A high-throughput platform for crystallography-based fragment screening

项目总结/摘要 基于片段的药物发现（FBDD）是一种广泛应用于制药行业的药物发现方法。 靶向新候选药物的分子的新设计。FBDD允许更有效地探索 与高通量筛选相比，化学空间具有更高的命中率，并且这可以具有显著的 在早期药物发现和挑战性或“非药物化”目标的情况下的效果。FBDD导致了 约30种新药进入临床试验，2种已进入市场。FBDD还可用于 发现和开发新的分子，用于已经上市的经过充分验证的重要药物靶点 针对它们的药物，既可以提高疗效，降低毒性，也可以创造新的知识分子。 专利过期药品的所有权蛋白质X射线晶体学（PX）是确定蛋白质的准确组成的金标准。 与药物靶标结合的给定片段的3D位置和方向。PX还可以检测更广泛的 与用于片段和化合物筛选的其他生物物理方法相比， 与蛋白质大小无关。然而，晶体学对于筛选大的 片段文库由于在用于共结晶的晶体的大规模生产中的显著瓶颈，晶体 用碎片浸泡、晶体收获、X射线数据收集、结构测定和分析。 互补的生物物理技术通常用于预先筛选结合的片段，然后 在第二步中用于确定每个片段的精确结合姿势。生物结构公司是 开发一个首次上市的、高效的、一步式的基于PX的片段文库筛选平台， 通过大幅提高效率和降低开发新型电极导线的成本来彻底改变该领域 用于临床前测试的分子。在第一阶段，我们评估了高密度结晶网格， 提高了靶-碎片共结晶、用碎片浸泡晶体和同步加速器的效率， 基于数据收集，在一个步骤中实现约5%的命中率，同时生成 蛋白质片段相互作用在成功完成第一阶段的目标后，我们现正 我们的第二阶段计划将这项实验技术与分布式计算晶体学相结合， 管道和数据管理/信息学骨干，使我们能够有效地处理大片段 图书馆屏幕我们将使用几种涉及各种肿瘤的可药物化和不可药物化的肿瘤学靶点， 癌症，从我们的行业和学术客户，作为概念验证系统，以证明的效用， 我们的整体平台。我们的计划与所有NCATS药物发现和开发SBIR保持一致 感兴趣的主题：“工具和技术，使化合物活性测定目前“非”， 可药用”目标”;“共结晶高通量筛选技术”;“工具和技术， 提高药物化学、生物或其他干预优化的预测性或效率”;以及 “开发高通量成像技术，重点是使转化研究更加 高效”。

Project Summary/Abstract Fragment-based drug discovery (FBDD) is a widely used method in the pharmaceutical industry for the de novo design of molecules that target new drug candidates. FBDD allows a more effective exploration of chemical space with a higher hit rate compared to high-throughput screening, and this can have significant effects in early drug discovery and in the case of challenging or “non-druggable” targets. FBDD has led to around 30 new drugs entering clinical trials and 2 that have entered the market. FBDD can also be used to discover and develop novel molecules for well-validated and important drug targets that already have marketed drugs against them, both for increasing efficacy with lower toxicity as well as creation of new intellectual property for off-patent drugs. Protein x-ray crystallography (PX) is the gold standard for determining the exact 3D location and orientation of a given fragment bound to a drug target. PX can also detect a wider range of binding affinities compared to other biophysical methods for fragment and compound screening and is independent of protein size. However, crystallography is expensive and inefficient for screening a large fragment library due to significant bottlenecks in mass production of crystals for co-crystallization, crystal soaking with fragments, crystal harvesting, X-ray data collection, structure determination and analysis. Complementary biophysical techniques are often used to prescreen for fragments that bind and PX is then used in a second step to determine the exact binding pose of each fragment. Accelero Biostructures is developing a first-to-market, efficient, one-step PX-based fragment library-screening platform that can revolutionize the field by dramatically increasing the efficiency and reducing the cost of developing novel lead molecules for preclinical testing. In Phase I we evaluated a high-density crystallization grid that dramatically increased the efficiency of target-fragment co-crystallization, crystal soaking with fragments and synchrotron- based data collection, leading to a hit rate of ~5% in a single step while simultaneously producing 3D details of protein-fragment interactions. After successfully completing our Phase I aims, we are now moving ahead with our Phase II plan to integrate this experimental technology with a distributed computational crystallography pipeline and data management/informatics backbone that will allow us to efficiently process a large fragment library screen. We will use several druggable and non-druggable oncology targets implicated in various cancers, from our industry and academic customers, as proof-of-concept systems to demonstrate the utility of our overall platform. Our plans are well-aligned with all of NCATS Drug Discovery and Development SBIR topics of interest: “Tools and technologies to enable assaying of compound activity on currently “non- druggable” targets”; “Co-crystallization high-throughput screening techniques”; “Tools and technologies that increase the predictivity or efficiency of medicinal chemistry, biologic or other intervention optimization”; and “Development of high-throughput imaging technologies that focus on making translational research more efficient”.