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从一级序列预测摆动功能灵活区域。

Wiggle-predicting functionally flexible regions from primary sequence.

作者信息

Gu Jenny, Gribskov Michael, Bourne Philip E

机构信息

Department of Pharmacology and Biomedical Sciences Graduate Program, University of California San Diego, La Jolla, California, USA.

出版信息

PLoS Comput Biol. 2006 Jul 14;2(7):e90. doi: 10.1371/journal.pcbi.0020090. Epub 2006 Jun 5.

Abstract

The Wiggle series are support vector machine-based predictors that identify regions of functional flexibility using only protein sequence information. Functionally flexible regions are defined as regions that can adopt different conformational states and are assumed to be necessary for bioactivity. Many advances have been made in understanding the relationship between protein sequence and structure. This work contributes to those efforts by making strides to understand the relationship between protein sequence and flexibility. A coarse-grained protein dynamic modeling approach was used to generate the dataset required for support vector machine training. We define our regions of interest based on the participation of residues in correlated large-scale fluctuations. Even with this structure-based approach to computationally define regions of functional flexibility, predictors successfully extract sequence-flexibility relationships that have been experimentally confirmed to be functionally important. Thus, a sequence-based tool to identify flexible regions important for protein function has been created. The ability to identify functional flexibility using a sequence based approach complements structure-based definitions and will be especially useful for the large majority of proteins with unknown structures. The methodology offers promise to identify structural genomics targets amenable to crystallization and the possibility to engineer more flexible or rigid regions within proteins to modify their bioactivity.

摘要

摆动系列是基于支持向量机的预测器,仅使用蛋白质序列信息来识别功能灵活性区域。功能灵活性区域被定义为可以采用不同构象状态的区域,并被认为是生物活性所必需的。在理解蛋白质序列与结构之间的关系方面已经取得了许多进展。这项工作通过努力理解蛋白质序列与灵活性之间的关系,为这些努力做出了贡献。使用粗粒度蛋白质动力学建模方法来生成支持向量机训练所需的数据集。我们基于残基参与相关大规模波动来定义我们感兴趣的区域。即使采用这种基于结构的方法来通过计算定义功能灵活性区域,预测器也成功提取了已通过实验证实具有功能重要性的序列 - 灵活性关系。因此,创建了一种基于序列的工具来识别对蛋白质功能重要的灵活区域。使用基于序列的方法识别功能灵活性的能力补充了基于结构的定义,对于绝大多数结构未知的蛋白质将特别有用。该方法有望识别适合结晶的结构基因组学靶点,并有可能在蛋白质中设计更灵活或更刚性的区域以改变其生物活性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/00c4/1523303/5284da297b3d/pcbi.0020090.g001.jpg

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