Building protein structure models for intermediate resolution cryo-electron microscopy maps
Building protein structure models for intermediate resolution cryo-electron microscopy maps
批准号:
10670831
负责人:
Daisuke Kihara
金额:
$30.54万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2020
资助国家:
美国
项目状态:
已结题
起止时间:
2020-09-20 至 2024-07-31
关键词:
3-DimensionalAlgorithmsAmino AcidsAreaBiologicalCellsChimera organismCodeCommunicationCommunitiesComplementComputer softwareComputing MethodologiesCryoelectron MicroscopyDNADataDevelopmentDiseaseElectron MicroscopyGoalsGrainHumanInterventionInvestigationKnowledgeLigand BindingMapsMethodologyMethodsModelingMolecularMolecular ConformationMultiprotein ComplexesNaturePlug-inPositioning AttributePreparationProtein RegionProteinsPublishingRNAResearchResearch PersonnelResolutionSamplingSource CodeStructureTechniquesThree-Dimensional ImageThree-dimensional analysisVisualization softwareX-Ray Crystallographycomputerized toolsdata acquisitiondeep learningdensitydetection methodgraphical user interfaceimage processingimprovedmachine learning methodmacromolecular assemblymacromoleculemodel buildingnovelprogramsprotein functionprotein structureprotein structure predictionrepositorysoftware developmentstructural biologythree dimensional structuretool
中文摘要
点击翻译按钮获取中文摘要
英文摘要
Project Summary
Cryo-electron microscopy (cryo-EM) is an emerging technique in structural biology, which is capable of
determining three-dimensional (3D) structures of biological macromolecules. Compared to conventional
structural biology techniques, such as X-ray crystallography and NMR, a major advantage of cryo-EM is its
ability to solve large macromolecular assemblies. Moreover, recent technical breakthroughs in cryo-EM have
enabled determination of 3D structures at nearly atomic-level resolutions. Cryo-EM will undoubtedly become a
method of central importance in structural biology in the next decade. With the rapid accumulation of cryo-EM
structure data, it has become crucial to develop computational methods that can effectively build and extract
3D structures of biological macromolecules from EM maps. The goal of this project is to develop computational
methods for modeling both global and local structures and for interpreting 3D structures embedded in EM
maps of around 4 Å to medium-resolution. Recently, we have developed a new de novo protein structure
modeling method, MAINMAST, which can model protein structures from an EM density map without using
existing template or fragment structures on the map. Based on the successful development of MAINMAST, we
further extend the capability of MAINMAST toward more accurate modeling and for multiple-chain modeling. In
addition, we will also develop novel modeling methods for medium-resolution EM maps, which combine a
coarse-grained protein structure modeling technique, methods in protein structure prediction, and a low-
resolution image processing approach with deep learning, a state-of-the-art powerful machine learning method.
The proposed project capitalizes on the tremendous efforts and progress made in structural determination with
cryo-EM by developing computational tools that allow researchers to perform efficient and reliable structure
analyses for 3D EM density maps. The project will greatly facilitate investigation into the molecular
mechanisms of macromolecule function by providing an efficient means of 3D structure modeling.
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Building protein structure models for intermediate resolution cryo-electron microscopy maps
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批准号:10405197
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项目类别:
-
资助金额:$23.25万
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财政年份:2020
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负责人:Daisuke Kihara
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依托单位:
Building protein structure models for intermediate resolution cryo-electron microscopy maps
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批准号:10794660
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项目类别:
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资助金额:$16.87万
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财政年份:2020
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负责人:Daisuke Kihara
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依托单位:
Building protein structure models for intermediate resolution cryo-electron microscopy maps
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批准号:10266083
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项目类别:
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资助金额:$30.55万
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财政年份:2020
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负责人:Daisuke Kihara
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依托单位:
Building protein structure models for intermediate resolution cryo-electron microscopy maps
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批准号:10462711
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项目类别:
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资助金额:$30.55万
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财政年份:2020
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负责人:Daisuke Kihara
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依托单位:
Identification of protein-metabolite interactome.
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批准号:8477213
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项目类别:
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资助金额:$26.99万
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财政年份:2011
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负责人:Daisuke Kihara
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依托单位:
Identification of protein-metabolite interactome.
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批准号:8324598
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项目类别:
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资助金额:$28.1万
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财政年份:2011
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负责人:Daisuke Kihara
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依托单位:
Identification of protein-metabolite interactome.
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批准号:8665991
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项目类别:
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资助金额:$27.83万
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财政年份:2011
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负责人:Daisuke Kihara
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依托单位:
Identification of protein-metabolite interactome.
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批准号:8086786
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项目类别:
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资助金额:$27.97万
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财政年份:2011
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负责人:Daisuke Kihara
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依托单位:
PROTEIN-PROTEIN DOCKING USING LOCAL SHAPE INVARIANTS
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批准号:8171888
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项目类别:
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资助金额:$0.11万
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财政年份:2010
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负责人:Daisuke Kihara
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依托单位:
PROTEIN-PROTEIN DOCKING USING LOCAL SHAPE INVARIANTS
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批准号:7956349
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项目类别:
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资助金额:$0.08万
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财政年份:2009
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负责人:Daisuke Kihara
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依托单位:
Surface Shape Based Screening of Large Protein Databases
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批准号:7125028
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项目类别:
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资助金额:$29.65万
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财政年份:2005
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负责人:Daisuke Kihara
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依托单位:
Surface Shape Based Screening of Large Protein Databases
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批准号:7683794
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项目类别:
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资助金额:$30.34万
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财政年份:2005
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负责人:Daisuke Kihara
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依托单位:
Surface Shape Based Screening of Large Protein Databases
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批准号:7491196
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项目类别:
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资助金额:$29.52万
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财政年份:2005
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负责人:Daisuke Kihara
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依托单位:
Surface Shape Based Screening of Large Protein Databases
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批准号:6960633
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项目类别:
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资助金额:$29.54万
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财政年份:2005
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负责人:Daisuke Kihara
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依托单位:
Surface Shape Based Screening of Large Protein Databases
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批准号:7274864
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项目类别:
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资助金额:$29.58万
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财政年份:2005
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负责人:Daisuke Kihara
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依托单位:
海外基金