Theoretical Perspectives in Organocatalysis

Melnyk, Nika; Iribarren, Íñigo; Mates‐Torres, Eric; Trujillo, Cristina

doi:10.1002/chem.202201570

Cited by 14 publications

(6 citation statements)

References 65 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Therefore, the most favorable TS conformation TS-( S ) creates an ideal-fit pocket where the substrate can coordinate with maximum stabilizing interactions during the C–O bond-forming step. Overall, the DFT calculations and subsequent analysis of the stereoselectivity-determining intramolecular conjugate addition provide detailed insights and understanding into the origin of the enantioselectivity for this transformation using a tuneable BIMP catalyst …”

Section: Resultsmentioning

confidence: 99%

Catalytic Enantioselective Intramolecular Oxa-Michael Reaction to α,β-Unsaturated Esters and Amides

Formica

Yamazaki

et al. 2023

J. Am. Chem. Soc.

View full text Add to dashboard Cite

A bifunctional iminophosphorane (BIMP)-catalyzed, enantioselective intramolecular oxa-Michael reaction of alcohols to tethered, low electrophilicity Michael acceptors is described. Improved reactivity over previous reports (1 day vs 7 days), excellent yields (up to 99%), and enantiomeric ratios (up to 99.5:0.5 er) are demonstrated. The broad reaction scope, enabled by catalyst modularity and tunability, includes substituted tetrahydrofurans (THFs) and tetrahydropyrans (THPs), oxaspirocycles, sugar and natural product derivatives, dihydro-(iso)-benzofurans, and iso-chromans. A state-of-the-art computational study revealed that the enantioselectivity originates from the presence of several favorable intermolecular hydrogen bonds between the BIMP catalyst and the substrate that induce stabilizing electrostatic and orbital interactions. The newly developed catalytic enantioselective approach was carried out on multigram scale, and multiple Michael adducts were further derivatized to an array of useful building blocks, providing access to enantioenriched biologically active molecules and natural products.

show abstract

Section: Resultsmentioning

confidence: 99%

Catalytic Enantioselective Intramolecular Oxa-Michael Reaction to α,β-Unsaturated Esters and Amides

Formica

Yamazaki

et al. 2023

J. Am. Chem. Soc.

View full text Add to dashboard Cite

show abstract

“…https://doi.org/10.26434/chemrxiv-2024-xfdn8 ORCID: https://orcid.org/0000-0002-0965-0208 Content not peer-reviewed by ChemRxiv. License: CC BY 4.0 4 Such tools have recently been extensively reviewed [23][24][25]. Based on a known mechanism, the tools calculate the energies of relevant species either via force field or quantum chemical methods to assess the properties of a reaction such as activation energies or selectivity.…”

Section: Introductionmentioning

confidence: 99%

Catalysing (organo-) catalysis: Trends in the application of machine learning to enantioselective organocatalysis

Schmid,

Schlosser,

Glorius

et al. 2024

Preprint

View full text Add to dashboard Cite

Organocatalysis has established itself as a third pillar of homogeneous catalysis, besides transition metal catalysis and biocatalysis, as its use for enantioselective reactions has gathered significant interest over the last decades. Concurrent to this development, machine learning (ML) has been increasingly applied in the chemical domain to efficiently uncover hidden patterns in data and accelerate scientific discovery. While the uptake of ML in organocatalysis has been comparably slow, recent years have shown an increased interest in the community. This review gives an overview of the work in the field of ML in organocatalysis. The review starts by giving a short primer on ML for experimental chemists, before discussing its application for predicting the selectivity of organocatalytic transformations. Subsequently, we review ML employed for privileged catalysts, before focusing on its application for catalyst and reaction design. Concluding, we give our view on current challenges and future directions for this field, drawing inspiration from the application of ML to other scientific domains.

show abstract

“…Various reviews on or with emphasis on computational organocatalysis include the works from the group of Duarte [ 11 ], Krenske [ 12 ], and Trujillo [ 13 , 14 ]. Modeling with computational chemistry provides microscopic insight at a level that cannot be otherwise obtained experimentally.…”

Section: Introductionmentioning

confidence: 99%

Molecular Understanding and Practical In Silico Catalyst Design in Computational Organocatalysis and Phase Transfer Catalysis—Challenges and Opportunities

Kee

2023

Molecules

View full text Add to dashboard Cite

Through the lens of organocatalysis and phase transfer catalysis, we will examine the key components to calculate or predict catalysis-performance metrics, such as turnover frequency and measurement of stereoselectivity, via computational chemistry. The state-of-the-art tools available to calculate potential energy and, consequently, free energy, together with their caveats, will be discussed via examples from the literature. Through various examples from organocatalysis and phase transfer catalysis, we will highlight the challenges related to the mechanism, transition state theory, and solvation involved in translating calculated barriers to the turnover frequency or a metric of stereoselectivity. Examples in the literature that validated their theoretical models will be showcased. Lastly, the relevance and opportunity afforded by machine learning will be discussed.

show abstract

Theoretical Perspectives in Organocatalysis

Cited by 14 publications

References 65 publications

Catalytic Enantioselective Intramolecular Oxa-Michael Reaction to α,β-Unsaturated Esters and Amides

Catalytic Enantioselective Intramolecular Oxa-Michael Reaction to α,β-Unsaturated Esters and Amides

Catalysing (organo-) catalysis: Trends in the application of machine learning to enantioselective organocatalysis

Molecular Understanding and Practical In Silico Catalyst Design in Computational Organocatalysis and Phase Transfer Catalysis—Challenges and Opportunities

Contact Info

Product

Resources

About