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MAVENs:弹性网络和结构集合的运动分析和可视化。

MAVENs: motion analysis and visualization of elastic networks and structural ensembles.

机构信息

LH Baker Center for Bioinformatics and Biological Statistics, Iowa State University, Ames, IA 50011, USA.

出版信息

BMC Bioinformatics. 2011 Jun 28;12:264. doi: 10.1186/1471-2105-12-264.

Abstract

BACKGROUND

The ability to generate, visualize, and analyze motions of biomolecules has made a significant impact upon modern biology. Molecular Dynamics has gained substantial use, but remains computationally demanding and difficult to setup for many biologists. Elastic network models (ENMs) are an alternative and have been shown to generate the dominant equilibrium motions of biomolecules quickly and efficiently. These dominant motions have been shown to be functionally relevant and also to indicate the likely direction of conformational changes. Most structures have a small number of dominant motions. Comparing computed motions to the structure's conformational ensemble derived from a collection of static structures or frames from an MD trajectory is an important way to understand functional motions as well as evaluate the models. Modes of motion computed from ENMs can be visualized to gain functional and mechanistic understanding and to compute useful quantities such as average positional fluctuations, internal distance changes, collectiveness of motions, and directional correlations within the structure.

RESULTS

Our new software, MAVEN, aims to bring ENMs and their analysis to a broader audience by integrating methods for their generation and analysis into a user friendly environment that automates many of the steps. Models can be constructed from raw PDB files or density maps, using all available atomic coordinates or by employing various coarse-graining procedures. Visualization can be performed either with our software or exported to molecular viewers. Mixed resolution models allow one to study atomic effects on the system while retaining much of the computational speed of the coarse-grained ENMs. Analysis options are available to further aid the user in understanding the computed motions and their importance for its function.

CONCLUSION

MAVEN has been developed to simplify ENM generation, allow for diverse models to be used, and facilitate useful analyses, all on the same platform. This represents an integrated approach that incorporates all four levels of the modeling process - generation, evaluation, analysis, visualization - and also brings to bear multiple ENM types. The intension is to provide a versatile modular suite of programs to a broader audience. MAVEN is available for download at http://maven.sourceforge.net.

摘要

背景

生成、可视化和分析生物分子运动的能力对现代生物学产生了重大影响。分子动力学得到了广泛的应用,但对于许多生物学家来说,它仍然计算要求高且难以设置。弹性网络模型(ENM)是一种替代方法,已被证明可以快速有效地生成生物分子的主要平衡运动。这些主导运动已被证明与功能相关,也能指示构象变化的可能方向。大多数结构都有少量的主导运动。将计算运动与结构的构象集合进行比较,该集合来自静态结构的集合或 MD 轨迹的帧数,是理解功能运动以及评估模型的重要方法。从 ENM 计算出的运动模式可以可视化,以获得功能和机械理解,并计算有用的量,如平均位置波动、内部距离变化、运动的一致性以及结构内的方向相关性。

结果

我们的新软件 MAVEN 通过将生成和分析方法集成到一个用户友好的环境中,将 ENM 及其分析带给更广泛的受众,该环境自动化了许多步骤。可以使用我们的软件或导出到分子查看器来进行可视化。混合分辨率模型允许在保留粗粒度 ENM 的大部分计算速度的同时,研究原子对系统的影响。分析选项可帮助用户进一步理解计算运动及其对功能的重要性。

结论

MAVEN 的开发简化了 ENM 的生成,允许使用多种模型,并在同一平台上促进有用的分析。这代表了一种集成方法,它整合了建模过程的四个层次——生成、评估、分析和可视化——并利用了多种 ENM 类型。目的是为更广泛的受众提供一套通用的模块化程序。MAVEN 可在 http://maven.sourceforge.net 下载。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f4a2/3213244/8e787c0d3abf/1471-2105-12-264-1.jpg

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