Alistair John Sterling

Engineered hemoproteins have emerged as powerful biocatalysts for asymmetric, new-to-nature carbene transfer reactions. Despite significant advances in biocatalytic cyclopropanation reactions, these transformations have been largely limited to diazo-based carbene precursors with electron-deficient substituents. Herein, we report a biocatalytic strategy for stereoselective cyclopropanation of olefins using gem-dibromoalkanes as carbene precursors. This method enables the asymmetric cyclopropanation of vinylarenes bearing both electron-donating and electron-withdrawing groups to afford trans-1,2-diarylcyclopropanes in up to >99% yield and with high diastereo- and enantiodivergent selectivity (>99:1 d.r.; up to >99% ee). This strategy could be further applied to the construction of a variety of three-dimensional, sp3-rich spirocyclic scaffolds via cyclopropanation of exocyclic olefins, and it could be extended to σ-bond carbene insertions. Mechanistic studies support the formation of an α-halo radical intermediate via either a chemical or an enzyme-mediated reduction of benzylic gem-dibromides as a key step for generation of the reactive heme-carbenoid species implicated in carbene transfer. This work expands the scope of biocatalytic carbene transfer reactions, and it paves the way to the exploitation of gem-dibromoalkanes and other non-diazo carbene precursors in enzyme-catalyzed new-to-nature transformations.

Asymmetric C(sp³)-S bonds are found in many bioactive natural products and pharmaceuticals. Despite progress in the development of methods for asymmetric S-H carbene insertion reactions, this transformation remains challenging and elusive in the presence of pyridotriazoles as carbene donor reagents. Herein, we report a biocatalytic platform for the stereoselective construction of asymmetric C(sp³)-S bonds via both a S-H carbene insertion (up to >99% ee) and a [2,3]-sigmatropic rearrangement reaction by harnessing engineered myoglobin catalysts in combination with pyridotriazole-based carbene precursors. These transformations enable the synthesis of valuable α-pyridyl sulfides with broad substrate scope, high yields, and good to excellent stereocontrol. Intriguingly, mechanistic studies show that the S-H insertion reaction proceeds via a radical pathway, while a polar, two-electron mechanism is exploited by the enzyme for mediating [2,3]-sigmatropic rearrangement reaction, thus revealing a remarkable versatility of the hemoprotein toward operating via both a radical and nonradical pathway. This methodology provides an efficient and sustainable route to valuable pyridine-containing chiral sulfides while unveiling a dual-reactivity mode of a hemoprotein catalyst in an abiological carbene transfer reaction.

The selectivity of Pd, Pt, Rh, and Ir complexes for the oxidative additions of carbon–hydrogen vs. carbon–halogen bonds is controlled by differences in thermodynamics, electronic properties, and degrees of distortions in the transition states.

The role of machine learning in computational chemistry is growing rapidly, promising expedited tasks while improving prediction accuracy. However, the interface of newly developed machine-learned interatomic potentials (MLIPs) with existing computational chemistry workflows based on quantum mechanics (QM) remains a challenge. Here, we introduce ChemRefine as a modular automated computational chemistry platform that enables researchers to seamlessly integrate the next generation of MLIPs into both complex and high-throughput computational workflows. We road-test ChemRefine on multiple real-world computational tasks, including host-guest binding for transmembrane anion transporter design, redox and photophysical property predictions for enzyme cofactors and photocatalysts, conformational sampling of organometallic complexes, and transition state finding for "click" reaction design. MLIPs can be automatically trained, fine-tuned, and deployed during workflows, accelerating simulations while maintaining prediction accuracy. In all cases, multiple computational tasks are condensed into a single reproducible workflow. To simplify the use of ChemRefine, we also introduce a custom large language model, ChemRefineGPT, that generates all required input and configuration files based on a natural language description of the desired workflow.

The role of machine learning (ML) in computational chemistry is growing rapidly, promising to expedite many routine tasks while improving prediction accuracy. However, the interface of newly developed machine-learned interatomic potentials (MLIPs) with existing computational chemistry workflows based on quantum mechanics (QM) remains a challenge. Here, we introduce ChemRefine as a modular automated computational chemistry platform that enables researchers to seamlessly integrate the next generation of MLIPs into their computational workflows. We road-test ChemRefine on multiple computational tasks commonly encountered by researchers, including conformational sampling, host–guest binding, redox and photophysical property prediction, transition state finding, molecular dynamics spawning, and the creation of optimal microsolvation ensembles. We also introduce a feature that enables automatic training/fine-tuning and deployment of MLIPs during workflows, enabling computational chemists to accelerate their simulations while maintaining prediction accuracy. To simplify the use of ChemRefine, we also introduce a custom large language model, ChemRefineGPT, that generates all required input and configuration files based on a natural language description of the desired workflow.

Understanding the impact of O₂ during a carbon capture process is vital for designing robust, cost-effective materials for carrying it out. However, mechanistic studies of the O₂-induced degradation of materials are not easily undertaken owing to the complex sequential reaction pathways that arise. Here, we report comprehensive mechanistic investigations of the O₂-induced degradation of diamine-appended metal-organic frameworks (MOFs) exhibiting cooperative CO₂ adsorption. Oxygen exposure experiments were performed on seven different diamine-appended MOFs, including e-2-Mg₂(dobpdc) (e-2 = N-ethylethylenediamine, dobpdc^4- = 4,4'-dioxidobiphenyl-3,3'-dicarboxylate), under various temperatures and O₂ pressures. These experiments show that diamine degradation inhibits CO₂ chemisorption and that the degradation rate is significantly influenced by the diamine structure. In contrast, the parent frameworks remain essentially intact upon O₂ exposure. Detailed characterization of O₂-exposed e-2-Mg₂(dobpdc) revealed the formation of various degradation products, including acetaldehyde, carbon dioxide, water, ethylamine, and other aldehyde- and imine-containing species. Together, these observations suggest that diamine degradation occurs via C-N bond cleavage through pathways involving C-centered radicals. Furthermore, computational evaluation of the initiation and propagation pathways for amine degradation in diamine-appended MOFs indicates that (i) degradation is likely initiated by OH^•, (ii) carbon-centered radicals generated via radical transfer reactions react with O₂, leading to amine degradation, and (iii) the rate-limiting step of the degradation reactions likely involves O-O bond cleavage. Overall, these mechanistic insights could inform strategies for mitigating O₂-induced amine degradation in next-generation carbon capture technologies.

Understanding the impact of O2 during a carbon capture process is vital for designing robust, cost-effective materials for carrying it out. However, mechanistic studies of the O2-induced degradation of materials are not easily undertaken owing to the complex sequential reaction pathways that arise. Here, we report comprehensive mechanistic investigations of the O2-induced degradation of diamine-appended metal–organic frameworks (MOFs) exhibiting cooperative CO2 adsorption. Oxygen exposure experiments were performed on seven different diamine-appended MOFs, includ-ing e-2–Mg2(dobpdc) (e-2 = N-ethylethylenediamine, dobpdc4− = 4,4′-dioxidobiphenyl-3,3′-dicarboxylate), under various temperatures and O2 pressures. These experiments show that diamine degradation inhibits CO2 chemisorption, and that the degradation rate is significantly influenced by the diamine structure. In contrast, the parent frame-works remain essentially intact upon O2 exposure. Detailed characterization of O2-exposed e-2–Mg2(dobpdc) revealed the formation of various degradation products, including acetaldehyde, carbon dioxide, water, ethylamine, and other aldehyde- and imine-containing species. Together, these observations suggest that diamine degradation occurs via C–N bond cleavage through pathways involving C-centered radicals. Furthermore, computational evaluation of the initiation and propagation pathways for amine degradation in diamine-appended MOFs indicates that: (i) degradation is likely initiated by OH•, (ii) carbon-centered radicals generated via radical transfer reactions react with O2, leading to amine degradation, and (iii) the rate-limiting step of the degradation reactions likely involves O–O bond cleavage. Overall, these mechanistic insights could inform strategies for mitigating O2-induced amine degradation in next-generation carbon capture technologies.

A nickel-catalyzed, branched-selective hydroalkylation of alkenes using diazo compounds has been developed. This protocol enables the functionalization of both activated and unactivated alkenes, in both directed and nondirected manners. Mono-, di-, and trisubstituted alkenes can be effectively transformed. Highly diastereoselective hydroalkylations have also been demonstrated. The method provides a novel approach for introducing an α-carbonyl moiety to alkenes, which is currently inaccessible by existing methods. Preliminary mechanistic investigations suggest a carbene-type mechanism, which is unusual for nickel catalysis.

The release of strain energy is a fundamental driving force for organic reactions. However, absolute strain energy alone is an insufficient predictor of reactivity, evidenced by the similar ring strain but disparate reactivity of cyclopropanes and cyclobutanes. In this work, we demonstrate that electronic delocalization is a key factor that operates alongside strain release to boost, or even dominate, reactivity. This delocalization principle extends across a wide range of molecules containing three-membered rings such as epoxides, aziridines, and propellanes and also applies to strain-driven cycloaddition reactions. Our findings lead to a "rule of thumb" for the accurate prediction of activation barriers in such systems, which can be easily applied to reactions involving many of the strained building blocks commonly encountered in organic synthesis, medicinal chemistry, polymer science, and bioconjugation. Given the significance of electronic delocalization in organic chemistry, for example in aromatic π-systems and hyperconjugation, we anticipate that this concept will serve as a versatile tool to understand and predict organic reactivity.

The chemical bond is the cornerstone of chemistry, providing a conceptual framework to understand and predict the behavior of molecules in complex systems. However, the fundamental origin of chemical bonding remains controversial and has been responsible for fierce debate over the past century. Here, we present a unified theory of bonding, using a separation of electron delocalization effects from orbital relaxation to identify three mechanisms [node-induced confinement (typically associated with Pauli repulsion, though more general), orbital contraction, and polarization] that each modulate kinetic energy during bond formation. Through analysis of a series of archetypal bonds, we show that an exquisite balance of energy-lowering delocalizing and localizing effects are dictated simply by atomic electron configurations, nodal structure, and electronegativities. The utility of this unified bonding theory is demonstrated by its application to explain observed trends in bond strengths throughout the periodic table, including main group and transition metal elements.