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利用信息与压缩技术对蛋白质结构比对进行统计推断

Statistical inference of protein structural alignments using information and compression.

作者信息

Collier James H, Allison Lloyd, Lesk Arthur M, Stuckey Peter J, Garcia de la Banda Maria, Konagurthu Arun S

机构信息

Faculty of Information Technology, Monash University, Clayton, VIC 3800, Australia.

Department of Biochemistry and Molecular Biology, Pennsylvania State University, University Park, PA 16802, USA.

出版信息

Bioinformatics. 2017 Apr 1;33(7):1005-1013. doi: 10.1093/bioinformatics/btw757.

DOI:10.1093/bioinformatics/btw757
PMID:28065899
Abstract

MOTIVATION

Structural molecular biology depends crucially on computational techniques that compare protein three-dimensional structures and generate structural alignments (the assignment of one-to-one correspondences between subsets of amino acids based on atomic coordinates). Despite its importance, the structural alignment problem has not been formulated, much less solved, in a consistent and reliable way. To overcome these difficulties, we present here a statistical framework for the precise inference of structural alignments, built on the Bayesian and information-theoretic principle of Minimum Message Length (MML). The quality of any alignment is measured by its explanatory power-the amount of lossless compression achieved to explain the protein coordinates using that alignment.

RESULTS

We have implemented this approach in MMLigner , the first program able to infer statistically significant structural alignments. We also demonstrate the reliability of MMLigner 's alignment results when compared with the state of the art. Importantly, MMLigner can also discover different structural alignments of comparable quality, a challenging problem for oligomers and protein complexes.

AVAILABILITY AND IMPLEMENTATION

Source code, binaries and an interactive web version are available at http://lcb.infotech.monash.edu.au/mmligner .

CONTACT

arun.konagurthu@monash.edu.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

摘要

动机

结构分子生物学在很大程度上依赖于比较蛋白质三维结构并生成结构比对(基于原子坐标在氨基酸子集之间进行一一对应分配)的计算技术。尽管其很重要,但结构比对问题尚未以一种一致且可靠的方式得到阐述,更不用说解决了。为克服这些困难,我们在此提出一个基于贝叶斯和最小消息长度(MML)信息论原理的用于精确推断结构比对的统计框架。任何比对的质量都通过其解释力来衡量——即使用该比对来解释蛋白质坐标时所实现的无损压缩量。

结果

我们已在MMLigner中实现了这种方法,MMLigner是首个能够推断具有统计学意义的结构比对的程序。与现有技术相比,我们还展示了MMLigner比对结果的可靠性。重要的是,MMLigner还能发现质量相当的不同结构比对,这对于寡聚体和蛋白质复合物来说是一个具有挑战性的问题。

可用性与实现方式

可在http://lcb.infotech.monash.edu.au/mmligner获取源代码、二进制文件及交互式网络版本。

联系方式

arun.konagurthu@monash.edu。

补充信息

补充数据可在《生物信息学》在线获取。

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