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

• 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: 2018
• 资助国家: 加拿大
• 起止时间: 2018-01-01 至 2019-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=649546
• 关键词: Detecting; protein; structural; functional; innovations

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、基因组学和遗传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的努力至关重要。我们的方法的一个基本组成部分是大规模的蛋白质3D结构模型的分析，从基因组数据的蛋白质功能，不能单独使用序列检测灵敏的检测。拟议的工作将扩大和推广我们的工作计算筛选大规模基因组数据的关键蛋白质结构和功能的适应。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，这对蛋白质折叠和设计研究有重要的应用。其次，我们将使用这种方法来发现谱系特异性结合位点在蛋白质组范围内的进化，然后通过实验表征预测的相互作用。这项工作的一个特别的重点将是识别新的碳水化合物结合位点的植物蛋白质防御植物病原体的作用。第三，我们的目标是应用该方法发现新的酶（例如，纤维素酶）变体。这将为宏基因组学辅助的蛋白质功能发现和设计创建一个框架。最终，拟议的工作将推进计算方法，用于从基因组数据中灵敏地检测蛋白质功能和适应性。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。