Detecting protein structural and functional innovations from genomic data

从基因组数据中检测蛋白质结构和功能创新

基本信息

批准号：
435973-2013
负责人：
Doxey, Andrew
金额：
$ 2.99万
依托单位：
University of Waterloo
依托单位国家：
加拿大
项目类别：
Discovery Grants Program - Individual
财政年份：
2017
资助国家：
加拿大
起止时间：
2017-01-01 至 2018-12-31
项目状态：
已结题

来源：
https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=630006
关键词：
Detecting protein structural functional innovations

项目摘要

Our work combines structural bioinformatics, genomics, and phylogenetics to study the evolution of protein structures and functions. Understanding how proteins structures evolve and encode different biological functions is critical in our efforts to interpret genomic data as well as design novel functions through synthetic biology.A fundamental component of our approach is large-scale analysis of protein 3D structure models derived from genomic data for sensitive detection of protein functions that cannot be detected using sequence alone. The proposed work will expand and generalize our work on computational screening of large-scale genomic data for key protein structural and functional adaptations. First, we intend to apply this approach to discover cases of ongoing protein fold evolution from genomic data, which has significant applications to protein folding and design research. Second, we will use this approach to discover evolution of lineage-specific binding sites at proteome-wide scales, followed by experimental characterization of predicted interactions. A particular focus of this work will be identification of novel carbohydrate-binding sites in plant proteins with roles in defense against plant pathogens. Third, we aim to apply the approach to discover novel enzyme (e.g., cellulase) variants from high diversity metagenomic sequence data. This will create a framework for metagenomics-aided protein function discovery and design.Ultimately, the proposed work will advance computational methods for sensitive detection of protein functions and adaptations from genomic data. This has applications in a range of areas within biology, but it also contributes to our basic understanding of protein diversity and how to mine it for our own purposes.

我们的工作结合了结构生物信息学、基因组学和系统发育学来研究蛋白质结构和功能的进化。了解蛋白质结构如何进化和编码不同的生物功能对于我们解释基因组数据以及通过合成生物学设计新功能至关重要。我们方法的一个基本组成部分是对源自基因组数据的蛋白质 3D 结构模型进行大规模分析。灵敏地检测仅使用序列无法检测到的蛋白质功能。拟议的工作将扩展和概括我们对大规模基因组数据进行计算筛选以进行关键蛋白质结构和功能适应的工作。首先，我们打算应用这种方法从基因组数据中发现正在进行的蛋白质折叠进化的案例，这对于蛋白质折叠和设计研究具有重要的应用。其次，我们将使用这种方法在蛋白质组范围内发现谱系特异性结合位点的进化，然后对预测的相互作用进行实验表征。这项工作的一个特别重点是鉴定植物蛋白中新的碳水化合物结合位点，这些位点在防御植物病原体中发挥作用。第三，我们的目标是应用该方法从高多样性宏基因组序列数据中发现新的酶（例如纤维素酶）变体。这将为宏基因组学辅助蛋白质功能发现和设计创建一个框架。最终，拟议的工作将推进用于灵敏检测蛋白质功能和基因组数据适应的计算方法。这在生物学的一系列领域都有应用，但它也有助于我们对蛋白质多样性的基本理解以及如何为我们自己的目的挖掘它。