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CAVER:一种探索蛋白质裂缝、口袋和腔道路径的新工具。

CAVER: a new tool to explore routes from protein clefts, pockets and cavities.

作者信息

Petrek Martin, Otyepka Michal, Banás Pavel, Kosinová Pavlína, Koca Jaroslav, Damborský Jirí

机构信息

National Center for Biomolecular Research, Masaryk University, Kamenice 5/A4, 625 00 Brno, Czech Republic.

出版信息

BMC Bioinformatics. 2006 Jun 22;7:316. doi: 10.1186/1471-2105-7-316.

Abstract

BACKGROUND

The main aim of this study was to develop and implement an algorithm for the rapid, accurate and automated identification of paths leading from buried protein clefts, pockets and cavities in dynamic and static protein structures to the outside solvent.

RESULTS

The algorithm to perform a skeleton search was based on a reciprocal distance function grid that was developed and implemented for the CAVER program. The program identifies and visualizes routes from the interior of the protein to the bulk solvent. CAVER was primarily developed for proteins, but the algorithm is sufficiently robust to allow the analysis of any molecular system, including nucleic acids or inorganic material. Calculations can be performed using discrete structures from crystallographic analysis and NMR experiments as well as with trajectories from molecular dynamics simulations. The fully functional program is available as a stand-alone version and as plug-in for the molecular modeling program PyMol. Additionally, selected functions are accessible in an online version.

CONCLUSION

The algorithm developed automatically finds the path from a starting point located within the interior of a protein. The algorithm is sufficiently rapid and robust to enable routine analysis of molecular dynamics trajectories containing thousands of snapshots. The algorithm is based on reciprocal metrics and provides an easy method to find a centerline, i.e. the spine, of complicated objects such as a protein tunnel. It can also be applied to many other molecules. CAVER is freely available from the web site http://loschmidt.chemi.muni.cz/caver/.

摘要

背景

本研究的主要目的是开发并实施一种算法,用于在动态和静态蛋白质结构中快速、准确且自动地识别从埋藏的蛋白质裂缝、口袋和腔通向外部溶剂的路径。

结果

执行骨架搜索的算法基于为CAVER程序开发并实施的倒数距离函数网格。该程序可识别并可视化从蛋白质内部通向本体溶剂的路径。CAVER最初是为蛋白质开发的,但该算法足够强大,可用于分析任何分子系统,包括核酸或无机材料。计算可使用来自晶体学分析和核磁共振实验的离散结构以及分子动力学模拟的轨迹来进行。该功能齐全的程序有独立版本,也可作为分子建模程序PyMol的插件。此外,选定的功能可在在线版本中使用。

结论

所开发的算法可自动找到从位于蛋白质内部的起点出发的路径。该算法足够快速且强大,能够对包含数千个快照的分子动力学轨迹进行常规分析。该算法基于倒数度量,提供了一种简便方法来找到复杂物体(如蛋白质通道)的中心线,即脊柱。它也可应用于许多其他分子。CAVER可从网站http://loschmidt.chemi.muni.cz/caver/免费获取。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c147/1539030/afed0e67419d/1471-2105-7-316-1.jpg

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