Platform for Massively Parallel Selection of Aptamer Ligands

描述(申请人提供)：适配子已经成为目前可用的最有前途的药物先导和诊断配体之一。适配子是源于大型组合文库的核酸配体，通常具有与抗体竞争的亲和力和特异性，但它们在治疗和诊断应用方面有许多显著的优势。不幸的是，目前的适体开发过程是低通量和繁琐的，因为DNA或RNA文库只针对一个靶点进行筛选。该项目专注于开发方法和工具，以允许同时对数千种蛋白质阵列进行大型组合筛选。这样的蛋白质阵列越来越容易获得，其含量具有很高的治疗和诊断价值。实现这一点的关键是制定必要的步骤，以破译哪些适配子(一旦选定)对应于哪个靶标。所谓的“下一代”测序将极大地促进拟议的过程以及在该项目中开发的必要的“序列标记”方法。一旦我们的大规模并行适配子选择过程被开发出来，我们将能够在大约一周内对数千种蛋白质产生高亲和力的适配子配体。然后，开发的配体将被进一步表征为有希望的候选药物、诊断标签和其他研究应用。与公共健康相关：美国联邦药品管理局最近的一份白皮书发现，将新药推向市场存在一个关键问题，FDA将其描述为“流水线问题”。根据这份报告和其他报告，制药公司在任何一种药物的发现、开发和批准上平均花费8-17亿美元。更糟糕的是，从候选药物的初始测试到最终上市可能需要长达20年的时间。因此，FDA的报告强烈敦促纳入新的定量预测工具，以在药物开发过程的早期评估新药先导和诊断配体的安全性和有效性。该项目提供了针对数千个潜在的“可药物”感兴趣的蛋白质靶标的DNA或RNA‘适配子’的巨大组合库的并行开发和评估。如果成功，这项技术可以提供超高的药物先导和诊断配体的产量。

DESCRIPTION (provided by applicant): Aptamers have emerged as one of the most promising classes of drug leads and diagnostic ligands presently available. Aptamers, nucleic acid ligands derived from large combinatorial libraries, typically have affinities and specificities that rival antibodies, yet they have a number of significant advantages for therapeutic and diagnostic applications. Unfortunately, the present process for aptamer development is low-throughput and tedious as DNA or RNA libraries are screened against only a single target. This project focuses on developing the methods and tools to allow large combinatorial to be screened against arrays of thousands of proteins simultaneously. Such protein arrays are increasing available with content of high therapeutic and diagnostic value. The key to achieving this is developing the necessary steps to decipher which aptamers (once selected) correspond to which target. So-called "next generation" sequencing will greatly enable the proposed process coupled with the necessary "sequence- tagging" approaches developed in this project. Once our massively parallel aptamer selection process is developed, we will be in a position to create high affinity aptamer ligands to thousands of proteins in roughly 1 week. The developed ligands will can then be further characterized as promising drug candidates, diagnostic labels, and other research applications. PUBLIC HEALTH RELEVANCE: A recent white paper by the US Federal Drug Administration finds that there exists a critical problem in bringing novel drugs to market, something the FDA describes as the 'pipeline problem'. According to this and other reports drug companies spend an average of $0.8-1.7 billion dollars on the discovery, development and approval of any one individual drug. To make matters worse, the time from the initial testing of a drug candidate and to its eventual marketing can take up to 20 years. Thus, the FDA report strongly urges the incorporation of novel quantitative predictive tools for the assessment of safety and efficacy of new drug leads and diagnostic ligands early in the drug development process. This project provides for the parallel development and evaluation of enormous combinatorial libraries of DNA or RNA 'aptamers' against of thousands of protein targets of potential 'druggable' interest. If successful, the technology could provide for unprecented throughput of drug leads and diagnostic ligands.