more likely to be attractive), forming some kind of tensegrity structure stabilized by a complicated network of forces. Being able to understand and predict the interaction network provides a basis for rational drug design and uncovering molecular recognition mechanisms.

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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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