Computational Models for Reactivity and Selectivity in Catalytic Olefin Functionalization
Project Number2R35GM128779-06
Former Number5R35GM128779-05
Contact PI/Project LeaderLIU, PENG
Awardee OrganizationUNIVERSITY OF PITTSBURGH AT PITTSBURGH
Description
Abstract Text
Abstract
Transition metal- and enzyme-catalyzed reactions of alkenes are among the most powerful approaches to
synthesize functionalized organic compounds for biomedical research. Recent experimental advancements have
enabled promising catalytic methods for various alkene functionalization reactions with different mechanistic
features and distinct types of bond formations. However, it remains a significant challenge to effectively control
regio- and stereoselectivity in reactions with readily available, unactivated alkenes. Due to the lack of theoretical
understanding of reaction mechanisms and origins of catalyst effects on reactivity and selectivity, experimental
developments of new catalytic reactions often rely on trial-and-error screening. A general strategy to investigate
catalytic reaction mechanisms and to utilize mechanistic information to guide catalyst discovery is warranted.
The overall goal of this proposal is to develop and apply computational tools to obtain mechanistic insights
and predictive models to guide experimental development of catalytic functionalizations of alkenes. We will use
a series of computational tools, including density functional theory (DFT) and ab initio molecular dynamics (AIMD)
simulations, to model reaction pathways and identify rate- and selectivity-determining transition states. We will
utilize energy decomposition analysis (EDA) calculations to analyze covalent and non-covalent interactions
between catalyst and substrate and provide quantitative and straightforward prediction of dominant catalyst–
substrate interactions that control reactivity and selectivity. We will apply these computational tools to investigate
mechanistically complex catalytic systems, including reactions involving conformationally flexible catalysts,
solvent cage effects in radical-mediated reactions, and cooperative effects in multicomponent reactions. We will
use computational tools to perform detailed studies of new-to-nature reactions catalyzed by engineered enzymes.
These studies will reveal the mechanisms of enantioinduction and the roles of key active site residues on
reactivity and selectivity.
The proposed research program is significant and innovative because it aims to address general challenges
in computational studies of a broad range of catalytic reactions, rather than to simply explain existing results for
specific experimental systems. Our studies will establish computational approaches to investigate complex, yet
important phenomena in catalysis, including the roles of non-covalent interactions, solvent, and catalyst flexibility.
These mechanistic insights can provide new principles and strategies in rational catalyst design to improve
reactivity, selectivity, and substrate scope. Our research is highly unique in collaborating with many prominent
experimental groups. These fruitful collaborations allowed us to progress in not only the understanding of many
specific examples of alkene functionalization reactions, but also the development of general rules of regio- and
stereoselectivity in these processes.
Public Health Relevance Statement
Project Narrative
Lack of robust and selective methods for the synthesis of structurally diverse organic
molecules is a major bottleneck in the drug discovery process. This proposal aims to address
this general challenge by developing and applying computational tools to guide experimental
development of transition metal and enzyme-catalyzed reactions to selectively functionalize
alkenes.
No Sub Projects information available for 2R35GM128779-06
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