GOALI: D3SC: New Ligands and Understanding from Pharmaceutical Compound Libraries

目标：D3SC：新配体和对药物化合物库的理解

• 批准号: 1900366
• 负责人: Daniel Weix
• 金额: $ 48.5万
• 依托单位: University of Wisconsin-Madison
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-08-01 至 2024-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1900366&HistoricalAwards=false
• 关键词: GOALI; D3SC; New; Ligands; Understanding

With this award, the Chemical Catalysis Program of the NSF Division of Chemistry is supporting the research of Professor Daniel Weix at the University of Wisconsin-Madison and Dr. Eric Hansen at Pfizer to explore new methods to find better catalysts for chemical reactions. Metal-catalyzed reactions are the key to improving the stewardship of the U.S.'s vast petrochemical resources and to discovering innovative, new medicines. Existing technology is based around scarce metals, such as palladium and rhodium, but recent developments with more earth-abundant metals, such as nickel, copper, and iron, show great promise. Unfortunately, there are currently few catalysts based around these more environmentally friendly and less expensive metals. This industrial-academic partnership is discovering new catalysts by mining an untapped resource, pharmaceutical compound libraries. Using these libraries of knowledge, the team is mining data to find new catalysts and to gather information on what properties make a good catalyst. Analysis of the collected data by researchers at Pfizer and UW-Madison, with the assistance of Professor Matthew Sigman at the University of Utah, guides the prediction of new catalysts and catalyst selection. The newly discovered catalysts are being made available to researchers through a partnership with Millipore-Sigma. This combination of experimental and computational training is preparing students to advance the use of data science in chemistry, an area that is rapidly growing in importance. This training includes students who are currently underrepresented in chemistry through partnerships with existing and new UW-Madison programs: the Chemistry Opportunities Program, Partners for Graduate School Experience in Chemistry, and the American Chemical Society BRIDGE to the Doctorate program.The UW-Madison team, led by Professor Weix, and the Pfizer team, led by Dr. Hansen, are systematically searching the very large Pfizer compound library for new ligands using an iterative experimental and computational approach inspired by fragment-based drug discovery. The goals of this collaboration are to discover new privileged ligands and to develop broadly applicable parameters and models. Diverse potential ligands sourced from the compound library are being screened against known reactions with different metal and ligand requirements to find new ligand core structures. These core structures are then being optimized using conventional methods. The data gathered is analyzed, in collaboration with Professor Sigman, to provide an understanding of which properties (if any) are universal for useful ligands and to predict improved ligands. The impacts of this this research program extend to the development of new ligands and versatile ligand precursors that are immediately made commercially available from Millipore-Sigma. The research may also result in better parameters and models that are useful for constructing a more diverse array of ligand types. The large data sets are helpful for developing new computational approaches made available through data repositories.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.

通过此奖项，NSF化学部的化学催化计划支持威斯康星大学麦迪逊分校的丹尼尔·韦克斯教授的研究和辉瑞派的埃里克·汉森博士探索新方法，以找到更好的化学反应催化剂。金属催化的反应是改善美国大量石化资源的管理并发现创新的新药物的关键。现有的技术基于稀缺的金属，例如钯和若i，但是最近的发展具有更多地球金属（例如镍，铜和铁），这表现出了很大的希望。不幸的是，目前很少有催化剂基于这些更加环保和较便宜的金属。这种工业学术伙伴关系通过挖掘未开发的资源，药品复合图书馆来发现新的催化剂。使用这些知识库，该团队正在挖掘数据以查找新的催化剂，并收集有关哪些属性构成良好催化剂的信息。在犹他州大学的Matthew Sigman教授的协助下，辉瑞和UW-Madison的研究人员对收集的数据分析，指导了新的催化剂和催化剂选择的预测。通过与Millipore-Sigma建立合作伙伴关系，新发现的催化剂可供研究人员使用。实验培训和计算培训的这种结合正在使学生准备提高数据科学在化学中的使用，这一领域正在迅速增长。这项培训包括通过与现有和新的UW-Madison计划的合作伙伴关系：化学机会计划，化学研究生经验的合作伙伴以及美国化学学会的博士学位课程的合作伙伴，由UW-Madison Team（由Weix教授和富萨尔博士领导的HANSEN IMPERIONT for HANSENTIONS HANSENTIONS）领导的UW-MADISON TEAM，该培训包括在化学方面的人数不足。以及受基于碎片的药物发现启发的计算方法。这项合作的目标是发现新的特权配体并开发广泛适用的参数和模型。来自复合文库的各​​种潜在配体正在针对具有不同金属和配体要求的已知反应，以找到新的配体核心结构。然后使用常规方法优化这些核心结构。与Sigman教授合作分析了收集的数据，以提供了解哪些属性（如果有的话）是通用的，以进行有用的配体并预测改进的配体。该研究计划的影响扩展到了新的配体和多功能配体前体的开发，这些配体前体可立即从Millipore-Sigma商业上获得。 该研究还可能导致更好的参数和模型，这些参数和模型可用于构建多种多样的配体类型。 大型数据集有助于开发通过数据存储库提供的新计算方法。该奖项反映了NSF的法定任务，并且使用基金会的知识分子优点和更广泛的影响审查标准，被认为值得通过评估来获得支持。