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用于假激酶研究的计算工具和资源。

Computational tools and resources for pseudokinase research.

机构信息

Department of Biochemistry & Molecular Biology, University of Georgia, Athens, GA, United States.

Institute of Bioinformatics, University of Georgia, Athens, GA, United States.

出版信息

Methods Enzymol. 2022;667:403-426. doi: 10.1016/bs.mie.2022.03.040. Epub 2022 Apr 8.

Abstract

Pseudokinases regulate diverse cellular processes associated with normal cellular functions and disease. They are defined bioinformatically based on the absence of one or more catalytic residues that are required for canonical protein kinase functions. The ability to define pseudokinases based on primary sequence comparison has enabled the systematic mapping and cataloging of pseudokinase orthologs across the tree of life. While these sequences contain critical information regarding pseudokinase evolution and functional specialization, extracting this information and generating testable hypotheses based on integrative mining of sequence and structural data requires specialized computational tools and resources. In this chapter, we review recent advances in the development and application of open-source tools and resources for pseudokinase research. Specifically, we describe the application of an interactive data analytics framework, KinView, for visualizing the patterns of conservation and variation in the catalytic domain motifs of pseudokinases and evolutionarily related canonical kinases using a consistent set of curated alignments organized based on the widely used kinome evolutionary hierarchy. We also demonstrate the application of an integrated Protein Kinase Ontology (ProKinO) and an interactive viewer, ProtVista, for mapping and analyzing primary sequence motifs and annotations in the context of 3D structures and AlphaFold2 models. We provide examples and protocols for generating testable hypotheses on pseudokinase functions both for bench biologists and advanced users.

摘要

假激酶调节与正常细胞功能和疾病相关的多种细胞过程。它们是根据经典蛋白激酶功能所需的一个或多个催化残基的缺失在生物信息学上定义的。基于序列比较定义假激酶的能力使得能够在生命之树中系统地绘制和编目假激酶直系同源物。虽然这些序列包含有关假激酶进化和功能特化的关键信息,但基于序列和结构数据的综合挖掘提取这些信息并生成可测试的假说需要专门的计算工具和资源。在本章中,我们回顾了用于假激酶研究的开源工具和资源的最新进展和应用。具体来说,我们描述了使用交互式数据分析框架 KinView 的应用,该框架用于使用一致的精选对齐集可视化催化结构域基序中的保守和变异模式,这些精选对齐集是基于广泛使用的激酶进化层次结构组织的。我们还展示了集成的蛋白激酶本体 (ProKinO) 和交互式查看器 ProtVista 的应用,用于在 3D 结构和 AlphaFold2 模型的上下文中映射和分析主要序列基序和注释。我们为实验生物学家和高级用户提供了生成假激酶功能的可测试假说的示例和方案。

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