Computational Prediction of Enantioselectivity in Metal-Catalyzed Reactions

金属催化反应中对映选择性的计算预测

• 批准号: 2247232
• 负责人: Olaf Wiest
• 金额: $ 62万
• 依托单位: University of Notre Dame
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-06-01 至 2026-05-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2247232&HistoricalAwards=false
• 关键词: Computational; Prediction; Enantioselectivity; Metal; Catalyzed

With the support of the Chemical Catalysis Program in the Division of Chemistry, Professors Olaf Wiest and Paul Helquist at the University of Notre Dame are developing computational methods for the fast and accurate prediction of the stereochemical, or three-dimensional, outcomes of chemical reactions. In many reactions, two different products known as enantiomers or mirror images can be formed. For applications such as pharmaceuticals, sometimes only one of the enantiomers is beneficial while the other may have no benefit or may even have deleterious effects. Traditional methods based entirely on experimental studies to find a means to selectively generate only one enantiomer are slow and expensive. They make use of largely trial-and-error approaches often requiring hundreds of experiments to be performed with expensive reagents and catalysts and, in the meantime, generate unnecessary chemical waste. In contrast, the computational methods that are the basis of the current project are a fast and cost-efficient means to predict specific catalysts that will produce the desired enantiomeric outcome. These predictions accelerate and support follow-up experimental studies. This work will likely have a significant broader impact because it is performed in close collaboration with AstraZeneca, a major international pharmaceutical company. They not only incorporate the Notre Dame methods into their process research to foster innovation, but also provide unique professional development opportunities for the students working on the project through industrial internships, interdisciplinary training at AstraZeneca in Sweden, and regular interactions with industrial researchers. The two lead investigators are strongly committed to broadening participation with a long track record of offering undergraduate research opportunities to students from underrepresented groups, as instructors in the Galvin Scholars Program for students from less well-prepared educational backgrounds, and by serving as mentors in the Building Bridges Program for underrepresented minority students.Professors Helquist and Wiest at the University of Notre Dame continue the development of a virtual screening tool for enantioselective catalysis (CatVS) that uses transition state force fields (TSFFs) derived using the quantum-guided molecular mechanics (Q2MM) method. This includes several new methods for the optimization of TSFFs that improve the accuracy of TSFF combinations with literature force fields, the semi-automation of the fitting procedure using a hybrid epsilon-constraint/PSO method; improved workflows for the generation and screening of virtual libraries (LibGen), new interfaces to other programs for conformational searching and TSFFs for new reactions selected by the team in collaboration with their industrial partners. Once tested and validated, all new developments will be incorporated in the Q2MM/LibGen/CatVS code that will continue to be available to the scientific community free of charge at github.com/q2mm. The impact of this method will be demonstrated in applications ranging from Ir-catalyzed hydroaminations of unactivated alkenes through novel nickel-catalyzed cross-coupling reactions to the computer-assisted design of new ligand classes for enantioselective synthesis. The combined computational and experimental approach, combined with the close collaboration with AstraZeneca, provides a unique interdisciplinary training environment for undergraduate and graduate students.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.

在化学催化计划的化学划分方案的支持下，巴黎圣母院的奥拉夫·韦斯特（Olaf Wiest）和保罗·赫尔奎斯特（Paul Helquist）正在开发计算方法，以快速准确地预测化学化学或三维化学反应结果。在许多反应中，可以形成两种称为对映异构体或镜像图像的不同产品。对于诸如药品之类的应用，有时只有一个对映异构体是有益的，而另一个对映异构体可能没有好处，甚至可能具有有害影响。完全基于实验研究的传统方法，以找到一种选择性产生一种对映异构体的方法缓慢而昂贵。他们利用经常需要使用昂贵的试剂和催化剂进行数百个实验的试验方法，同时产生了不必要的化学废物。相反，作为当前项目的基础的计算方法是一种快速且经济高效的方法，用于预测将产生所需的对映体结果的特定催化剂。这些预测加速并支持后续实验研究。这项工作可能会产生更大的影响，因为它是与主要的国际制药公司Astrazeneca密切合作进行的。他们不仅将巴黎圣母院的方法纳入了他们的过程研究中以促进创新，而且还为通过工业实习，瑞典阿斯利康市的跨学科培训以及与工业研究人员进行定期互动的学生提供了独特的专业发展机会。 The two lead investigators are strongly committed to broadening participation with a long track record of offering undergraduate research opportunities to students from underrepresented groups, as instructors in the Galvin Scholars Program for students from less well-prepared educational backgrounds, and by serving as mentors in the Building Bridges Program for underrepresented minority students.Professors Helquist and Wiest at the University of Notre Dame continue the development of a virtual screening使用量子引导的分子力学（Q2mm）方法得出的过渡状态力场（TSFF）的对映选择性催化（CATV）的工具。这包括几种优化TSFF的新方法，这些方法可以提高TSFF组合与文献力场的准确性，使用混合Epsilon-Constraint/PSO方法的拟合程序的半自动化；改进了虚拟库（Libgen）生成和筛选的工作流程，其他程序进行构象搜索的新接口以及团队与工业合作伙伴合作选择的新反应的TSFF。经过测试和验证后，所有新的开发项目都将纳入Q2mm/libgen/catvs代码中，该代码将继续在GitHub.com/Q2MM上免费提供给科学界。该方法的影响将在从IR催化的盐水通过新型镍催化的交叉偶联反应到对映选择性合成的新配体类的计算机辅助设计的应用中证明。结合的计算和实验方法，再加上与阿斯利康的密切合作，为本科和研究生提供了独特的跨学科培训环境。该奖项反映了NSF的法定任务，并被认为是值得通过基金会的知识分子优点和更广泛影响的审查标准来通过评估来获得支持的。

项目成果

A Proline-Squaraine Ligand Framework (Pro-SqEB) for Stereoselective Rhodium(II)-Catalyzed Cyclopropanations

用于立体选择性铑 (II) 催化环丙烷化的脯氨酸-方酸菁配体框架 (Pro-SqEB)

• DOI: 10.1021/acs.orglett.3c03344
• 发表时间: 2023
• 期刊: Organic Letters
• 影响因子: 5.2
• 作者: Bacher, Emily P.;Twiringiyimana, Raïssa;Rodriguez, Kevin X.;Wilson, Renita A.;Bodnar, Alexandra K.;O’Connell, Ryan;Toni, Tiffany A.;Eckert, Kaitlyn E.;Wiest, Olaf;Ashfeld, Brandon L.
• 通讯作者: Ashfeld, Brandon L.