ICARUS: flexible protein structural alignment based on Protein Units.

IF 4.4 3区 生物学 Q1 BIOCHEMICAL RESEARCH METHODS
Gabriel Cretin, Charlotte Périn, Nicolas Zimmermann, Tatiana Galochkina, Jean-Christophe Gelly
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引用次数: 0

Abstract

Motivation: Alignment of protein structures is a major problem in structural biology. The first approach commonly used is to consider proteins as rigid bodies. However, alignment of protein structures can be very complex due to conformational variability, or complex evolutionary relationships between proteins such as insertions, circular permutations or repetitions. In such cases, introducing flexibility becomes useful for two reasons: (i) it can help compare two protein chains which adopted two different conformational states, such as due to proteins/ligands interaction or post-translational modifications, and (ii) it aids in the identification of conserved regions in proteins that may have distant evolutionary relationships.

Results: We propose ICARUS, a new approach for flexible structural alignment based on identification of Protein Units, evolutionarily preserved structural descriptors of intermediate size, between secondary structures and domains. ICARUS significantly outperforms reference methods on a dataset of very difficult structural alignments.

Availability and implementation: Code is freely available online at https://github.com/DSIMB/ICARUS.

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ICARUS:基于蛋白质单位的柔性蛋白质结构比对。
动机:蛋白质结构的排列是结构生物学中的一个主要问题。常用的第一种方法是把蛋白质看作刚体。然而,由于构象变异性或蛋白质之间复杂的进化关系(如插入、循环排列或重复),蛋白质结构的排列可能非常复杂。在这种情况下,引入灵活性有两个原因:(i)它可以帮助比较由于蛋白质/配体相互作用或翻译后修饰而采用两种不同构象状态的两条蛋白质链,以及(ii)它有助于鉴定可能具有遥远进化关系的蛋白质中的保守区域。结果:我们提出了ICARUS,一种基于鉴定蛋白质单元的柔性结构比对的新方法,蛋白质单元是进化保存的中等大小的结构描述符,位于二级结构和结构域之间。在非常困难的结构比对数据集上,ICARUS显著优于参考方法。可用性和实现:代码可在https://github.com/DSIMB/ICARUS免费在线获得。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Bioinformatics
Bioinformatics 生物-生化研究方法
CiteScore
11.20
自引率
5.20%
发文量
753
审稿时长
2.1 months
期刊介绍: The leading journal in its field, Bioinformatics publishes the highest quality scientific papers and review articles of interest to academic and industrial researchers. Its main focus is on new developments in genome bioinformatics and computational biology. Two distinct sections within the journal - Discovery Notes and Application Notes- focus on shorter papers; the former reporting biologically interesting discoveries using computational methods, the latter exploring the applications used for experiments.
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