A systematic investigation of quaternary ammonium ions as asymmetric phase-transfer catalysts. Synthesis of catalyst libraries and evaluation of catalyst activity

Enantioselective Phase-Transfer-Catalyzed Synthesis of Spirocyclic Azetidine Oxindoles

Spiro-3,2'-azetidine oxindoles combine two independently important pharmacophores in an understudied spirocyclic motif that is attractive for medicinal chemistry. Here, the enantioselective synthesis of these structures is achieved in up to 2:98 er through intramolecular C-C bond formation, involving activation of the substrate with a novel SF5-containing chiral cation phase-transfer (PT) catalyst. The products are readily elaborated/deprotected to afford medicinally relevant enantioenriched compounds. Control experiments suggest an interfacial PT mechanism, whereby catalytic asymmetric induction is achieved through the activation of the chloride leaving group.

Synthesis and Catalytic Activity of Bifunctional Phase-Transfer Organocatalysts Based on Camphor

Ten novel bifunctional quaternary ammonium salt phase-transfer organocatalysts were synthesized in four steps from (+)-camphor-derived 1,3-diamines. These quaternary ammonium salts contained either (thio)urea or squaramide hydrogen bond donor groups in combination with either trifluoroacetate or iodide as the counteranion. Their organocatalytic activity was evaluated in electrophilic heterofunctionalizations of β-keto esters and in the Michael addition of a glycine Schiff base with methyl acrylate. α-Fluorination and chlorination of β-keto esters proceeded with full conversion and low enantioselectivities (up to 29% ee). Similarly, the Michael addition of a glycine Schiff base with methyl acrylate proceeded with full conversion and up to 11% ee. The new catalysts have been fully characterized; the stereochemistry at the C-2 chiral center was unambiguously determined.

(Thio)urea containing chiral ammonium salt catalysts

(Thio)-urea-containing bifunctional quaternary ammonium salts emerged as powerful non-covalently interacting organocatalysts over the course of the last decade. The most commonly employed catalysts in this field are either based on Cinchona alkaloids, α-amino acids, or trans-cyclohexane-1,2-diamine. Our group has been heavily engaged in the design and use of such catalysts, i. e. trans-cyclohexane-1,2-diamine-based ones for around 10 years now, and it is therefore the intention of this short personal account to provide an overview of the, at least in our opinion, most significant and pioneering achievements in this field by looking on catalyst design and asymmetric method development, with a special focus on our own contributions.

Study of Ground State Interactions of Enantiopure Chiral Quaternary Ammonium Salts and Amides, Nitroalkanes, Nitroalkenes, Esters, Heterocycles, Ketones and Fluoroamides

Chiral phase-transfer catalysis provides high level of enantiocontrol, however no experimental data showed the interaction of catalysts and substrates. 1 H NMR titration was carried out on Cinchona and Maruoka ammonium bromides vs. nitro, carbonyl, heterocycles, and N-F containing compounds. It was found that neutral organic species and quaternary ammonium salts interacted via an ensemble of catalyst + N-C-H and (sp2 )C-H, specific for each substrate studied. The correspondent BArF salts interacted with carbonyls via a diverse set of + N-C-H and (sp2 )C-H compared to bromides. This data suggests that BArF ammonium salts may display a different enantioselectivity profile. Although not providing quantitative data for the affinity constants, the data reported proofs that chiral ammonium salts coordinate with substrates, prior to transition state, through specific C-H positions in their structures, providing a new rational to rationalize the origin of enantioselectivity in their catalyses.

An Ion-Pairing Approach to Stereoselective Metal-Free Ring-Opening Metathesis Polymerization

Stereochemistry can have a profound impact on polymer and materials properties. Unfortunately, straightforward methods for realizing high levels of stereocontrolled polymerizations are often challenging to achieve. In a departure from traditional metal-mediated ring-opening metathesis polymerization (ROMP), we discovered a remarkably simple method for controlling alkene stereochemistry in photoredox mediated metal-free ROMP. Ion-pairing, initiator sterics, and solvation effects each had profound impact on the stereochemistry of polynorbornene (PNB). Simple modifications to the reaction conditions produced PNB with trans alkene content of 25 to >98 %. High cis content was obtained from relatively larger counterions, toluene as solvent, low temperatures (-78 °C), and initiators with low Charton values. Conversely, smaller counterions, dichloromethane as solvent, and enol ethers with higher Charton values enabled production of PNB with high trans content. Data from a combined experimental and computational investigation are consistent with the stereocontrolling step of the radical cationic mechanism proceeding under thermodynamic control.

Dreams, False Starts, Dead Ends, and Redemption: A Chronicle of the Evolution of a Chemoinformatic Workflow for the Optimization of Enantioselective Catalysts

Catalyst design in enantioselective catalysis has historically been driven by empiricism. In this endeavor, experimentalists attempt to qualitatively identify trends in structure that lead to a desired catalyst function. In this body of work, we lay the groundwork for an improved, alternative workflow that uses quantitative methods to inform decision making at every step of the process. At the outset, we define a library of synthetically accessible permutations of a catalyst scaffold with the philosophy that the library contains every potential catalyst we are willing to make. To represent these chiral molecules, we have developed general 3D representations, which can be calculated for tens of thousands of structures. This defines the total chemical space of a given catalyst scaffold; it is constructed on the basis of catalyst structure only without regard to a specific reaction or mechanism. As such, any algorithmic subset selection method, which is unsupervised (i.e., only considers catalyst structure), should provide an ideal initial screening set for any new reaction that can be catalyzed by that scaffold. Notably, because this design strategy, the same set of catalysts can be used for any reaction that can be catalyzed with that parent catalyst scaffold. These are tested experimentally, and statistical learning tools can be used to create a model relating catalyst structure to catalyst function. Further, this model can be used to predict the performance of each catalyst candidate in the greater database of virtual catalyst candidates. In this way, it is possible estimate the performance of tens of thousands of catalysts by experimentally testing a smaller subset. Using error assessment metrics, it is possible to understand the confidence in new predictions. An experimentalist using this tool can balance the predicted results (reward) with the prediction confidence (risk) when deciding which catalysts to synthesize next in an optimization campaign. These catalysts are synthesized and tested experimentally. At this stage, either the optimization is a success or the predicted values were incorrect and further optimization is required. In the case of the latter, the information can be fed back into the statistical learning model to refine the model, and this iterative process can be used to determine the optimal catalyst. In this body of work, we not only establish this workflow but quantitatively establish how best to execute each step. Herein, we evaluate several 3D molecular representations to determine how best to represent molecules. Several selection protocols are examined to best decide which set of molecules can be used to represent the library of interest. In addition, the number of reactions needed to make accurate, statistical learning models is evaluated. Taken together these components establish a tool ready to progress from the development stage to the utility stage. As such, current research endeavors focus on applying these tools to optimize new reactions.

Trialkylammonium salt degradation: implications for methylation and cross-coupling

Trialkylammonium (most notably N,N,N-trimethylanilinium) salts are known to display dual reactivity through both the aryl group and the N-methyl groups. These salts have thus been widely applied in cross-coupling, aryl etherification, fluorine radiolabelling, phase-transfer catalysis, supramolecular recognition, polymer design, and (more recently) methylation. However, their application as electrophilic methylating reagents remains somewhat underexplored, and an understanding of their arylation versus methylation reactivities is lacking. This study presents a mechanistic degradation analysis of N,N,N-trimethylanilinium salts and highlights the implications for synthetic applications of this important class of salts. Kinetic degradation studies, in both solid and solution phases, have delivered insights into the physical and chemical parameters affecting anilinium salt stability. ¹H NMR kinetic analysis of salt degradation has evidenced thermal degradation to methyl iodide and the parent aniline, consistent with a closed-shell S_N2-centred degradative pathway, and methyl iodide being the key reactive species in applied methylation procedures. Furthermore, the effect of halide and non-nucleophilic counterions on salt degradation has been investigated, along with deuterium isotope and solvent effects. New mechanistic insights have enabled the investigation of the use of trimethylanilinium salts in O-methylation and in improved cross-coupling strategies. Finally, detailed computational studies have helped highlight limitations in the current state-of-the-art of solvation modelling of reaction in which the bulk medium undergoes experimentally observable changes over the reaction timecourse.

The dual reactivity of N,N,N-trimethylanilinium salts towards arylation and methylation is decoupled in this mechanistic investigation to enable more strategic application of these salts in either reaction class.

Asymmetric α-Hydroxylation of α-Aryl-δ-lactams with Molecular Oxygen under Phase-Transfer Conditions

An asymmetric synthesis of α-aryl-α-hydroxy-δ-lactams via phase-transfer-catalyzed hydroxylation with molecular oxygen is described. High yields and high enantioselectivities were achieved using 2,2-diarylvinyl group as an achiral auxiliary. This strategy allows facile access to α-aryl-α-hydroxy-δ-lactam derivatives containing a chiral quaternary center.

Computational methods for training set selection and error assessment applied to catalyst design: guidelines for deciding which reactions to run first and which to run next

Different subset selection methods are examined to guide catalyst selection in optimization campaigns. Error assessment methods are used to quantitatively inform selection of new catalyst candidates from in silico libraries of catalyst structures.

Development of a Computer-Guided Workflow for Catalyst Optimization. Descriptor Validation, Subset Selection, and Training Set Analysis

Modern, enantioselective catalyst development is driven largely by empiricism. Although this approach has fostered the introduction of most of the existing synthetic methods, it is inherently limited by the skill, creativity, and chemical intuition of the practitioner. Herein, we present a complementary approach to catalyst optimization in which statistical methods are used at each stage to streamline development. To construct the optimization informatics workflow, a number of critical components had to be subjected to rigorous validation. First, the critically important molecular descriptors were validated in two case studies to establish the importance of conformation-dependent molecular representations. Next, with a large data set available, it was possible to investigate the amount of data necessary to make predictive models with different modeling methods. Given the commercial availability of many catalyst structures, it was possible to compare models generated with algorithmically selected training sets and commercially available training sets. Finally, the augmentation of limited data sets is demonstrated in a method informed by unsupervised learning to restore the accuracy of the generated models.

Quantitative Structure-Selectivity Relationships in Enantioselective Catalysis: Past, Present, and Future

The dawn of the 21st century has brought with it a surge of research related to computer-guided approaches to catalyst design. In the past two decades, chemoinformatics, the application of informatics to solve problems in chemistry, has increasingly influenced prediction of activity and mechanistic investigations of organic reactions. The advent of advanced statistical and machine learning methods, as well as dramatic increases in computational speed and memory, has contributed to this emerging field of study. This review summarizes strategies to employ quantitative structure-selectivity relationships (QSSR) in asymmetric catalytic reactions. The coverage is structured by initially introducing the basic features of these methods. Subsequent topics are discussed according to increasing complexity of molecular representations. As the most applied subfield of QSSR in enantioselective catalysis, the application of local parametrization approaches and linear free energy relationships (LFERs) along with multivariate modeling techniques is described first. This section is followed by a description of global parametrization methods, the first of which is continuous chirality measures (CCM) because it is a single parameter derived from the global structure of a molecule. Chirality codes, global, multivariate descriptors, are then introduced followed by molecular interaction fields (MIFs), a global descriptor class that typically has the highest dimensionality. To highlight the current reach of QSSR in enantioselective transformations, a comprehensive collection of examples is presented. When combined with traditional experimental approaches, chemoinformatics holds great promise to predict new catalyst structures, rationalize mechanistic behavior, and profoundly change the way chemists discover and optimize reactions.

Evaluating continuous chirality measure as a 3D descriptor in chemoinformatics applied to asymmetric catalysis

Continuous Chirality Measure (CCM) is a computational metric by which to quantify the chirality of a compound. In enantioselective catalysis, prior work has postulated that CCM is correlated to selectivity and can be used to understand which structural features dictate catalyst efficacy. Herein, the investigation of CCM as a metric capable of guiding catalyst optimization is explored. Conformer-dependent CCM is also explored. Finally, CCM is used with Sterimol parameters to significantly improve the performance of Random Forest models.

Prediction of higher-selectivity catalysts by computer-driven workflow and machine learning

Catalyst design in asymmetric reaction development has traditionally been driven by empiricism, wherein experimentalists attempt to qualitatively recognize structural patterns to improve selectivity. Machine learning algorithms and chemoinformatics can potentially accelerate this process by recognizing otherwise inscrutable patterns in large datasets. Herein we report a computationally guided workflow for chiral catalyst selection using chemoinformatics at every stage of development. Robust molecular descriptors that are agnostic to the catalyst scaffold allow for selection of a universal training set on the basis of steric and electronic properties. This set can be used to train machine learning methods to make highly accurate predictive models over a broad range of selectivity space. Using support vector machines and deep feed-forward neural networks, we demonstrate accurate predictive modeling in the chiral phosphoric acid-catalyzed thiol addition to N-acylimines.

Computational prediction of chemical reactions: current status and outlook

Over the past few decades, various computational methods have become increasingly important for discovering and developing novel drugs. Computational prediction of chemical reactions is a key part of an efficient drug discovery process. In this review, we discuss important parts of this field, with a focus on utilizing reaction data to build predictive models, the existing programs for synthesis prediction, and usage of quantum mechanics and molecular mechanics (QM/MM) to explore chemical reactions. We also outline potential future developments with an emphasis on pre-competitive collaboration opportunities.

Chiral phase-transfer catalysis in the asymmetric α-heterofunctionalization of prochiral nucleophiles

Chiral phase-transfer catalysis is one of the major catalytic principles in asymmetric catalysis. A broad variety of different catalysts and their use for challenging applications have been reported over the last decades. Besides asymmetric C–C bond forming reactions the use of chiral phase-transfer catalysts for enantioselective α-heterofunctionalization reactions of prochiral nucleophiles became one of the most important field of application of this catalytic principle. Based on several highly spectacular recent reports, we thus wish to discuss some of the most important achievements in this field within the context of this review.

Chiral Tertiary Sulfonium Salts as Effective Catalysts for Asymmetric Base-Free Neutral Phase-Transfer Reactions

Although chiral quaternary ammonium and phosphonium salts are commonly used for asymmetric organocatalysis, the catalytic ability of chiral tertiary sulfonium salts has yet to be demonstrated in asymmetric synthesis. Herein, we show that chiral bifunctional trialkylsulfonium salts catalyze highly enantioselective conjugate additions of 3-substituted oxindoles to maleimides under base-free neutral phase-transfer conditions.

A new generation of chiral phase-transfer catalysts

Phase-transfer catalysis has long been recognized as a versatile method for organic synthesis. In particular, over more than the past three decades, asymmetric phase-transfer catalysis based on the use of structurally well-defined chiral catalysts has become a topic of great scientific interest. Although various effective chiral catalysts have already been reported and these catalysts were utilized for practical asymmetric transformations, further design and development of new chiral phase-transfer catalysts are still attractive research subjects in organic chemistry due to the high utility and practicability of phase-transfer-catalyzed reactions. This review focuses on the recent examples of newly designed effective chiral phase-transfer catalysts.

Asymmetric tandem hemiaminal-heterocyclization-aza-Mannich reaction of 2-formylbenzonitriles and amines using chiral phase transfer catalysis: an experimental and theoretical study

The first asymmetric synthesis of 3-amino-substituted isoindolinones was accomplished via cascade hemiaminal-heterocyclization-intramolecular aza-Mannich reaction of amines and 2-formylbenzonitriles using chiral phase transfer conditions (PTC).

Asymmetric intramolecular α-cyclopropanation of aldehydes using a donor/acceptor carbene mimetic

Enantioselective α-alkylation of carbonyl is considered as one of the most important processes for asymmetric synthesis. Common alkylation agents, that is, alkyl halides, are notorious substrates for both Lewis acids and organocatalysts. Recently, olefins emerged as a benign alkylating species via photo/radical mechanisms. However, examples of enantioselective alkylation of aldehydes/ketones are scarce and direct asymmetric dialkylation remains elusive. Here we report an intramolecular α-cyclopropanation reaction of olefinic aldehydes to form chiral cyclopropane aldehydes. We demonstrate that an α-iodo aldehyde can function as a donor/acceptor carbene equivalent, which engages in a formal [2+1] annulation with a tethered double bond. Privileged bicyclo[3.1.0]hexane-type scaffolds are prepared in good optical purity using a chiral amine. The synthetic utility of the products is demonstrated by versatile transformations of the bridgehead formyl functionality. We expect the concept of using α-iodo iminium as a donor/acceptor carbene surrogate will find wide applications in chemical reaction development.

The formation of chiral centres adjacent to carbonyl groups is a highly challenging task in asymmetric catalysis. Here, the authors report the asymmetric diakylation of carbonyls via an intramolceular α-cyclopropanation procedure.

Phase-transfer and other types of catalysis with cyclopropenium ions

This work establishes the cyclopropenium ion as a viable platform for efficient phase-transfer catalysis of a diverse range of organic transformations. The amenability of these catalysts to large-scale synthesis and structural modification is demonstrated. Evaluation of the molecular structure of an optimal catalyst reveals some unique structural features of these systems. Finally, a discussion of electronic charge distribution underscores an important consideration for catalyst design.

Redefining q: quaternary ammonium cross sectional area (XSA) as a general descriptor for transport-limiting PTC rate approximations

The relationships of several key molecular descriptors with the rate of the O'Donnell alkylation under phase transfer catalysis (PTC) have been investigated. The most common parameter used to predict PTC rates, the ammonium ion accessibility, q , is defined in such a way that limits its use to straight-chain tetraalkylammonium catalysts. To find a general descriptor of rate, eight linear, symmetrical tetraalkylammonium cations were examined to determine if a model containing broadly applicable descriptors could be found. The catalytic activity of these salts was determined under PTC conditions (operating under an interfacial, transport-rate limiting mechanism) and was compared with these molecular descriptors. Models could be generated from the ammonium ion accessibility parameter q and the amphiphilic cross sectional area descriptor (XSA), and each gave a correlative model predicting the rate of alkylation. However, a similar model cannot be generated from a descriptor that is a direct measure of ammonium ion accessibility, the solvent accessible ammonium surface area (NC4_SA). These models lead to the conclusion that q must approximate catalyst properties other than ammonium ion accessibility. Additionally, the relationship between XSA and rate demonstrates that XSA approximates the complex behavior of ammonium ions at the interfacial region of a biphasic system, allowing for its use as a general descriptor for transport-limiting PTC rate approximations.