Cinchona Urea-Catalyzed Asymmetric Sulfa-Michael Reactions: The Brønsted Acid-Hydrogen Bonding Model.

This is the final version of the article. It first appeared from the American Chemical Society via http://dx.doi.org/10.1021/jacs.6b05074The cinchona alkaloid-derived urea-catalyzed asymmetric conjugate addition of aromatic thiols to cycloalkenones was studied using density functional theory (DFT). Deprotonation of the thiol gives a protonated amine that activates the electrophile by Brønsted acid catalysis, while the urea group binds the nucleophilic thiolate by hydrogen bonding. These results demonstrate the generality of the Brønsted acid-hydrogen bonding transition state (TS) model for cinchona alkaloid catalysis that we recently showed to be favored over Wynberg's widely accepted ion pair-hydrogen bonding model and represent the first detailed mechanistic study of a cinchona urea-catalyzed reaction. The conformation of the catalyst methoxy group has a strong effect on the TS, an effect overlooked in previous mechanistic studies of reactions catalyzed by cinchona alkaloids.We are grateful to The English-Speaking Union (Lindemann Trust Fellowship to M.N.G.), Girton College, Cambridge (Research Fellowship to M.N.G.) and the NSF (CHE- 1361104 to K.N.H.) for financial support. Computational resources were provided by the UCLA Institute for Digital Research and Education (IDRE) and the Extreme Science and Engineering Discovery Environment (XSEDE), which is supported by the NSF (OCI-1053575). Part of this work was performed using the Darwin Supercomputer of the University of Cambridge High Performance Computing Service (http://www. hpc.cam.ac.uk/), provided by Dell Inc. using Strategic Research Infrastructure Funding from the Higher Education Funding Council for England and funding from the Science and Technology Facilities Council

Cinchona Alkaloid-Catalyzed Asymmetric Conjugate Additions: The Bifunctional Brønsted Acid-Hydrogen Bonding Model.

Wynberg's report from 1977 that natural cinchona alkaloids catalyze the asymmetric conjugate addition of aromatic thiols to cycloalkenones is a landmark discovery in hydrogen bonding organocatalysis. Wynberg proposed that this reaction proceeded via the formation of a thiolate-alkylammonium tight ion pair and activation of the enone electrophile by a hydrogen bond from the catalyst's hydroxyl group. This reaction model provided the mechanistic basis for understanding Wynberg's reaction and many other asymmetric transformations since. Our quantum mechanical calculations reveal a different model should be used to explain the results: the alkylammonium ion activates the enone by Brønsted acid catalysis, and the catalyst's hydroxyl group orients the thiolate nucleophile. The new model rationalizes the stereoselective outcome of Wynberg's reaction and provides a new, general model for asymmetric cinchona organocatalysis

Understanding the mechanism of the chiral phosphoric acid-catalyzed aza-Cope rearrangement

The first catalytic enantioselective aza-Cope rearrangement was reported in 2008 by Rueping et al. The reaction is catalyzed by a 1,1′-bi-2-naphthol-derived (BINOL-derived) phosphoric acid and achieved high yields and enantioselectivities (up to 97 : 3 er with 75% yield). This work utilizes Density Functional Theory to understand the mechanism of the reaction and explain the origins of the enantioselectivity. An extensive conformational search was carried out to explore the different activation modes by the catalyst and, the Transition State (TS) leading to the major product was found to be 1.3 kcal mol−1 lower in energy than the TS leading to the minor product. The origin of this stabilization was rationalized with NBO and NCI analysis: it was found that the major TS has a greater number of non-bonding interactions between the substrate and the catalyst, and shows stronger H-bond interactions between H atoms in the substrate and the O atoms in the phosphate group of the catalyst

Density Functional Theory in the Prediction of Mutagenicity: A Perspective

As a field, computational toxicology is concerned with using in silico models to predict and understand the origins of toxicity. It is fast, relatively inexpensive, and avoids the ethical conundrum of using animals in scientific experimentation. In this perspective, we discuss the importance of computational models in toxicology, with a specific focus on the different model types that can be used in predictive toxicological approaches toward mutagenicity (SARs and QSARs). We then focus on how quantum chemical methods, such as density functional theory (DFT), have previously been used in the prediction of mutagenicity. It is then discussed how DFT allows for the development of new chemical descriptors that focus on capturing the steric and energetic effects that influence toxicological reactions. We hope to demonstrate the role that DFT plays in understanding the fundamental, intrinsic chemistry of toxicological reactions in predictive toxicology

Asymmetric boronate addition to o-quinone methides: ligand exchange, solvent effects, and Lewis acid catalysis.

Density functional theory calculations suggest that asymmetric boronate addition to o-quinone methides proceeds via a Lewis acid catalyzed process through a closed six-membered transition structure. The BINOL-derived catalyst undergoes an exchange process with the original ethoxide boronate ligands. This activation mode successfully accounts for the sense and level of enantioselectivity observed experimentally. A qualitative model which accurately predicts the observed enantioselectivity has been developed and is consistent with results from our study of ketone propargylation demonstrating the reaction model's generality. The effects of replacing the BINOL framework with H8-BINOL have been rationalized.We thank Girton College, Cambridge (Research Fellowship to M.N.G.), the EPSRC (studentship to M.N.G.), and Unilever for support.This is the final published version. It first appeared at http://pubs.acs.org/doi/abs/10.1021/jo502616a

Density Functional Theory Transition-State Modeling for the Prediction of Ames Mutagenicity in 1,4 Michael Acceptors

Assessing the safety of new chemicals, without introducing the need for animal testing, is a task of great importance. The Ames test, a widely used bioassay to assess mutagenicity, can be an expensive, wasteful process with animal-derived reagents. Existing in silico methods for the prediction of Ames test results are traditionally based on chemical category formation and can lead to false positive predictions. Category formation also neglects the intrinsic chemistry associated with DNA reactivity. Activation energies and HOMO/LUMO energies for thirty 1,4 Michael acceptors were calculated using a model nucleobase and were further used to predict the Ames test result of these compounds. The proposed model builds upon existing work and examines the fundamental toxicant-target interactions using density functional theory transition-state modeling. The results show that Michael acceptors with activation energies <20.7 kcal/mol and LUMO energies < -1.85 eV are likely to act as direct mutagens upon exposure to DNA

Machine learning and semi-empirical calculations: a synergistic approach to rapid, accurate, and mechanism-based reaction barrier prediction

Modern QM modelling methods, such as DFT, have provided detailed mechanistic insights into countless reactions. However, their computational cost inhibits their ability to rapidly screen large numbers of substrates and catalysts in reaction discovery. For a C–C bond forming nitro-Michael addition, we introduce a synergistic semi-empirical quantum mechanical (SQM) and machine learning (ML) approach that allows the prediction of DFT-quality reaction barriers in minutes, even on a standard laptop using widely available modelling software. Mean absolute errors (MAEs) are obtained that are below the accepted chemical accuracy threshold of 1 kcal mol(−1) and substantially better than SQM methods without ML correction (5.71 kcal mol(−1)). Predictive power is shown to hold when the ML models are applied to an unseen set of compounds from the toxicology literature. Mechanistic insight is also achieved via the generation of full SQM transition state (TS) structures which are found to be very good approximations for the DFT-level geometries, revealing important steric interactions in some TSs. This combination of speed, accuracy, and mechanistic insight is unprecedented; current ML barrier models compromise on at least one of these important criteria

Vinylidene Homologation of Boronic Esters and its Application to the Synthesis of the Proposed Structure of Machillene

Alkenyl boronic esters are important reagents in organic synthesis. Herein, we report that these valuable products can be accessed by the homologation of boronic esters with lithiated epoxysilanes. Aliphatic and electron-rich aromatic boronic esters provided vinylidene boronic esters in moderate to high yields, while electron-deficient aromatic and vinyl boronic esters were found to give the corresponding vinyl silane products. Through DFT calculations, this divergence in mechanistic pathway has been rationalized by considering the stabilization of negative charge in the C-Si and C-B bond breaking transition states. This vinylidene homologation was used in a short six-step stereoselective synthesis of the proposed structure of machillene, however, synthetic and reported data were found to be inconsistent.</p