HIGH THROUGHPUT SELECTION OF FABS TO THE HUMAN PROTEOME

高通量选择人类蛋白质组 FABS

• 批准号: 6017904
• 负责人: ROBERT F BALINT
• 金额: $ 10万
• 依托单位: PANORAMA RESEARCH, INC.
• 依托单位国家: 美国
• 财政年份: 1999
• 资助国家: 美国
• 起止时间: 1999-09-01 至 2000-02-29
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6017904
• 关键词: beta lactamase; genetic library; genetic screening; immunoglobulin structure; molecular cloning; nucleic acid hybridization; nucleic acid probes; phenotype; protein folding; protein protein interaction; protein structure; protein structure function; technology /technique development; transfection /expression vector

Within a few years, all of the 70,000-I 00,000 protein coding sequences in the human genome will become available, providing an enormously- valuable resource for the discovery of new pharmacological targets. However, the realization of that value will require new methods for high- throughput identification and functional evaluation of new targets. The high-throughput potential of current methods for rapid antibody isolation is severely limited by the need for target purification. Cell-based selection methods, in which target and antibody are expressed in the same cell and target-antibody interaction produces a selectable phenotype, may be the only way to circumvent this bottleneck. The goal of the present proposal is to adapt a proprietary high-throughput cellular selection system, based on interaction-dependent beta-lactamase, for the rapid isolation of specific, high-affinity antibody Fab fragments to as much of the human proteome as possible for use in the functional evaluation of new pharmacological targets, and as leads for the development of new drugs and diagnostics. In a companion proposal we will use essentially the same methods to discover interaction networks among the domains of the human proteome. Such interactions will be expected to provide a rich source of potential new targets for pharmaceutical intervention in disease. PROPOSED COMMERCIAL APPLICATIONS: The primary goal of this work is to develop new technologies to accelerate the process for identifying and evaluating new pharmaceutical targets from genomics data.

在未来几年内，人类基因组中的7万到10万个蛋白质编码序列将全部可用，这将为发现新的药理靶点提供极其宝贵的资源。然而，实现这一价值将需要新的方法来进行高通量鉴定和新靶标的功能评估。当前快速抗体分离方法的高通量潜力受到目标纯化需求的严重限制。基于细胞的选择方法，其中靶标和抗体在同一细胞中表达，靶标-抗体相互作用产生可选择的表型，可能是绕过这一瓶颈的唯一途径。本提案的目标是采用一种专有的高通量细胞选择系统，基于相互作用依赖性β -内酰胺酶，用于快速分离特异性的高亲和力抗体Fab片段，尽可能多地用于新的药理靶点的功能评估，并作为开发新药和诊断的先导。在一项配套提案中，我们将使用本质上相同的方法来发现人类蛋白质组结构域之间的相互作用网络。这种相互作用有望为药物干预疾病提供丰富的潜在新靶点。建议的商业应用：这项工作的主要目标是开发新技术，以加速从基因组学数据中识别和评估新的药物靶点的过程。