Saturday, December 21, 2024
12/21/2024
Project Summary: Mechanistic understanding of emerging catalytic methodologies is an important factor in the successful application of novel transformations to the synthesis of pharmaceuticals and other high- value chemicals. Despite this, there is a significant lag between new reaction discovery and its mechanistic description. This research program addresses this challenge in two important areas of contemporary catalysis – photoredox catalysis and biocatalysis by engineered enzymes. Photocatalysts harness the power of visible light to generate highly reactive radical intermediates that can be strategically channeled to participate in a variety of valuable bond-formations. There are a variety of photophysical approaches for the detection and characterization of these open-shell intermediates. However, experimental probes of the transition state geometry, of key bond-forming and bond-breaking events in photoredox catalysis, are virtually non-existent. In this context, this research program establishes 13C kinetic isotope effects as the elusive experimental probe of the transition state geometry of photoredox reactions. In addition to shedding light on these complex reaction mechanisms, this measurement serves as an important experimental benchmark to calibrate theoretical methods to accurately evaluate the rate- and selectivity-determining steps in these reactions. Directed evolution of cytochromes P450 has led to the discovery of carbene- and nitrene-transfer activity of these heme-containing enzymes. Mechanistic investigations of these systems have largely been limited to theoretical studies due to the inherent challenges associated with conducting standard physical organic experiments in enzymatic systems. This program utilizes a newly developed intramolecular 13C kinetic isotope effect technique along with classical kH/kD experiments to gain insight into the transition state geometry of C–C and C–N bond-forming steps in these reactions. High-level QM/MM calculations and MD simulations are also utilized to interpret experimental findings and understand the origin of selectivity in these biocatalytic reactions.
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