Real-time discovery of inhibitors among billion compounds for preview and download

实时发现十亿种化合物中的抑制剂以供预览和下载

• 批准号: 9246147
• 负责人: Carlos J. Camacho
• 金额: $ 32.11万
• 依托单位: UNIVERSITY OF PITTSBURGH AT PITTSBURGH
• 依托单位国家: 美国
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-07-15 至 2021-02-28
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9246147
• 关键词: Address; Adenine; Agonist; Amino Acids; Ants; Benchmarking; Binding; Biological Assay; Biology; Chemicals; Chemistry; Collaborations; Communities; Computational Technique; Computer Simulation; Cytosine; DNA; Data; Databases; Development; Docking; Drug Design; Funding; Glutamine; Goals; Guanine; Human; In Vitro; Individual; Intervention; Lead; Left; Libraries; Link; Methodology; Methods; Modality; Modeling; Modification; Molecular Weight; Monoclonal Antibody F19; Natural Products; Natural Products Chemistry; Pathway interactions; Pharmaceutical Chemistry; Pharmaceutical Preparations; Proteins; Proteome; RNA; Reaction; Research; Research Infrastructure; Research Personnel; Sampling; Site; Speed; Structure; Structure-Activity Relationship; TP53 gene; Technology; Testing; Therapeutic; Thymine; Time; Uracil; Validation; Virtual Library; analog; arginyllysine; base; chemical reaction; chemical synthesis; database query; design; drug discovery; experimental study; high throughput screening; improved; in vivo; inhibitor/antagonist; innovation; insight; novel; pharmacophore; prospective; protein function; protein phosphatase inhibitor-2; protein protein interaction; scaffold; screening; small molecule; success; tool; user-friendly; virtual

Realtime Discovery of Inhibitors among Billion Compounds for Preview and Download Current drug discovery collaborations are mainly centered on the high-throughput screening of large libraries of commercially available or proprietary compounds. This rigid modality is inaccessible to most individual researchers, providing little opportunity for leveraging the large number of small-scale assays available in biology research labs. On the other hand, in silico screening methods of an expanding chemical space that is inaccessible to high-throughput approaches are credible and efficient alternatives for developing novel chemical probes of protein function, yet they are not readily accessible to biologists. Our ultimate goal is to empower researchers around the world to use their own in-house small-scale screening assays to validate compounds that they, as experts on their own targets, rationally designed using structure-based pharmacophore methods and large virtual libraries of both commercially accessible and novel, chemically accessible, small molecular weight drug-like compounds that are biased to target protein interactions. In the previous funding period, we have developed open access structure-based platforms that successfully potentiate real time iterative exact pharmacophore matching, model modification and fast database query for a given target. These technologies, AnchorQuery and ZincPharmer, presently screen over 55 million compounds readily synthesizable by multi-component reaction (MCR) or commercially available at the press of a “click”, supporting drug discovery efforts worldwide. Building on these robust platforms, we plan to improve and significantly expand the design capabilities of our tools for rational drug design. Specifically, our aims are to: (a) expand the chemical space and targets covered by our libraries with novel MCR-accessible virtual compounds biased to target protein-protein and protein-RNA/DNA interactions, as well as natural products; (b) develop new virtual screening technologies for disrupting protein-RNA/DNA interactions and for leveraging natural product chemistry; (c) develop a new in silico hit-to-lead optimization tool to perform on the fly virtual structure activity relationship analysis of a billion size MCR chemical space; (d) improve the ranking, optimization and other analytical capabilities of our virtual screening technology; and (e) actively engage worldwide research groups with in vitro and/or in vivo assays with the goal of developing small molecular weight (ant)agonists. These aims will deliver cutting edge open access, interactive, user-friendly technologies for virtual screening of billion size libraries for preview and download to any biomedical researcher in the world.

在数十亿种化合物中实时发现抑制剂，供预览和下载 目前的药物发现合作主要集中在大分子的高通量筛选上。 市售或专有化合物的库。这种僵硬的形式是无法接近的， 大多数个体研究人员，几乎没有机会利用大量的小规模研究人员， 生物学研究实验室提供的检测方法。另一方面，计算机模拟筛选方法 扩大高通量方法无法达到的化学空间是可信的， 开发蛋白质功能的新型化学探针的有效替代品，但它们并不容易 生物学家可以接触到。我们的最终目标是使世界各地的研究人员能够利用他们的 自己的内部小规模筛选试验，以验证化合物，他们作为专家自己 使用基于结构的药效团方法和大型虚拟库合理设计的靶标 商业上可获得的和新的，化学上可获得的，小分子量的药物， 偏向于靶蛋白相互作用的化合物。 在上一个融资期，我们开发了基于开放获取结构的平台， 成功地增强了真实的时间迭代精确药效团匹配、模型修改和快速 针对给定目标的数据库查询。这些技术，AnchorQuery和ZincPharmer，目前 筛选超过5500万种可通过多组分反应（MCR）合成的化合物， 在商业上可在“点击”的新闻，支持药物发现的努力在世界各地。建筑 在这些强大的平台上，我们计划改进并显著扩展我们的 合理药物设计的工具。具体而言，我们的目标是：（a）扩大化学空间和目标 我们的库涵盖了偏向于靶蛋白质-蛋白质的新型MCR可访问虚拟化合物 和蛋白质-RNA/DNA相互作用，以及天然产物;（B）开发新的虚拟筛选 破坏蛋白质-RNA/DNA相互作用和利用天然产物的技术 化学;（c）开发一种新的计算机模拟命中引导优化工具，以执行动态虚拟结构 十亿级MCR化学空间的活性关系分析;（d）改进排序， 我们的虚拟筛选技术的优化和其他分析能力;以及（e）积极 让世界各地的研究小组参与体外和/或体内试验，目的是开发 小分子量（ANT）激动剂。这些目标将提供尖端的开放获取，互动， 用户友好的技术，用于虚拟筛选数十亿大小的图书馆，以便预览和下载到任何 生物医学研究者。