SusChEM: Design of Organocatalysts through Computational Screening

SusChEM：通过计算筛选设计有机催化剂

基本信息

批准号：
1665407
负责人：
Steven Wheeler
金额：
$ 35.89万
依托单位：
University of Georgia Research Foundation Inc
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2017
资助国家：
美国
起止时间：
2017-07-15 至 2021-06-30
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1665407&HistoricalAwards=false
关键词：
SusChEM Design Organocatalysts through Computational

项目摘要

The Chemical Catalysis Program of the Chemistry Division supports the project by Professor Steven E. Wheeler. Professor Wheeler is a faculty member in the Center for Computational Quantum Chemistry, Department of Chemistry at the University of Georgia. He is developing a free, open-source computational toolkit (AARON) to facilitate the design of transition-metal free asymmetric catalysts. This toolkit is being implemented to help develop new catalysts with applications in the synthesis of complex natural products and pharmaceuticals. This project will make it easier for non-specialists to use computational chemistry to design and evaluate new organocatalysts. The primary goal of this project is to provide computational tools that reduce the time and materials required to design new catalysts, thereby streamlining the catalyst design process. The project combines ideas from computational quantum chemistry, software development, data analytics, and organic synthesis, and provides graduate and undergraduate students with diverse training in highly transferrable skills. The project also supports a workshop on computational organic chemistry that is held in conjunction with an annual undergraduate computational chemistry conference organized by the MERCURY consortium.The development of new asymmetric organocatalysts typically depends on the experimental screening of a library of potential catalysts to identify the best catalysts for a single substrate. The substrate scope of this catalyst is then tested. The AARON program provides an alternative path for the development of organocatalysts with broad substrate scope by enabling the automated computational screening of virtual libraries of catalysts applied to multiple substrates simultaneously. In this way, the synthesis and testing of new catalysts can be prioritized based on predicted stereoselectivities and catalytic activities across a range of substrates. AARON is designed to identify novel bifunctional hydrogen bonding catalysts and chiral phosphoric acids for several reactions and to unravel the origin of stereoselectivity in ion-pairing catalysis. The development of an accompanying graphical interface for AARON enable its widespread use among organic chemists, while an online public database provides access to transition state structures, energies, and stereoselectivities, facilitating the application of modern data analysis tools to these rich datasets. Educational activities include the training of undergraduate and graduate students in computer programming, advanced electronic structure theory, and physical organic chemistry. Outreach activities include the development of a computational organic chemistry workshop for undergraduates, and the training of students in modern data analytics through the Georgia Informatics Institutes (GII).

化学部化学催化项目支持 Steven E. Wheeler 教授的项目。惠勒教授是佐治亚大学化学系计算量子化学中心的教员。他正在开发一个免费的开源计算工具包（AARON），以促进无过渡金属的不对称催化剂的设计。该工具包的实施是为了帮助开发新的催化剂，用于合成复杂的天然产物和药物。该项目将使非专业人士更容易使用计算化学来设计和评估新的有机催化剂。该项目的主要目标是提供计算工具，减少设计新催化剂所需的时间和材料，从而简化催化剂设计过程。该项目结合了计算量子化学、软件开发、数据分析和有机合成的思想，为研究生和本科生提供高度可转移技能的多样化培训。该项目还支持与 MERCURY 联盟组织的年度本科生计算化学会议同时举办的计算有机化学研讨会。新型不对称有机催化剂的开发通常取决于对潜在催化剂库的实验筛选，以确定最佳催化剂。单一底物的催化剂。然后测试该催化剂的底物范围。 AARON 计划通过自动计算筛选同时应用于多种底物的催化剂虚拟库，为开发具有广泛底物范围的有机催化剂提供了替代途径。通过这种方式，可以根据预测的立体选择性和一系列底物的催化活性来确定新催化剂的合成和测试的优先顺序。 AARON 旨在识别用于多种反应的新型双功能氢键催化剂和手性磷酸，并揭示离子对催化中立体选择性的起源。 AARON 随附图形界面的开发使其能够在有机化学家中广泛使用，同时在线公共数据库提供对过渡态结构、能量和立体选择性的访问，促进现代数据分析工具在这些丰富的数据集上的应用。教育活动包括对本科生和研究生进行计算机编程、高级电子结构理论和物理有机化学方面的培训。外展活动包括为本科生举办计算有机化学研讨会，以及通过佐治亚信息学院 (GII) 对学生进行现代数据分析培训。