SBIR Phase I: Developing a Platform for Multiplexed Drug Profiling Using Yeast Synthetic Agglutination

SBIR 第一阶段：开发利用酵母合成凝集进行多重药物分析的平台

• 批准号: 1819398
• 负责人: David Younger
• 金额: $ 22.5万
• 依托单位: A-Alpha Bio, Inc.
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-07-01 至 2019-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1819398&HistoricalAwards=false
• 关键词: SBIR; Phase; Developing; Platform; Multiplexed

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) project will be to develop a preclinical drug characterization platform capable of profiling the effect of a drug candidate on whole protein-protein interaction (PPI) networks. PPIs play a pivotal role in most diseases, and are considered high-impact therapeutic targets for cancers, autoimmune diseases, infectious diseases, and more. Over 40 clinically relevant PPIs have been disrupted successfully with small molecules, and several have entered clinical trials. One recently approved cancer drug, Venetoclax, is expected to reach $2.2B in sales by 2020. Despite the enormous clinical and commercial potential of PPI disrupting drugs, preclinical characterization remains a major challenge. Pharmaceutical companies are limited by slow and laborious techniques to measure protein interactions that require each protein to be purified, and each PPI to be measured separately. As a result, only a small subset of relevant interactions are tested during preclinical drug development, which leads to a high incidence of failure during clinical trials. The proposed platform for PPI network characterization is expected to have a major commercial and societal impact by enabling more thorough preclinical screening of PPI inhibiting drugs, reducing the overall cost and time associated with drug development.This SBIR Phase I project proposes to develop and commercialize a novel platform for screening PPI disrupting drugs that provides quantitative accuracy, enables simultaneous characterization of whole PPI networks, and eliminates the need for protein purification. This platform combines the throughput of a cell-based assay with the accuracy of a bioanalytical technique by linking yeast haploid mating efficiency to the affinity of proteins displayed on the cells' surfaces. Preliminary results demonstrate that next generation sequencing of diploid cells may be used to accurately measure many PPI strengths simultaneously. The goal of this project is to demonstrate that the proposed platform can correctly recapitulate whole disease-relevant PPI networks and accurately characterize well-studied inhibitors in a format that is compatible with existing high-throughput screening workflows. To demonstrate feasibility, the well-studied BCL2 PPI network, which contains unstable proteins and considerable complexity, will be analyzed to identify each pairwise PPI and compared to known interactions from the literature. The yeast strains and assay parameters will then be optimized for screening water insoluble small molecule drugs and 96-well plate compatibility. The ultimate goal of this project is to establish a new platform technology for the preclinical characterization of PPI inhibiting drug candidates.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

这个小型企业创新研究(SBIR)项目的更广泛的影响/商业潜力将是开发一个临床前药物表征平台，能够描述候选药物对整个蛋白质-蛋白质相互作用(PPI)网络的影响。PPI在大多数疾病中发挥着关键作用，被认为是癌症、自身免疫性疾病、传染病等的高影响治疗靶点。超过40个临床相关的PPI已经成功地被小分子干扰，其中几个已经进入临床试验。最近获批的一种抗癌药物Venetclax预计到2020年销售额将达到22亿美元。尽管PPI干扰药物具有巨大的临床和商业潜力，但临床前表征仍然是一个重大挑战。制药公司在测量蛋白质相互作用方面受到缓慢和繁琐技术的限制，这些技术需要对每种蛋白质进行纯化，并分别测量每种蛋白质的PPI。结果，在临床前药物开发期间，只测试了相关相互作用的一小部分，这导致了临床试验期间的高失败率。拟议的PPI网络表征平台有望通过实现更彻底的PPI抑制药物的临床前筛选，减少与药物开发相关的总体成本和时间，从而产生重大的商业和社会影响。这个SBIR第一阶段项目建议开发并商业化一种新的平台，用于筛选PPI干扰药物，提供定量准确性，使整个PPI网络能够同时表征，并消除对蛋白质纯化的需要。该平台通过将酵母单倍体交配效率与显示在细胞表面的蛋白质的亲和力联系起来，将基于细胞的分析的吞吐量与生物分析技术的准确性结合在一起。初步结果表明，二倍体细胞的下一代测序可以用来同时准确地测量许多PPI强度。该项目的目标是证明建议的平台可以正确概括整个与疾病相关的PPI网络，并以与现有高通量筛选工作流程兼容的格式准确地表征经过充分研究的抑制剂。为了证明可行性，将分析研究充分的BCL2 PPI网络，它包含不稳定的蛋白质和相当复杂的蛋白质，以识别每个成对的PPI，并与文献中的已知相互作用进行比较。然后对酵母菌株和检测参数进行优化，以筛选水不溶性小分子药物和96孔板的兼容性。该项目的最终目标是建立一种新的平台技术，用于PPI抑制候选药物的临床前表征。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。