Detecting protein structural and functional innovations from genomic data

点击翻译按钮获取中文摘要

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.