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An integrated pipeline for next-generation protein interactomics

An integrated pipeline for next-generation protein interactomics
下一代蛋白质相互作用组学的集成管道
批准号:
10061613
负责人:
John Paul LaCava
金额:
$50.29万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2017
资助国家:
美国
项目状态:
已结题
起止时间:
2017-12-01 至 2022-11-30

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Project Summary Proteins are the chief effectors of cellular processes. Within the context of the living cell, proteins form networks of interactions to exert their functions through both stable and transient macromolecular complexes. These protein-protein interactions (PPIs), and interactions with other biomolecules, constitute the interactome of a cell. Alterations in proteins, including changes to protein length, amino acid sequence, expression level, and subcellular localization, can lead to the formation of altered protein interaction networks that cause cellular dysfunction and disease. Therefore, to understand molecular and cellular function and dysfunction, to understand health and disease, we must understand interactomes, creating a need for methods that detect and dissect interactomes and any such alterations. This project will significantly advance a proof-of-concept method to produce a mature platform technology aimed at revealing the compositions of interactomes and behaviors of PPIs at previously unrealized depth and accuracy. The approach taken is akin to a crystallographic screen, except applied to the affinity capture of endogenous protein complexes, optimizing sample preparation in conjunction with initial characterization by mass spectrometry. This project will demonstrate the application of the platform beyond detecting protein interactions, to include biochemical and structural characterization of macromolecular complexes (among other possibilities). Three Aims, composed of an innovative synthesis of methods and technologies, will permit us to achieve our goals: we will (1) optimize access to interactomes, (2) preserve interactomes for bioanalytical assays, and (3) interpret interactomes aided by computational tools. The knowledge generated will improve success rates in affinity capture experimental design and find applications in basic, biomedical, and biotechnology research, from protein complex discovery and characterization, to sample storage, basic and clinical assay development, and industrial engineering.
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  • 项目类别:
  • 资助金额:
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  • 财政年份:
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  • 负责人:
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  • 依托单位:
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  • 项目类别:
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  • 批准号:
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  • 项目类别:
  • 资助金额:
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  • 财政年份:
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