A focus on molecular representation learning for the prediction of chemical properties.

Molecular representation learning (MRL) is a specialized field in which deep-learning models condense essential molecular information into a vectorized form. Whereas recent research has predominantly emphasized drug discovery and bioactivity applications, MRL holds significant potential for diverse chemical properties beyond these contexts. The recently published study by King-Smith introduces a novel application of molecular representation training and compellingly demonstrates its value in predicting molecular properties (E. King-Smith, Chem. Sci., 2024, https://doi.org/10.1039/D3SC04928K). In this focus article, we will briefly delve into MRL in chemistry and the significance of King-Smith's work within the dynamic landscape of this evolving field.

Nickel/biimidazole-catalyzed electrochemical enantioselective reductive cross-coupling of aryl aziridines with aryl iodides.

Here, we report an asymmetric electrochemical organonickel-catalyzed reductive cross-coupling of aryl aziridines with aryl iodides in an undivided cell, affording ß-phenethylamines in good to excellent enantioselectivity with broad functional group tolerance. The combination of cyclic voltammetry analysis of the catalyst reduction potential as well as an electrode potential study provides a convenient route for reaction optimization. Overall, the high efficiency of this method is credited to the electroreduction-mediated turnover of the nickel catalyst instead of a metal reductant-mediated turnover. Mechanistic studies suggest a radical pathway is involved in the ring opening of aziridines. The statistical analysis serves to compare the different design requirements for photochemically and electrochemically mediated reactions under this type of mechanistic manifold.

Small Data Can Play a Big Role in Chemical Discovery.

The chemistry community is currently witnessing a surge of scientific discoveries in organic chemistry supported by machine learning (ML) techniques. Whereas many of these techniques were developed for big data applications, the nature of experimental organic chemistry often confines practitioners to small datasets. Herein, we touch upon the limitations associated with small data in ML and emphasize the impact of bias and variance on constructing reliable predictive models. We aim to raise awareness to these possible pitfalls, and thus, provide an introductory guideline for good practice. Ultimately, we stress the great value associated with statistical analysis of small data, which can be further boosted by adopting a holistic data-centric approach in chemistry.

Reactivity and Enantioselectivity in NHC Organocatalysis Provide Evidence for the Complex Role of Modifications at the Secondary Sphere.

Secondary-sphere interactions are often harnessed to control reactivity and selectivity in organometallic and enzymatic catalysis. Yet, such strategies have only recently been explicitly applied in the context of organocatalytic systems. Although increased stability, reproducibility, and selectivity were obtained in previous work using this approach, the precise mechanistic pathway promoted by secondary-sphere modification in organocatalysis remained unclear. Herein, we report a comprehensive mechanistic study on the origin of the unique reactivity patterns and stereocontrol observed with boronic acids (BAs) as secondary-sphere modifiers of N-heterocyclic carbene (NHC) organocatalysts. Kinetic experiments revealed partial order in catalyst upon the addition of BA and unusual preactivation behavior, indicating the presence of stable off-cycle catalyst aggregation and BA-base adducts. These hypotheses were supported both by computations and by a series of NMR and nonlinear effect experiments. Furthermore, computations indicated a rate-limiting, water-assisted hydrogen atom transfer mechanism. This finding led to a considerable enhancement in the experimental reaction rate while maintaining excellent enantioselectivity by adding catalytic amounts of water. Finally, computations and racemization experiments uncovered an uncommon Curtin-Hammett-controlled enantioselectivity in the presence of secondary-sphere modifiers.

Metal-Free Multicomponent Strategy for Amidine Synthesis.

Amidines are a ubiquitous class of bioactive compounds found in a wide variety of natural products; thus, efficient strategies for their preparation are in great demand. Specifically, their common structural core decorated with three substituents sets amidines as perfect candidates for multicomponent synthesis. Herein, we present a highly modular metal-free multicomponent strategy for the synthesis of sulfonyl amidines. This work was focused on selecting readily accessible reagents to facilitate the in situ formation of enamines by the addition of amines to ketones. These components were coupled with azides to provide a broad reaction scope with respect to all three coupling partners. Aromatic and aliphatic amines and ketones were tolerated under our reaction conditions. Likewise, the presence of a methyl group on the ketone was critical to reactivity, which was leveraged for the design of a highly regioselective reaction with aliphatic ketones. A biologically active compound was successfully synthesized in one step, demonstrating the practical utility of our methodology. Finally, the postulated mechanism was investigated and supported both experimentally and by means of a multivariate statistical model.

Tuning the Properties of Protein-Based Polymers Using High-Performance Orthogonal Translation Systems for the Incorporation of Aromatic Non-Canonical Amino Acids.

The incorporation of non-canonical amino acids (ncAAs) using engineered aminoacyl-tRNA synthetases (aaRSs) has emerged as a powerful methodology to expand the chemical repertoire of proteins. However, the low efficiencies of typical aaRS variants limit the incorporation of ncAAs to only one or a few sites within a protein chain, hindering the design of protein-based polymers (PBPs) in which multi-site ncAA incorporation can be used to impart new properties and functions. Here, we determined the substrate specificities of 11 recently developed high-performance aaRS variants and identified those that enable an efficient multi-site incorporation of 15 different aromatic ncAAs. We used these aaRS variants to produce libraries of two temperature-responsive PBPs-elastin- and resilin-like polypeptides (ELPs and RLPs, respectively)-that bear multiple instances of each ncAA. We show that incorporating such aromatic ncAAs into the protein structure of ELPs and RLPs can affect their temperature responsiveness, secondary structure, and self-assembly propensity, yielding new and diverse families of ELPs and RLPs, each from a single DNA template. Finally, using a molecular model, we demonstrate that the temperature-responsive behavior of RLPs is strongly affected by both the hydrophobicity and the size of the unnatural aromatic side-chain. The ability to efficiently incorporate multiple instances of diverse ncAAs alongside the 20 natural amino acids can help to elucidate the effect of ncAA incorporation on these and many other PBPs, with the aim of designing additional precise and chemically diverse polymers with new or improved properties.

Secondary-sphere modification in proline catalysis: old friend, new connection.

In this work, we exploit our strategy of in situ secondary-sphere modification of organocatalysts to improve the reactivity and selectivity of amino catalysts. Herein, the carboxylic acid moiety of proline was targeted as a site for modification under catalytic reaction conditions with boronic acids. Intermolecular aldol reactions between aromatic aldehydes and cyclopentanone were selected as a proof-of-concept because cyclopentanone as an aldol donor was often associated with decreased selectivity compared to its 6-membered ring analog, hexanone. Our secondary-sphere modification strategy, using naturally occurring L-proline amino acid, enabled reactions at room temperature with high levels of diastereo- and enantio-selectivity and short reaction times. NMR and HR-MS studies shed light on the nature of the catalyst structure and on the role of water in our reactions.

Effect of Solvents on Proline Modified at the Secondary Sphere: A Multivariate Exploration.

The critical influence of solvent effects on proline-catalyzed aldol reactions has been extensively described. Herein, we apply multivariate regression strategies to probe the influence of different solvents on an aldol reaction catalyzed by proline modified at its secondary sphere with boronic acids. In this system, both in situ binding of the boronic acid to proline and the outcome of the aldol reaction are impacted by the solvent-controlled microenvironment. Thus, with the aim of uncovering mechanistic insight and an ancillary aim of identifying methodological improvements, we designed a set of experiments, spanning 15 boronic acids in five different solvents. Based on hypothesized intermediates or interactions that could be responsible for the selectivity in these reactions, we proposed several structural configurations for the library of boronic acids. Subsequently, we compared the statistical models correlating the outcome of the reaction in different solvents with molecular descriptors produced for each of these proposed configurations. The models allude to the importance of different interactions in controlling selectivity in each of the studied solvents. As a proof-of-concept for the practicality of our approach, the models in chloroform ultimately led to lowering the ketone loading to only two equivalents while retaining excellent yield and enantio- and diastereo-selectivity.

N-Heterocyclic Carbene Triazolium Salts Containing Brominated Aromatic Motifs: Features and Synthetic Protocol.

In this work, we provide a brief overview of the role of N-aryl substituents on triazolium N-heterocyclic carbene (NHC) catalysis. This synopsis provides context for the disclosed synthetic protocol for new chiral N-heterocyclic carbene (NHC) triazolium salts with brominated aromatic motifs. Incorporating brominated aryl rings into NHC structures is challenging, probably due to the substantial steric and electronic influence these substituents exert throughout the synthetic protocol. However, these exact characteristics make it an interesting N-aryl substituent, because the electronic and steric diversity it offers could find broad use in organometallic- and organo-catalysis. Following the synthetic reaction by NMR guided the extensive modification of a known protocol to enable the preparation of these challenging NHC pre-catalysts.

Unravelling mechanistic features of organocatalysis with in situ modifications at the secondary sphere.

Secondary-sphere interactions serve a fundamental role in controlling the reactivity and selectivity of organometallic and enzymatic catalysts. However, there is a dearth of studies that explicitly incorporate secondary-sphere modifiers into organocatalytic systems. In this work, we introduce an approach for the in situ systematic modification of organocatalysts in their secondary sphere through dynamic covalent binding under the reaction conditions. As a proof-of-concept, we applied boronic acids as secondary-sphere modifiers of N-heterocyclic carbenes that contained a hydroxy handle. The bound system formed in the reaction mixture catalysed the enantioselective benzoin condensations of a challenging substrate class that contains electron-withdrawing groups. Linear regression coupled with data visualization served to pinpoint the divergent origins of enantioselectivity for different substrates and decision tree algorithms served to formulate selection criteria for the appropriate secondary-sphere modifiers. The combination of this highly modular catalytic approach with machine-learning techniques provided mechanistic insights and guided the streamlined optimization process of a gram-scale reaction at low organocatalyst loading.

Highlights from the 53rd EUCHEM conference on stereochemistry, Bürgenstock, Switzerland, May 2018.

When we first heard of the Bürgenstock conference it was described as a guarded meeting in a remote location, undisturbed by modern diversions, with mysterious customs and a secret handshake. All of these rumors turned out to be completely true. We arrived at an undisclosed location and three young men, who knew our names upon sight, greeted us and gave us an agenda in which we discovered the identity of the speakers, moderators and other participants. We then had a few moments to bask in their glory before being treated to a delicious dose of chemistry. During the banquet, before the first lecture, this year's president, Prof. Ilan Marek, gave the opening address from a balcony reserved only for these meetings, rumors hold that it stands vacant all year in anticipation. He mentioned several of the traditions of the meeting, which we are not allowed to share of course, and described the joy of putting together this year's exciting program with the help of an exceptional organizing committee that included Prof. Cristina Nevado, Prof. Christian Bochet, Dr Fabrice Gallou and Dr Alain De Mesmaeker. He also introduced this year's guest of honor, Prof. Yitzhak Apeloig, and wished the best luck to the current Vice President and future President, Prof. Véronique Gouverneur, not only for preparing the 54th Bürgenstock Conference, but also with her duty this year, maintaining the good weather for the whole week. Although the official title of the conference is the EUCHEM conference on stereochemistry, the topics covered span a broad range of cutting edge chemical transformations and insights, which can appeal to anyone working in chemistry and its interfaces with other disciplines. We will briefly describe each of the talks following one of our favorite citable quotes from these inspiring speakers.

Developing a Modern Approach To Account for Steric Effects in Hammett-Type Correlations.

The effects of aryl ring ortho-, meta-, and para-substitution on site selectivity and enantioselectivity were investigated in the following reactions: (1) enantioselective Pd-catalyzed redox-relay Heck reaction of arylboronic acids, (2) Pd-catalyzed ß-aryl elimination of triarylmethanols, and (3) benzoylformate decarboxylase-catalyzed enantioselective benzoin condensation of benzaldehydes. Through these studies, it is demonstrated that the electronic and steric effects of various substituents on selectivities obtained in these reactions can be described by NBO charges, the IR carbonyl stretching frequency, and Sterimol values of various substituted benzoic acids. An extended compilation of NBO charges and IR carbonyl stretching frequencies of various substituted benzoic acids was used as an alternative to Hammett values. These parameters provide a correlative tool that allows for the analysis of a much greater range of substituent effects because they can also account for proximal and remote steric effects.

Parameterization of phosphine ligands reveals mechanistic pathways and predicts reaction outcomes.

The mechanistic foundation behind the identity of a phosphine ligand that best promotes a desired reaction outcome is often non-intuitive, and thus has been addressed in numerous experimental and theoretical studies. In this work, multivariate correlations of reaction outcomes using 38 different phosphine ligands were combined with classic potentiometric analyses to study a Suzuki reaction, for which the site selectivity of oxidative addition is highly dependent on the nature of the phosphine. These studies shed light on the generality of hypotheses regarding the structural influence of different classes of phosphine ligands on the reaction mechanism(s), and deliver a methodology that should prove useful in future studies of phosphine ligands.

The Development of Multidimensional Analysis Tools for Asymmetric Catalysis and Beyond.

In most modern organic chemistry reports, including many of ours, reaction optimization schemes are typically presented to showcase how reaction conditions have been tailored to augment the reaction's yield and selectivity. In asymmetric catalysis, this often involves evaluation of catalyst, solvent, reagent, and, sometimes, substrate features. Such an article will then detail the process's scope, which mainly focuses on its successes and briefly outlines the "limitations". These limitations or poorer-performing substrates are occasionally the result of obvious, significant changes to structure (e.g., a Lewis basic group binds to a catalyst), but frequently, a satisfying explanation for inferior performance is not clear. This is one of several reasons such results are not often reported. These apparent outliers are also commonplace in the evaluation of catalyst structure, although most of this information is placed in the Supporting Information. These practices are unfortunate because results that appear at first glance to be peculiar or poor are considerably more interesting than ones that follow obvious or intuitive trends. In other words, all of the data from an optimization campaign contain relevant information about the reaction under study, and the "outliers" may be the most revealing. Realizing the power of outliers as an entry point to entirely new reaction development is not unusual. Nevertheless, the concept that no data should be wasted when considering the underlying phenomena controlling the observations of a given reaction is at the heart of the strategy we describe in this Account. The idea that one can concurrently optimize a reaction to expose the structural features that control its outcomes would represent a transformative addition to the arsenal of catalyst development and, ultimately, de novo design. Herein we outline the development of a recently initiated program in our lab that unites optimization with mechanistic interrogation by correlating reaction outputs (e.g., electrochemical potential or enantio-, site, or chemoselectivity) with structural descriptors of the molecules involved. The ever-evolving inspiration for this program is rooted in outliers of classical linear free energy relationships. These outliers encouraged us to ask questions about the parameters themselves, suggest potential interactions at the source of the observed effects, and, of particular applicability, identify more sophisticated physical organic descriptors. Throughout this program, we have integrated techniques from disparate fields, including synthetic methodology development, mechanistic investigations, statistics, computational chemistry, and data science. The implementation of many of these strategies is described, and the resulting tools are illustrated in a wide range of case studies, which include data sets with simultaneous and multifaceted changes to the reagent, substrate, and catalyst structures. This tactic constitutes a modern approach to physical organic chemistry wherein no data are wasted and mechanistic hypotheses regarding sophisticated processes can be developed and probed.

Enantiodivergent Fluorination of Allylic Alcohols: Data Set Design Reveals Structural Interplay between Achiral Directing Group and Chiral Anion.

Enantioselectivity values represent relative rate measurements that are sensitive to the structural features of the substrates and catalysts interacting to produce them. Therefore, well-designed enantioselectivity data sets are information rich and can provide key insights regarding specific molecular interactions. However, if the mechanism for enantioselection varies throughout a data set, these values cannot be easily compared. This premise, which is the crux of free energy relationships, exposes a challenging issue of identifying mechanistic breaks within multivariate correlations. Herein, we describe an approach to addressing this problem in the context of a chiral phosphoric acid catalyzed fluorination of allylic alcohols using aryl boronic acids as transient directing groups. By designing a data set in which both the phosphoric and boronic acid structures were systematically varied, key enantioselectivity outliers were identified and analyzed. A mechanistic study was executed to reveal the structural origins of these outliers, which was consistent with the presence of several mechanistic regimes within the data set. While 2- and 4-substituted aryl boronic acids favored the (R)-enantiomer with most of the studied catalysts, meta-alkoxy substituted aryl boronic acids resulted in the (S)-enantiomer when used in combination with certain (R)-phosphoric acids. We propose that this selectivity reversal is the result of a lone pair-π interaction between the substrate ligated boronic acid and the phosphate. On the basis of this proposal, a catalyst system was identified, capable of producing either enantiomer in high enantioselectivity (77% (R)-2 to 92% (S)-2) using the same chiral catalyst by subtly changing the structure of the achiral boronic acid.

Organic chemistry. A data-intensive approach to mechanistic elucidation applied to chiral anion catalysis.

Knowledge of chemical reaction mechanisms can facilitate catalyst optimization, but extracting that knowledge from a complex system is often challenging. Here, we present a data-intensive method for deriving and then predictively applying a mechanistic model of an enantioselective organic reaction. As a validating case study, we selected an intramolecular dehydrogenative C-N coupling reaction, catalyzed by chiral phosphoric acid derivatives, in which catalyst-substrate association involves weak, noncovalent interactions. Little was previously understood regarding the structural origin of enantioselectivity in this system. Catalyst and substrate substituent effects were probed by means of systematic physical organic trend analysis. Plausible interactions between the substrate and catalyst that govern enantioselectivity were identified and supported experimentally, indicating that such an approach can afford an efficient means of leveraging mechanistic insight so as to optimize catalyst design.