High-Resolution Modeling of Protein-Protein Interaction Networks Within and Between Species

物种内和物种间蛋白质-蛋白质相互作用网络的高分辨率建模

• 批准号: RGPIN-2014-03892
• 负责人: Xia, Yu
• 金额: $ 3.57万
• 依托单位: McGill University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2016
• 资助国家: 加拿大
• 起止时间: 2016-01-01 至 2017-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=610707
• 关键词: Resolution; Modeling; Protein; Interaction; Networks

A major focus of the emerging field of host-microbe systems biology is the elucidation of general principles governing host-microbe protein-protein interaction networks. However, current analyses generate limited insights into host-microbe interactions as they operate on a highly abstract level, treating proteins as nodes and protein-protein interactions as edges. A key bottleneck is the lack of a three-dimensional (3D), atomistic view of the host-microbe biomolecular interaction network at the genomic scale. Recently, we constructed the first 3D structural map of the network of interactions among human proteins and viral proteins. The resulting host-virus structural interaction network provided significant insights into host-virus interactions. However, our preliminary map of human-microbe structural interaction network is severely limited in coverage and accuracy. The long-term objective of the proposed research program is to develop and apply novel methods to build 3D atomistic structural models for known human-human and human-microbe protein-protein interactions with the highest possible accuracy and coverage. Such a high-resolution view of cellular circuitry will enable algorithm development for better prediction of gene function and better understanding of normal and disease biology, enable the discovery of new principles governing intra- and inter-species interactions that are otherwise hidden in the binary network, and enable the construction of in silico whole-cell models for predictive simulation of cell behavior. To achieve this long-term objective, five short-term objectives are proposed. First, we will construct 3D structural models for within-human and human-microbe protein-protein interactions using homology modeling. Second, we will improve the coverage of within-human and human-microbe structural interaction networks by building structural models not only for interactions between globular domains, but also for the equally abundant interactions between linear motif binding domains and the substrate domains that contain the linear peptide motifs. Third, we will improve the coverage of within-human and human-microbe structural interaction networks by developing new threading- and docking-based algorithms for structural interaction modeling. Fourth, we will build accurate structural models of within-human and human-microbe protein-protein interactions by explicitly using 3D structural information to improve sequence alignment. Fifth, we will validate our predictions by a combination of computational analyses and experimental collaborations. The proposed research program will significantly advance the state-of-the-art in host-microbe systems biology by constructing a 3D structural view of human-human and human-microbe interactions that are otherwise hidden in the binary network. The proposed work is the first to apply a structural systems biology approach to host-microbe interaction and infectious disease research. Successful completion of the research program will lead to structural models of human-human and human-microbe protein-protein interactions with significantly improved accuracy and coverage, new tools for structural modeling of within-host and host-microbe protein-protein interaction networks, and improved systems-level understanding of host-microbe interactions and infectious diseases. Finally, the execution of this proposal will provide a set of algorithms, tools, and datasets that serve to maximize the impact of structural systems biology approaches on host-microbe interaction research.

宿主-微生物系统生物学这一新兴领域的一个主要焦点是阐明宿主-微生物蛋白质-蛋白质相互作用网络的一般原理。然而，目前的分析对宿主-微生物相互作用的了解有限，因为它们在高度抽象的水平上操作，将蛋白质视为节点，将蛋白质-蛋白质相互作用视为边缘。一个关键的瓶颈是缺乏一个三维（3D），原子的宿主-微生物生物分子相互作用网络在基因组规模的视图。最近，我们构建了人类蛋白质和病毒蛋白质之间相互作用网络的第一个3D结构图。由此产生的宿主-病毒结构相互作用网络为宿主-病毒相互作用提供了重要的见解。然而，我们初步的人类-微生物结构相互作用网络图在覆盖范围和准确性方面受到严重限制。 拟议研究计划的长期目标是开发和应用新方法，以尽可能高的准确性和覆盖率为已知的人类-人类和人类-微生物蛋白质-蛋白质相互作用构建3D原子结构模型。这种高分辨率的细胞电路视图将使算法开发能够更好地预测基因功能，更好地理解正常和疾病生物学，能够发现管理物种内和物种间相互作用的新原理，这些原理原本隐藏在二元网络中，并能够构建用于预测模拟细胞行为的计算机全细胞模型。 为实现这一长期目标，提出了五项短期目标。首先，我们将使用同源建模来构建人内和人-微生物蛋白质-蛋白质相互作用的3D结构模型。其次，我们将通过建立结构模型，不仅为球状结构域之间的相互作用，而且为线性基序结合结构域和含有线性肽基序的底物结构域之间的同样丰富的相互作用，提高覆盖范围内的人类和人类微生物结构相互作用网络。第三，我们将通过开发新的基于线程和对接的结构相互作用建模算法来提高人体内和人类-微生物结构相互作用网络的覆盖率。第四，我们将通过明确使用3D结构信息来改进序列比对，建立人内和人-微生物蛋白质-蛋白质相互作用的精确结构模型。第五，我们将通过计算分析和实验合作的结合来验证我们的预测。 拟议的研究计划将通过构建人与人和人与微生物相互作用的3D结构视图来显着推进宿主-微生物系统生物学的最新技术，否则这些相互作用将隐藏在二元网络中。拟议的工作是第一个将结构系统生物学方法应用于宿主-微生物相互作用和传染病研究。该研究计划的成功完成将导致人与人和人与微生物蛋白质相互作用的结构模型，具有显着提高的准确性和覆盖率，用于宿主内和宿主-微生物蛋白质相互作用网络的结构建模的新工具，以及提高对宿主-微生物相互作用和传染病的系统级理解。最后，该提案的执行将提供一套算法，工具和数据集，以最大限度地发挥结构系统生物学方法对宿主-微生物相互作用研究的影响。