High-throughput Identification of Membrane Protein MAbs
膜蛋白单克隆抗体的高通量鉴定
基本信息
- 批准号:8831071
- 负责人:
- 金额:$ 22.48万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2015
- 资助国家:美国
- 起止时间:2015-02-01 至 2016-06-30
- 项目状态:已结题
- 来源:
- 关键词:AbbreviationsBiomedical ResearchCell Surface ProteinsCell membraneCell surfaceCellsComplementDevelopmentDiagnosticDiagnostics ResearchEpitopesExhibitsFDA approvedGoalsHumanHuman Cell LineImmunizationIndustryLibrariesMembraneMembrane ProteinsMethodsMolecularMolecular ConformationMonoclonal AntibodiesMutationNutrientOrphanPerformancePhage DisplayPharmaceutical PreparationsPhasePlasmidsProtein ArrayProteinsProteomePublic HealthQualifyingReagentReproducibilityServicesSignal TransductionSourceSpecificityStaining methodStainsSurfaceSystemTechnologyTestingTherapeuticTherapeutic AgentsTherapeutic Monoclonal AntibodiesTimeTissuesUnited States National Institutes of Healthcell typecommercial applicationhuman diseasenovel strategiesprotein expressionpublic health relevanceresearch studyscreeningsuccesstherapeutic developmenttrafficking
项目摘要
DESCRIPTION (provided by applicant): Membrane proteins control the flow of information, nutrients, and signals through the cell membrane, and are the targets for more than 40% of FDA-approved drugs. Monoclonal antibodies (MAbs) that target membrane proteins can be exceptionally useful in research, diagnostic, and therapeutic applications, but for most membrane proteins there are no MAbs that recognize the native protein on the cell surface. The need for such MAbs has been recognized by industry and the NIH, but efforts to identify such MAbs are limited by the difficulty in expressing and purifying membrane proteins in exogenous systems and by conventional MAb isolation strategies that typically focus on one target at a time. A novel approach to identify membrane protein MAbs in a high-throughput manner is needed to derive MAbs against the entire human membrane proteome. Here we propose a platform technology that can be used to rapidly isolate MAbs against structurally-intact membrane proteins for therapeutic development, diagnostics, and biomedical research.
描述(由申请人提供):膜蛋白控制信息、营养物质和信号通过细胞膜的流动,并且是超过40%的FDA批准药物的靶点。靶向膜蛋白的单克隆抗体(MAb)在研究、诊断和治疗应用中特别有用,但是对于大多数膜蛋白,没有识别细胞表面上的天然蛋白的MAb。工业界和NIH已经认识到对这种单克隆抗体的需求,但是鉴定这种单克隆抗体的努力受到在外源系统中表达和纯化膜蛋白的困难以及通常一次集中于一个靶标的常规单克隆抗体分离策略的限制。需要一种以高通量方式鉴定膜蛋白单克隆抗体的新方法来衍生针对整个人类膜蛋白质组的单克隆抗体。在这里,我们提出了一个平台技术,可用于快速分离单克隆抗体对结构完整的膜蛋白的治疗开发,诊断和生物医学研究。
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)
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Benjamin Jacob Doranz其他文献
Benjamin Jacob Doranz的其他文献
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{{ truncateString('Benjamin Jacob Doranz', 18)}}的其他基金
Identifying Regulators of Cellular Aging that can Prevent Alzheimer's Disease
识别可以预防阿尔茨海默病的细胞衰老调节因子
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10624244 - 财政年份:2022
- 资助金额:
$ 22.48万 - 项目类别:
Identifying Regulators of Cellular Aging that can Prevent Alzheimer's Disease
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10383454 - 财政年份:2022
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$ 22.48万 - 项目类别:
Identifying New Immunomodulatory Targets for Alzheimers and Other Neurodegenerative Diseases
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9766179 - 财政年份:2018
- 资助金额:
$ 22.48万 - 项目类别:
Development of CB1 Monoclonal Antibodies for Treating NASH
治疗 NASH 的 CB1 单克隆抗体的开发
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9918931 - 财政年份:2018
- 资助金额:
$ 22.48万 - 项目类别:
Next Generation Specificity Screening for Biotherapeutics using an Extracellular Proteome Array
使用细胞外蛋白质组阵列进行下一代生物治疗药物特异性筛选
- 批准号:
10206171 - 财政年份:2015
- 资助金额:
$ 22.48万 - 项目类别:
Next Generation Specificity Screening for Biotherapeutics using an Extracellular Proteome Array
使用细胞外蛋白质组阵列进行下一代生物治疗药物特异性筛选
- 批准号:
10077411 - 财政年份:2015
- 资助金额:
$ 22.48万 - 项目类别:
Next Generation Specificity Screening for Biotherapeutics using an Extracellular Proteome Array
使用细胞外蛋白质组阵列进行下一代生物治疗药物特异性筛选
- 批准号:
10438827 - 财政年份:2015
- 资助金额:
$ 22.48万 - 项目类别:
Phage Display Isolation of Antibodies against Antigenically Conserved Membrane Pr
抗抗原保守膜抗体的噬菌体展示分离
- 批准号:
8309899 - 财政年份:2012
- 资助金额:
$ 22.48万 - 项目类别:
Engineering Stable, Soluble, and Trimeric HIV gp140 by Paired Cys Scanning
通过配对半胱氨酸扫描工程设计稳定、可溶和三聚体 HIV gp140
- 批准号:
8404028 - 财政年份:2012
- 资助金额:
$ 22.48万 - 项目类别:
Engineering Stable, Soluble, and Trimeric HIV gp140 by Paired Cys Scanning
通过配对半胱氨酸扫描工程设计稳定、可溶和三聚体 HIV gp140
- 批准号:
8507144 - 财政年份:2012
- 资助金额:
$ 22.48万 - 项目类别:
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