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Application of new multi-resolution methods for the comparison of biomolecular electrostatic properties in the absence of global structural similarity

机译：在没有全局结构相似性的情况下新的多分辨率方法在生物分子静电特性比较中的应用

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In this paper we present a method for the multi-resolution comparison of biomolecular electrostatic potentials without the need for global structural alignment of the biomolecules. The underlying computational geometry algorithm uses multi-resolution attributed contour trees (MACTs) to compare the topological features of volumetric scalar fields. We apply the MACTs to compute electrostatic similarity metrics for a large set of protein chains with varying degrees of sequence, structure, and function similarity. For calibration, we also compute similarity metrics for these chains by a more traditional approach based upon 3D structural alignment and analysis of Carbo similarity indices. Moreover, because the MACT approach does not rely upon pairwise structural alignment, its accuracy and efficiency promises to perform well on future large-scale classification efforts across groups of structurally-diverse proteins. The MACT method discriminates between protein chains at a level comparable to the Carbo similarity index method; i.e., it is able to accurately cluster proteins into functionally-relevant groups which demonstrate strong dependence on ligand binding sites. The results of the analyses are available from the linked web databases and . The MACT analysis tools are available as part of the public domain library of the Topological Analysis and Quantitative Tools (TAQT) from the Center of Computational Visualization, at the University of Texas at Austin (). The Carbo software is available for download with the open-source APBS software package at .
机译：在本文中，我们提出了一种用于生物分子静电势多分辨率比较的方法，而无需对生物分子进行整体结构比对。底层的计算几何算法使用多分辨率属性轮廓树（MACT）来比较体积标量场的拓扑特征。我们应用MACT来计算具有不同程度的序列，结构和功能相似性的大量蛋白质链的静电相似性度量。为了进行校准，我们还基于3D结构对齐和Carbo相似性指数分析，通过更传统的方法为这些链计算了相似性度量。此外，由于MACT方法不依赖于成对的结构比对，因此其准确性和效率有望在未来跨结构多样蛋白的大规模分类工作中表现出色。 MACT方法以与Carbo相似性指数方法相当的水平区分蛋白质链。即，它能够将蛋白质准确地聚类为功能相关的基团，这些基团表现出对配体结合位点的强烈依赖性。分析结果可从链接的Web数据库和中获得。 MACT分析工具可从德克萨斯大学奥斯汀分校的计算可视化中心的拓扑分析和定量工具（TAQT）的公共领域库中获得。 Carbo软件可从上通过开源APBS软件包下载。

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