Modeling multimetallic transition metal catalysts to enhance organic synthesis transition metal catalyzed reactions have emerged as an extremely important aspect of modern organic synthesis and drug…

The National Institute of General Medical Sciences awarded Brigham Young University $442,140 on July 1, 2026, under the Biomedical Research and Research Training program (CFDA 93.859) to develop quantum-chemical and data science approaches for modeling multimetallic transition metal catalyzed organic reactions. The work focuses on two reaction types: metal hydrogen atom transfer reactions for alkene functionalization and cross-coupling reactions relevant to drug discovery. The project will create computational tools and methodologies for designing and identifying new multimetallic catalysts, addressing a gap in understanding complex multimetallic catalytic cycles and reaction mechanisms. Performance takes place in Provo, Utah, with a period of performance from July 1, 2026 through June 30, 2029. The award is classified as a Project Grant.

Modeling multimetallic transition metal catalysts to enhance organic synthesis transition metal catalyzed reactions have emerged as an extremely important aspect of modern organic synthesis and drug discovery. Typically, this involves the use of a single transition metal and an organic ligand. In contrast, an emerging frontier in organic synthesis is the use of two active transition metals that have interdependent catalytic cycles. This type of multimetallic catalysis has significant potential to achieve new transformations as well as greater reactivity and higher selectivity. However, while a few general patterns and classifications have emerged for multimetallic reactions there remains a general lack of understanding that can be applied across many types of reactions. Also, multimetallic reactions often have especially complex reaction mechanisms and reaction conditions that require the development and application of new atomistic modeling approaches. Therefore, this work will develop and use state-of-the-art quantum-chemical and data science approaches to model and predict multimetallic transition metal catalyzed organic reactions. The modeling will focus on two types of multimetallic reactions. The first is multimetallic catalyzed reactions that involve metal hydrogen atom transfer (mhat) reaction steps. These reactions are important because they result in alkene functionalization to build complex organic compounds. The second is multimetallic catalyzed cross-coupling reactions. These reactions are important because cross-couplings provide key compounds for drug discovery. In addition to providing new insights into existing chemical reactions this work will demonstrate new tools and approaches to computational design and identification of new multimetallic catalysts, which remains a challenging frontier in organic chemistry.