High-Throughput Assessment of De Novo Protein Design: Generation of Molecular Probes for Guanine Exchange Factors
High-Throughput Assessment of De Novo Protein Design: Generation of Molecular Probes for Guanine Exchange Factors
批准号:
9911096
负责人:
David Thieker
金额:
$6.53万
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:
2020-01-09 至 2021-01-08
关键词:
AffinityAmino AcidsBindingBinding SitesBiological ProcessBiological SciencesBiosensorCancer BiologyCell ProliferationCellsChimeric ProteinsCommunitiesComplexCrystallizationDataDevelopmentDiseaseEngineeringEnvironmentEquilibriumEvaluationFluorescenceGenerationsGenesGoalsGuanineGuanine Nucleotide Exchange FactorsGuanosine Triphosphate PhosphohydrolasesIn VitroKnowledgeLearningLinkMalignant NeoplasmsMethodsMicroinjectionsMolecularMolecular ProbesMutationNatureOligonucleotidesOutcomePlayProceduresProcessProtein EngineeringProteinsProtocols documentationRampReagentReportingReproducibilityResearchRoleSample SizeSamplingScientistSideSignal TransductionStructural ProteinTechniquesTechnologyTestingTimeWeightYeastsbasebiophysical modeldesignfluorophoregene synthesishigh throughput screeninghigh throughput technologyimprovedin silicoinhibitor/antagonistinterestmodel designnanomolarnovelprocess optimizationprogramsprotein complexprotein protein interactionprotein structureprotein structure functionscreeningsmall moleculesmall molecule inhibitortherapeutic targettool
中文摘要
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英文摘要
Knowledge of the underlying principles of protein-protein interactions facilitates the design of
proteins with novel functions that remain unobserved in nature and create new opportunities for
scientists to dissect the molecular basis for diseases. Although significant advancements in the
field have been made, evaluation of the computational design process by expressing proteins in
vitro has been limited to small sample sizes due to constraints associated with gene synthesis.
Recent advances in the field of oligonucleotide synthesis have enabled the high-throughput
screening of designs with yeast display. We will harness this technology to assess new methods
for packing amino acids at protein interfaces and to determine ideal score term targets for
designed models. During this process, we will develop proteins that inhibit guanine exchange
factors (GEFs), which are critical for cellular proliferation and have thereby garnered significant
interest as therapeutic targets for cancer. We also aim to develop novel biosensors that are
capable of reporting GEF activation by engineering a binding site into the SnapTag and HaloTag
constructs. These results are expected to have an important positive impact for the field of
protein engineering, ultimately providing new opportunities for the development of reagents that
enable the scientific community to advance our understanding of biological processes.
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