Computational Tools for Protein Complex Structure Prediction from MS Data
根据 MS 数据预测蛋白质复杂结构的计算工具
基本信息
- 批准号:9978851
- 负责人:
- 金额:$ 11.67万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:
- 资助国家:美国
- 起止时间:至
- 项目状态:未结题
- 来源:
- 关键词:AddressAgreementAlgorithmsAppearanceBenchmarkingBindingBurialCommunitiesComplexComputational TechniqueComputing MethodologiesCryoelectron MicroscopyDataData AnalysesData SetDeuteriumDevelopmentDissociationDockingEntropyExposure toFluorescence Resonance Energy TransferGasesHigh Performance ComputingHybridsHydrogenKineticsLabelLeadLigand BindingLipidsMacromolecular ComplexesMass Spectrum AnalysisMeasurementMeasuresMembrane ProteinsMethodsModelingMolecular ConformationMonitorOhioPatternPhaseProceduresProtein Complex SubunitProtein RegionProteinsQuaternary Protein StructureRNAReactionResearchResolutionResourcesRotationShapesStructural ModelsStructural ProteinStructureSurfaceTechniquesTestingWorkX-Ray Crystallographybasebiomacromoleculecomplex data computerized toolsexperienceexperimental studyflexibilityimprovedinterfacialion mobilitymacromoleculenovelprotein complexprotein structureprotein structure predictionrestraintstoichiometrystructural biologystructured datasupercomputertool
项目摘要
TR&D 5: Project Summary. The proposed Resource for Native Mass Spectrometry Guided Structural Biology
aims to develop advanced MS techniques for the structural characterization of biomacromolecules such as
protein:protein, membrane protein:lipid, and RNA:protein complexes. Experimental development in the resource
will focus on effective separations methods to purify and deliver native proteins to the MS, effective surface
induced dissociation methods for non-covalent interface cleavages and UVPD for covalent fragmentation of
native protein complexes, and measurement of the intact complexes and dissociation products (subcomplexes
and covalent fragments) with ion mobility MS (for conformations and conformational changes e.g., upon ligand
binding) and/or high resolution MS. Valuable structural information about macromolecular complexes will be
obtained. However, there is currently no automated way of generating structural restraints from the MS data,
and those restraints are generally insufficient to generate high accuracy complex structures from the data alone.
In TR&D 5, we are proposing that, in combination with novel computational methods, the restraints from SID and
IM, combined with restraints from established methods such as hydrogen deuterium exchange (HDX) and
covalent labeling (CL), are sufficient for improved macromolecular complex structure prediction. We will develop
tools to automatically extract restraints from experimental MS data and incorporate them into the Rosetta
structure prediction tools to guide protein complex structure prediction. The proposed research is structured into
two main stages.
Aim 1. We will develop computational tools for macromolecular complex structure prediction from solution
measurements that are monitored by MS (H/D exchange and covalent labeling). We will implement quantitative
covalent labeling and HDX exposure constraints into the Rosetta docking algorithm, such that it is driven by
agreement with the exposure pattern of the docked subunits. This aim use complexes as testbeds or will be
applied to predict structures from HDX and CL data for complexes from DBPs 1, 2, 3, 7 and 8
Aim 2. We will develop computational tools for macromolecular complex structure prediction from the surface-
induced dissociation and collision cross sections from ion mobility experiments. We will develop new Rosetta
docking scores that measure the agreement of complex models with the SID and IM CCS data. TR&D 5 is tightly
integrated with the other TR&Ds because it aims to extend the applicability of the developed experimental
methods by tailoring computational methods that allow structural modeling based on the experimental data. This
aim will use SID onset energies, oligomeric products generated, and CCS values to test the procedure and to
predict structures by using data from DBPs 1, 2, 3, 7 and 10.
研发5:项目总结。天然质谱学指导结构生物学的建议资源
旨在开发先进的MS技术来表征生物大分子的结构,如
蛋白质:蛋白质,膜蛋白:脂质,RNA:蛋白质复合体。资源中的实验开发
将重点放在有效的分离方法上,将天然蛋白质纯化并输送到MS,有效的表面
非共价界面裂解的诱导解离方法和共价碎裂的UVPD
天然蛋白质复合体及其完整复合体和解离产物(亚复合体)的测定
和共价片段)具有离子迁移率MS(例如,在配体上的构象和构象变化
结合)和/或高分辨率MS,有关大分子络合物的有价值的结构信息将是
获得。然而,目前还没有从MS数据生成结构约束的自动方式,
这些约束通常不足以仅从数据中生成高精度的复杂结构。
在研发5中,我们提出,结合新的计算方法,SID和SID的约束
IM,结合氢-氚交换(HDX)和现有方法的限制
共价标记(CL),这对于改进的大分子复杂结构预测是足够的。我们将发展
从实验MS数据中自动提取约束并将其合并到Rosetta中的工具
结构预测工具,用于指导蛋白质复杂结构预测。拟议的研究报告的结构如下
主要有两个阶段。
目标1.我们将开发从溶液中预测大分子复杂结构的计算工具
由MS监测的测量(H/D交换和共价标记)。我们将实施量化
Rosetta对接算法中的共价标记和HDX曝光限制,因此它是由
与对接的亚基的曝光图案一致。这一目标使用复合体作为试验床,或者将
用于从HDX和CL数据预测DBP 1、2、3、7和8的络合物的结构
目标2.我们将开发用于从表面预测大分子复杂结构的计算工具-
离子迁移率实验的诱导解离和碰撞截面。我们将开发新的罗塞塔
衡量复杂模型与SID和IM CCS数据一致性的对接分数。R&D 5紧绷
与其他研究与开发相结合,因为它旨在扩大所开发的实验的适用性
方法通过量身定制计算方法,允许基于实验数据的结构建模。这
AIM将使用SID起始能量、生成的寡聚产物和CCS值来测试该程序并
使用DBP 1、2、3、7和10中的数据预测结构。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
数据更新时间:{{ journalArticles.updateTime }}
{{
item.title }}
{{ item.translation_title }}
- DOI:
{{ item.doi }} - 发表时间:
{{ item.publish_year }} - 期刊:
- 影响因子:{{ item.factor }}
- 作者:
{{ item.authors }} - 通讯作者:
{{ item.author }}
数据更新时间:{{ journalArticles.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ monograph.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ sciAawards.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ conferencePapers.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ patent.updateTime }}
Steffen Lindert其他文献
Steffen Lindert的其他文献
{{
item.title }}
{{ item.translation_title }}
- DOI:
{{ item.doi }} - 发表时间:
{{ item.publish_year }} - 期刊:
- 影响因子:{{ item.factor }}
- 作者:
{{ item.authors }} - 通讯作者:
{{ item.author }}
{{ truncateString('Steffen Lindert', 18)}}的其他基金
Molecular models to characterize actions of calcium sensitizing drugs
表征钙增敏药物作用的分子模型
- 批准号:
10307610 - 财政年份:2018
- 资助金额:
$ 11.67万 - 项目类别:
Computational Tools for Protein Complex Structure Prediction from MS Data
根据 MS 数据预测蛋白质复杂结构的计算工具
- 批准号:
10441403 - 财政年份:2018
- 资助金额:
$ 11.67万 - 项目类别:
Computational Tools for Protein Complex Structure Prediction from MS Data
根据 MS 数据预测蛋白质复杂结构的计算工具
- 批准号:
10192753 - 财政年份:2018
- 资助金额:
$ 11.67万 - 项目类别:
Molecular models to characterize actions of calcium sensitizing drugs
表征钙增敏药物作用的分子模型
- 批准号:
10063891 - 财政年份:2018
- 资助金额:
$ 11.67万 - 项目类别:
Rational Drug Design for Chronic Neuronal Damage
针对慢性神经元损伤的合理药物设计
- 批准号:
9550891 - 财政年份:2017
- 资助金额:
$ 11.67万 - 项目类别:
相似海外基金
A study for cross borders Indonesian nurses and care workers: Case of Japan-Indonesia Economic Partnership Agreement
针对跨境印度尼西亚护士和护理人员的研究:日本-印度尼西亚经济伙伴关系协定的案例
- 批准号:
22KJ0334 - 财政年份:2023
- 资助金额:
$ 11.67万 - 项目类别:
Grant-in-Aid for JSPS Fellows
NSF-NOAA Interagency Agreement (IAA) for the Global Oscillations Network Group (GONG)
NSF-NOAA 全球振荡网络组 (GONG) 机构间协议 (IAA)
- 批准号:
2410236 - 财政年份:2023
- 资助金额:
$ 11.67万 - 项目类别:
Cooperative Agreement
Conditions for U.S. Agreement on the Closure of Contested Overseas Bases: Relations of Threat, Alliance and Base Alternatives
美国关于关闭有争议的海外基地协议的条件:威胁、联盟和基地替代方案的关系
- 批准号:
23K18762 - 财政年份:2023
- 资助金额:
$ 11.67万 - 项目类别:
Grant-in-Aid for Research Activity Start-up
MSI Smart Manufacturing Data Hub – Open Calls Grant Funding Agreement
MSI 智能制造数据中心 – 公开征集赠款资助协议
- 批准号:
900240 - 财政年份:2023
- 资助金额:
$ 11.67万 - 项目类别:
Collaborative R&D
Challenges of the Paris Agreement Exposed by the Energy Shift by External Factors: The Case of Renewable Energy Policies in Japan, the U.S., and the EU
外部因素导致的能源转移对《巴黎协定》的挑战:以日本、美国和欧盟的可再生能源政策为例
- 批准号:
23H00770 - 财政年份:2023
- 资助金额:
$ 11.67万 - 项目类别:
Grant-in-Aid for Scientific Research (B)
Continuation of Cooperative Agreement between U.S. Food and Drug Administration and S.C. Department of Health and Environmental Control (DHEC) for MFRPS Maintenance.
美国食品和药物管理局与南卡罗来纳州健康与环境控制部 (DHEC) 继续签订 MFRPS 维护合作协议。
- 批准号:
10829529 - 财政年份:2023
- 资助金额:
$ 11.67万 - 项目类别:
National Ecological Observatory Network Governing Cooperative Agreement
国家生态观测站网络治理合作协议
- 批准号:
2346114 - 财政年份:2023
- 资助金额:
$ 11.67万 - 项目类别:
Cooperative Agreement
The Kansas Department of Agriculture's Flexible Funding Model Cooperative Agreement for MFRPS Maintenance, FPTF, and Special Project.
堪萨斯州农业部针对 MFRPS 维护、FPTF 和特别项目的灵活资助模式合作协议。
- 批准号:
10828588 - 财政年份:2023
- 资助金额:
$ 11.67万 - 项目类别:
Robust approaches for the analysis of agreement between clinical measurements: development of guidance and software tools for researchers
分析临床测量之间一致性的稳健方法:为研究人员开发指南和软件工具
- 批准号:
MR/X029301/1 - 财政年份:2023
- 资助金额:
$ 11.67万 - 项目类别:
Research Grant
Doctoral Dissertation Research: Linguistic transfer in a contact variety of Spanish: Gender agreement production and attitudes
博士论文研究:西班牙语接触变体中的语言迁移:性别协议的产生和态度
- 批准号:
2234506 - 财政年份:2023
- 资助金额:
$ 11.67万 - 项目类别:
Standard Grant