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
基本信息
- 批准号:RGPIN-2014-03892
- 负责人:
- 金额:$ 3.57万
- 依托单位:
- 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:
- 关键词:
项目摘要
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运作,将蛋白质视为节点,将蛋白质-蛋白质相互作用视为边缘。一个关键的瓶颈是在基因组尺度上缺乏宿主-微生物生物分子相互作用网络的三维(3D)原子观点。最近,我们构建了人类蛋白质和病毒蛋白质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,我们初步绘制的人-微生物结构相互作用网络在覆盖范围和准确性上受到严重限制。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建立已知的人类-人类和人类-微生物蛋白质-蛋白质相互作用的3D原子结构模型。这种细胞电路的高分辨率视图将使算法开发能够更好地预测基因功能和更好地理解正常和疾病生物学,使发现控制物种内和物种间相互作用的新原理成为可能,否则这些原理隐藏在二进制网络中,并使构建全细胞模型能够预测细胞行为的模拟。为实现这一长期目标,提出了五个短期目标。首先,我们将使用同源建模构建人体内和人-微生物蛋白质-蛋白质相互作用的3D结构模型。其次,我们将通过构建结构模型,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包含线性肽基序的底物结构域之间同样丰富的相互作用,来提高人类和人类-微生物结构相互作用网络的覆盖范围。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类内部和人类-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三维结构信息来提高序列比对,建立准确的人体内和人-微生物蛋白质-蛋白质相互作用的结构模型。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隐藏在二进制网络中的人类和人类-微生物相互作用的3D结构视图,显着推进宿主-微生物系统生物学的最新技术。这项工作是首次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类-人类和人类-微生物蛋白质-蛋白质相互作用的结构模型的准确性和覆盖率显著提高,宿主内和宿主-微生物蛋白质-蛋白质相互作用网络结构建模的新工具,以及改进系统级对宿主-微生物相互作用和传染病的理解。最后,本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。
项目成果
期刊论文数量(0)
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Xia, Yu其他文献
Histological and molecular glioblastoma, IDH-wildtype: a real-world landscape using the 2021 WHO classification of central nervous system tumors.
- DOI:
10.3389/fonc.2023.1200815 - 发表时间:
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Ma, Wenbin
Antioxidant capacity, phytochemical profiles, and phenolic metabolomics of selected edible seeds and their sprouts.
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10.3389/fnut.2022.1067597 - 发表时间:
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Liu, Hong-Yan;Liu, Yi;Li, Ming-Yue;Ge, Ying-Ying;Geng, Fang;He, Xiao-Qin;Xia, Yu;Guo, Bo-Li;Gan, Ren-You - 通讯作者:
Gan, Ren-You
An adaptive control framework based multi-modal information-driven dance composition model for musical robots.
音乐机器人的基于自适应控制框架的多模式信息驱动的舞蹈构成模型。
- DOI:
10.3389/fnbot.2023.1270652 - 发表时间:
2023 - 期刊:
- 影响因子:3.1
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Xu, Fumei;Xia, Yu;Wu, Xiaorun - 通讯作者:
Wu, Xiaorun
Oxalate Pushes Efficiency of CsPb(0.7) Sn(0.3) IBr(2) Based All-Inorganic Perovskite Solar Cells to over 14.
- DOI:
10.1002/advs.202106054 - 发表时间:
2022-04 - 期刊:
- 影响因子:15.1
- 作者:
Zhang, Weihai;Liu, Heng;Qi, Xingnan;Yu, Yinye;Zhou, Yecheng;Xia, Yu;Cui, Jieshun;Shi, Yueqing;Chen, Rui;Wang, Hsing-Lin - 通讯作者:
Wang, Hsing-Lin
The ADRENAL score: A comprehensive scoring system for standardized evaluation of adrenal tumor.
- DOI:
10.3389/fendo.2022.1073082 - 发表时间:
2022 - 期刊:
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- 作者:
Zhou, Xiaochen;Li, Xuwen;Fu, Bin;Liu, Weipeng;Zhang, Cheng;Xia, Yu;Gong, Honghan;Zhu, Lingyan;Lei, Enjun;Kaplan, Joshua;Deng, Yaoliang;Eun, Daniel;Wang, Gongxian - 通讯作者:
Wang, Gongxian
Xia, Yu的其他文献
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{{ truncateString('Xia, Yu', 18)}}的其他基金
Using Structural Systems Biology Modelling to Probe High-Resolution Design Principles of Protein Networks
利用结构系统生物学模型探索蛋白质网络的高分辨率设计原理
- 批准号:
RGPIN-2019-05952 - 财政年份:2022
- 资助金额:
$ 3.57万 - 项目类别:
Discovery Grants Program - Individual
Computational and Systems Biology
计算和系统生物学
- 批准号:
CRC-2021-00424 - 财政年份:2022
- 资助金额:
$ 3.57万 - 项目类别:
Canada Research Chairs
High-Resolution Modeling in Systems Biology
系统生物学中的高分辨率建模
- 批准号:
CRC-2015-00042 - 财政年份:2022
- 资助金额:
$ 3.57万 - 项目类别:
Canada Research Chairs
Using Structural Systems Biology Modelling to Probe High-Resolution Design Principles of Protein Networks
利用结构系统生物学模型探索蛋白质网络的高分辨率设计原理
- 批准号:
RGPIN-2019-05952 - 财政年份:2021
- 资助金额:
$ 3.57万 - 项目类别:
Discovery Grants Program - Individual
High-Resolution Modeling In Systems Biology
系统生物学中的高分辨率建模
- 批准号:
CRC-2015-00042 - 财政年份:2021
- 资助金额:
$ 3.57万 - 项目类别:
Canada Research Chairs
High-Resolution Modeling in Systems Biology
系统生物学中的高分辨率建模
- 批准号:
CRC-2015-00042 - 财政年份:2020
- 资助金额:
$ 3.57万 - 项目类别:
Canada Research Chairs
Using Structural Systems Biology Modelling to Probe High-Resolution Design Principles of Protein Networks
利用结构系统生物学模型探索蛋白质网络的高分辨率设计原理
- 批准号:
RGPIN-2019-05952 - 财政年份:2020
- 资助金额:
$ 3.57万 - 项目类别:
Discovery Grants Program - Individual
Using Structural Systems Biology Modelling to Probe High-Resolution Design Principles of Protein Networks
利用结构系统生物学模型探索蛋白质网络的高分辨率设计原理
- 批准号:
RGPAS-2019-00012 - 财政年份:2020
- 资助金额:
$ 3.57万 - 项目类别:
Discovery Grants Program - Accelerator Supplements
Using Structural Systems Biology Modelling to Probe High-Resolution Design Principles of Protein Networks
利用结构系统生物学模型探索蛋白质网络的高分辨率设计原理
- 批准号:
RGPAS-2019-00012 - 财政年份:2019
- 资助金额:
$ 3.57万 - 项目类别:
Discovery Grants Program - Accelerator Supplements
High-Resolution Modeling in Systems Biology
系统生物学中的高分辨率建模
- 批准号:
CRC-2015-00042 - 财政年份:2019
- 资助金额:
$ 3.57万 - 项目类别:
Canada Research Chairs
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