Designing Affinity and Specificity at Protein Interfaces
Designing Affinity and Specificity at Protein Interfaces
批准号:
7616465
负责人:
BRIAN A KUHLMAN
金额:
$21.95万
依托单位国家:
美国
项目类别:
财政年份:
2005
资助国家:
美国
项目状态:
已结题
起止时间:
2005-05-01 至 2011-04-30
关键词:
AffinityAlgorithmsAmino Acid SequenceAmino AcidsAreaBindingBiological AssayBiosensorCell physiologyCellular biologyComplexComputersComputing MethodologiesCoupledDevelopmentEnsureEventFellowshipGTP-Binding ProteinsGoalsModelingMolecular ConformationMutationPathway interactionsProceduresProtein BindingProteinsProtocols documentationQuantum MechanicsResearchResearch PersonnelScoring MethodScreening procedureSideSignal TransductionSignal Transduction PathwaySignaling ProteinSpecificityStructureSurfaceTechniquesTestingTorsionUbiquitin-Conjugating EnzymesUbiquitinationVertebral columnbasecomputer programdesignflexibilityinterestknowledge basemodel designmolecular mechanicsnovelprogramsprotein protein interactionprotein structuresimulationsuccesstherapeutic proteintoolubiquitin ligase
中文摘要
描述(由申请人提供):蛋白质-蛋白质相互作用对几乎所有细胞过程都是必不可少的。合理操纵这些相互作用的能力将为研究细胞生物学和创造新的蛋白质疗法创造新的工具。本研究的目的是开发和测试计算机协议的蛋白质界面设计,包括全骨干和侧链的灵活性。我们将在界面设计中的两个重要问题上测试这些协议:增强自然发生的相互作用的结合亲和力和改变信号蛋白的结合特异性。为了实现这一目标,我们将利用计算机程序,罗塞塔设计,我们开发的同时优化氨基酸序列和主链结构的目标结构。令人鼓舞的是,该方案以前已被用于设计具有原子水平精度的新型蛋白质结构。一些证据表明,当在模拟过程中考虑更多侧链构象时,蛋白质设计模拟的准确性会增加。为了允许侧链扭转角的完全灵活性,我们将使用蒙特卡罗最小化程序,其中离散转子替换之后是基于梯度的侧链扭转角最小化。我们将通过设计两组模型蛋白之间的功能正交结合相互作用来测试柔性侧链模型:泛素化途径的蛋白质和参与g蛋白信号传导的蛋白质。我们将通过设计通过增加与伴侣分子的有利接触数量来增强结合亲和力的蛋白质延伸来测试我们的具有柔性骨架的蛋白质设计模型。具体来说,我们将在泛素偶联酶UbcH7的n端加入额外的残基,预计这些残基将增强其与天然结合伙伴泛素连接酶E6AP的结合亲和力。结合亲和力将通过各种生物物理技术确定,活性测定将用于确定重新设计的蛋白质是否作为活性复合物结合。
英文摘要
DESCRIPTION (provided by applicant): Protein-protein interactions are essential to almost all cellular processes. The ability to rationally manipulate these interactions would allow for the creation of new tools for studying cell biology and the creation of new protein therapeutics. The objective of this research is to develop and test computer protocols for protein interface design that include full backbone and side chain flexibility. We will test these protocols on two important problems in interface design: enhancing the binding affinity of naturally occurring interactions and changing the binding specificity of signaling proteins. To achieve this objective we will make use of a computer program, Rosetta Design, that we developed for simultaneously optimizing the amino acid sequence and backbone conformation of a target structure. Encouragingly, this protocol has been previously used to design a novel protein structure with atomic level accuracy. Several lines of evidence suggest that the accuracy of protein design simulations increase when more side chain conformations are considered during the simulation. To allow complete flexibility in side chain torsion angles we will use a Monte Carlo minimization procedure in which discrete rotamer substitutions are followed by gradient-based minimization of side chain torsion angles. We will test the flexible side chain model by designing functionally orthogonal binding interactions between two sets of model proteins: proteins from the ubiquitination pathway and proteins involved in G-protein signaling. We will test our model for protein design with a flexible backbone by designing protein extensions that enhance binding affinity by increasing the number of favorable contacts with the partner molecule. Specifically, we will incorporate additional residues off the N-terminus of the ubiquitin conjugating enzyme, UbcH7, that are predicted to enhance its binding affinity for its natural binding partner, the ubiquitin ligase E6AP. Binding affinities will be determined with various biophysical techniques and activity assays will be used to determine if the redesigned proteins bind as an active complex.
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Computational Design of Protein Structures and Complexes
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批准号:10433948
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项目类别:
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资助金额:$79.13万
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财政年份:2019
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负责人:BRIAN A KUHLMAN
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批准号:10119999
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财政年份:2019
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批准号:10647739
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负责人:BRIAN A KUHLMAN
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依托单位:
GPU workstation for deep learning-based protein design and cryo-EM data processing
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资助金额:$4.8万
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资助金额:$29.92万
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财政年份:2015
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负责人:BRIAN A KUHLMAN
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依托单位:
Computational Methods for Requirement-Driven Protein Design
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批准号:9549177
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项目类别:
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资助金额:$14.99万
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财政年份:2015
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负责人:BRIAN A KUHLMAN
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依托单位:
Design of Genetically Encoded Photoactivatable Proteins
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项目类别:
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负责人:BRIAN A KUHLMAN
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依托单位:
Design of Genetically Encoded Photoactivatable Proteins
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项目类别:
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资助金额:$28.28万
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财政年份:2010
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负责人:BRIAN A KUHLMAN
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依托单位:
Design of Genetically Encoded Photoactivatable Proteins
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项目类别:
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资助金额:$27.29万
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财政年份:2010
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负责人:BRIAN A KUHLMAN
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依托单位:
Design of Genetically Encoded Photoactivatable Proteins
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批准号:8053307
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项目类别:
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资助金额:$28.28万
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财政年份:2010
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负责人:BRIAN A KUHLMAN
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依托单位:
DE NOVO DESIGN OF A BETA SHEET PROTEIN
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批准号:7723264
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项目类别:
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资助金额:$0.05万
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财政年份:2008
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负责人:BRIAN A KUHLMAN
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依托单位:
DE NOVO DESIGN OF A BETA SHEET PROTEIN
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项目类别:
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财政年份:2007
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负责人:BRIAN A KUHLMAN
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依托单位:
Computational Design of Protein-Protein Interactions
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批准号:8691870
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项目类别:
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资助金额:$27.04万
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财政年份:2005
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负责人:BRIAN A KUHLMAN
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依托单位:
Designing Affinity and Specificity at Protein Interfaces
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批准号:7414563
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项目类别:
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资助金额:$21.95万
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财政年份:2005
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负责人:BRIAN A KUHLMAN
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依托单位:
ROSETTA An Integrated Protein Structure Modeling Suite
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项目类别:
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资助金额:$64.12万
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财政年份:2005
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负责人:BRIAN A KUHLMAN
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依托单位:
Rosetta: An Integrated Macromolecular Modeling Suite
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负责人:BRIAN A KUHLMAN
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依托单位:
海外基金