SGER: Computational Prediction of Enantioselectivity in Metal-Catalyzed Reactions

本计画将研究手性配体及金属配合物作为对映选择性反应催化剂的计算驱动的合理设计、虚拟筛选及实验验证。 这些反应在药物制剂、农业化学品和其他高价值化合物的生产中具有广泛的重要性。 该项目通过提供一种非常快速且易于使用的用于选择手性配体的虚拟筛选工具，具有改变对映选择性催化领域的潜力。 研究的初始阶段将集中于开发设计和发现用于对映选择性氢化和氢胺化的新催化剂的方法。 反应的这种选择是基于氢化和亲核加成产物的重要性。 在研究的后期阶段，这些方法将扩展到其他类型的对映选择性反应。有机和高分子化学计划的探索性研究小额赠款将支持圣母大学化学和生物化学系的Paul Helquist和Olaf Wiest教授的合作研究。 这两位研究人员及其同事的工作将为制药和化学工业提供更好的理解和更好的获得高效生产对映体纯化合物的方法。 这项研究还将为本科生和研究生提供宝贵的多学科培训，为他们在工业或学术界担任研究科学家的职业生涯做准备，重点是计算和实验方法之间的联系。

This project will study the computationally driven rational design, virtual screening, and experimental validation of chiral ligands and metal complexes as catalysts for enantioselective reactions. Such reactions are of widespread importance in the production of pharmaceutical agents, agricultural chemicals, and other high-value compounds. This project has the potential of transforming the field of enantioselective catalysis by providing a very fast and easy to use virtual screening tool for the selection of chiral ligands. The initial phases of the research will focus on development of methods for designing and discovering new catalysts for enantioselective hydrogenations and hydroaminations. This selection of reactions is based upon the importance of the hydrogenation and nucleophilic addition products. In later stages of the research, the methods will be extended to other types of enantioselective reactions.This Small Grants for Exploratory Research award from the Organic and Macromolecular Chemistry Program will support the collaborative research of Professors Paul Helquist and Olaf Wiest in the Department of Chemistry and Biochemistry at the University of Notre Dame. The work of these two investigators and their co-workers will provide greater understanding of and improved access to highly efficient methods for producing enantiomerically pure compounds for the pharmaceutical and chemical industries. This research will also provide valuable multi-disciplinary training of undergraduate and graduate students in preparation for their careers as research scientists in industry or academia, with emphasis on the connection between computational and experimental methods.