# Computational Models for Reactivity and Selectivity in Transition Metal-Catalyzed Olefin Functionalization

> **NIH NIH R35** · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · 2020 · $369,498

## Abstract

Transition metal-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 hydro- and difunctionalization of alkenes, which add a hydrogen and a functional
group or two different functional groups across a carbon-carbon double bond in an atom- and step-economical
fashion. These approaches can serve as an important new platform for the synthesis of biologically active organic
molecules because they can be utilized to construct structurally diverse target molecules using a broad scope of
coupling partners. However, it remains a significant challenge to effectively control regio- and stereoselectivity
in the reactions with readily available, unactivated alkenes. The current state-of-the-art approach relies on
experimental trial-and-error to screen ancillary ligands, additives, and directing groups. Rational catalyst design
remains challenging, due to the lack of theoretical understanding about the mechanisms of these multistep
catalytic processes and the complex nature of the catalyst-substrate interactions.
 The overall goal of this proposal is to develop and apply computational tools to address these challenges in
the development of transition-metal-catalyzed functionalizations of alkenes. We will perform high-level
computational studies to reveal the reaction mechanisms and develop generally applicable models for reactivity
and selectivity. These theoretical models aim to provide quantitative and straightforward prediction of the effects
of ligands and directing groups. Therefore, they can be effectively applied to various experimental systems to
guide future development of new catalytic reactions. During the first three years of my independent career, my
group has published 24 manuscripts that focused on three general experimental strategies for alkene
functionalization: (1) catalyst-controlled hydrofunctionalization of unactivated alkenes; (2) hydro- and
difunctionalization of alkenes utilizing directing groups; and (3) radical-mediated reactions with alkenes. In the
next five years, we plan to expand our computational studies to a broader scope of reactions. We will further
optimize and validate our theoretical models to enable more robust prediction of reactivity and selectivity. We
also intend to establish more collaborations with experimental groups to streamline the use of theoretical insights
to guide experimental discovery.
 The proposed research program is significant and innovative because it aims to address general challenges
and provide predictions to a broad range of catalytic reactions, rather than to simply explain existing results for
specific experimental systems. 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 fu...

## Key facts

- **NIH application ID:** 9990823
- **Project number:** 5R35GM128779-03
- **Recipient organization:** UNIVERSITY OF PITTSBURGH AT PITTSBURGH
- **Principal Investigator:** Peng Liu
- **Activity code:** R35 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $369,498
- **Award type:** 5
- **Project period:** 2018-09-01 → 2023-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9990823

## Citation

> US National Institutes of Health, RePORTER application 9990823, Computational Models for Reactivity and Selectivity in Transition Metal-Catalyzed Olefin Functionalization (5R35GM128779-03). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/9990823. Licensed CC0.

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