Enantiodivergent Pd-catalyzed C-C bond formation enabled through ligand parameterization

Selective recognition between aromatics and aliphatics by cage-shaped borates supported by a machine learning approach

Selective recognition between hydrocarbon moieties is a longstanding issue. Although we developed a π-pocket Lewis acid catalyst with high selectivity for aromatic aldehydes over aliphatic ones, a general strategy for catalyst design remains elusive. As an approach that transfers the molecular recognition based on multiple cooperative non-covalent interactions within the π-pocket to a rational catalyst design, herein, we demonstrate Lewis acid catalysts showing improved selectivity through the support of an ensemble algorithm with random forest, Ada Boost, and XG Boost as a machine learning (ML) approach. Using 7963 explanatory variables extracted from model hetero-Diels-Alder reactions, the ensemble algorithm predicted the chemoselectivity of unlearned catalysts. Experiments confirmed the prediction. The proposed catalyst shows the highest selective recognition, reminiscing enzymatic catalytic activity. Additionally, a SHapley Additive exPlanations (SHAP) method suggested that the selectivity originates from the polarizability and three-dimensional size of the catalyst. This insight leads to rational design guidelines for Lewis acid catalysts with dispersion forces.

Leveraging Limited Experimental Data with Machine Learning: Differentiating a Methyl from an Ethyl Group in the Corey-Bakshi-Shibata Reduction

We present a case study on how to improve an existing metal-free catalyst for a particularly difficult reaction, namely, the Corey-Bakshi-Shibata (CBS) reduction of butanone, which constitutes the classic and prototypical challenge of being able to differentiate a methyl from an ethyl group. As there are no known strategies on how to address this challenge, we leveraged the power of machine learning by constructing a realistic (for a typical laboratory) small, albeit high-quality, data set of about 100 reactions (run in triplicate) that we used to train a model in combination with a key-intermediate graph (of substrate and catalyst) to predict the differences in Gibbs activation energies ΔΔG‡ of the enantiomeric reaction paths. With the help of this model, we were able to select and subsequently screen a small selection of catalysts and increase the selectivity for the CBS reduction of butanone to 80% enantiomeric excess (ee), the highest possible value achieved to date for this substrate with a metal-free catalyst, thereby also exceeding the best available enzymatic systems (64% ee) and the selectivity with Corey's original catalyst (60% ee). This translates into a >50% improvement in relative ΔG‡ from 0.9 to 1.4 kcal mol-1. We underscore the transformative potential of machine learning in accelerating catalyst design because we rely on a manageable small data set and a key-intermediate graph representing a combination of catalyst and substrate graphs in lieu of a transition-state model. Our results highlight the synergy of synthetic chemistry and data-centric approaches and provide a blueprint for future catalyst optimization.

Simultaneous Stereoinvertive and Stereoselective C(sp3)-C(sp3) Cross-Coupling of Boronic Esters and Allylic Carbonates

With increasing interest in constructing more three-dimensional entities, there has been growing interest in cross-coupling reactions that forge C(sp3)-C(sp3) bonds, which leads to additional challenges as it is not just a more difficult bond to construct but issues of stereocontrol also arise. Herein, we report the stereocontrolled cross-coupling of enantioenriched boronic esters with racemic allylic carbonates enabled by iridium catalysis, leading to the formation of C(sp3)-C(sp3) bonds with single or vicinal stereogenic centers. The method shows broad substrate scope, enabling primary, secondary, and even tertiary boronic esters to be employed, and can be used to prepare any of the four possible stereoisomers of a coupled product with vicinal chiral centers. The new method, which combines the simultaneous enantiospecific reaction of a chiral nucleophile with the enantioselective reaction of a chiral electrophile in a single process, offers a solution for stereodivergent cross-coupling of two C(sp3) fragments.

Orthogonal sp3-Ge/B Bimetallic Modules: Enantioselective Construction and Enantiospecific Cross-Coupling

In this study, a series of enantioenriched sp3-Ge/B bimetallic modules were successfully synthesized via an enantioselective copper-catalyzed hydroboration of carbagermatrane (Ge)-containing alkenes. Orthogonal cross-coupling selectivity under different Pd-catalyzed conditions was achieved in an enantiospecific manner. Notably, the chiral secondary Ge exhibited a remarkable transmetallation ability prior to primary or secondary Bpin. The effectiveness of this Ge/B bimetallic strategy was further demonstrated through the development of new functional small molecules with Aggregation-Induced Emission (AIE) and Circularly Polarized Luminescence (CPL) performance. This represents the first successful example of synthesis of enantioenriched alkylgermanium reagents that permit enantiospecific cross-coupling reactions.

Artificial Intelligence for Retrosynthetic Planning Needs Both Data and Expert Knowledge

Rapid advancements in artificial intelligence (AI) have enabled breakthroughs across many scientific disciplines. In organic chemistry, the challenge of planning complex multistep chemical syntheses should conceptually be well-suited for AI. Yet, the development of AI synthesis planners trained solely on reaction-example-data has stagnated and is not on par with the performance of "hybrid" algorithms combining AI with expert knowledge. This Perspective examines possible causes of these shortcomings, extending beyond the established reasoning of insufficient quantities of reaction data. Drawing attention to the intricacies and data biases that are specific to the domain of synthetic chemistry, we advocate augmenting the unique capabilities of AI with the knowledge base and the reasoning strategies of domain experts. By actively involving synthetic chemists, who are the end users of any synthesis planning software, into the development process, we envision to bridge the gap between computer algorithms and the intricate nature of chemical synthesis.

Rapid, Homogenous, B-Alkyl Suzuki-Miyaura Cross-Coupling of Boronic Esters

A rapid, anhydrous Suzuki-Miyaura cross-coupling of alkylboronic esters with aryl halides is described. Parallel experimentation revealed that the combination of AntPhos, an oxaphosphole ligand, neopentyldiol alkylboronic esters, and potassium trimethylsilanolate (TMSOK) enables successful cross-coupling. In general, reactions proceed in under 1 h with good yields and high linear/branched (l/b) selectivities. Crucially, two literature examples which previously took >20 h to reach completion were accomplished in a fraction of the time with the method described herein. Mechanistic studies revealed that the reaction proceeds through a stereoretentive pathway and identified the boronic ester skeleton as a predominant pathway for deleterious protodehalogenation.

Computationally Guided Ligand Discovery from Compound Libraries and Discovery of a New Class of Ligands for Ni-Catalyzed Cross-Electrophile Coupling of Challenging Quinoline Halides

Although screening technology has heavily impacted the fields of metal catalysis and drug discovery, its application to the discovery of new catalyst classes has been limited. The diversity of on- and off-cycle pathways, combined with incomplete mechanistic understanding, means that screens of potential new ligands have thus far been guided by intuitive analysis of the metal binding potential. This has resulted in the discovery of new classes of ligands, but the low hit rates have limited the use of this strategy because large screens require considerable cost and effort. Here, we demonstrate a method to identify promising screening directions via simple and scalable computational and linear regression tools that leads to a substantial improvement in hit rate, enabling the use of smaller screens to find new ligands. The application of this approach to a particular example of Ni-catalyzed cross-electrophile coupling of aryl halides with alkyl halides revealed a previously overlooked trend: reactions with more electron-poor amidine ligands result in a higher yield. Focused screens utilizing this trend were more successful than serendipity-based screening and led to the discovery of two new types of ligands, pyridyl oxadiazoles and pyridyl oximes. These ligands are especially effective for couplings of bromo- and chloroquinolines and isoquinolines, where they are now the state of the art. The simplicity of these models with parameters derived from metal-free ligand structures should make this approach scalable and widely accessible.

Computational Methods Enable the Prediction of Improved Catalysts for Nickel-Catalyzed Cross-Electrophile Coupling

Cross-electrophile coupling has emerged as an attractive and efficient method for the synthesis of C(sp2)-C(sp3) bonds. These reactions are most often catalyzed by nickel complexes of nitrogenous ligands, especially 2,2'-bipyridines. Precise prediction, selection, and design of optimal ligands remains challenging, despite significant increases in reaction scope and mechanistic understanding. Molecular parameterization and statistical modeling provide a path to the development of improved bipyridine ligands that will enhance the selectivity of existing reactions and broaden the scope of electrophiles that can be coupled. Herein, we describe the generation of a computational ligand library, correlation of observed reaction outcomes with features of the ligands, and the in silico design of improved bipyridine ligands for Ni-catalyzed cross-electrophile coupling. The new nitrogen-substituted ligands display a 5-fold increase in selectivity for product formation versus homodimerization when compared to the current state of the art. This increase in selectivity and yield was general for several cross-electrophile couplings, including the challenging coupling of an aryl chloride with an N-alkylpyridinium salt.

Rational Design of Palladium(II) Indenyl and Allyl Complexes Bearing Phosphine and Isocyanide Ancillary Ligands with Promising Antitumor Activity

A new class of palladium-indenyl complexes characterized by the presence of one bulky alkyl isocyanide and one aryl phosphine serving as ancillary ligands has been prepared, presenting high yields and selectivity. All the new products were completely characterized using spectroscopic and spectrometric techniques (NMR, FT-IR, and HRMS), and, for most of them, it was also possible to define their solid-state structures via X-ray diffractometry, revealing that the indenyl fragment always binds to the metal centre with a hapticity intermediate between ƞ3 and ƞ5. A reactivity study carried out using piperidine as a nucleophilic agent proved that the indenyl moiety is the eligible site of attack rather than the isocyanide ligand or the metal centre. All complexes were tested as potential anticancer agents against three ovarian cancer cell lines (A2780, A2780cis, and OVCAR-5) and one breast cancer cell line (MDA-MB-231), displaying comparable activity with respect to cisplatin, which was used as a positive control. Moreover, the similar cytotoxicity observed towards A2780 and A2780cis cells (cisplatin-sensitive and cisplatin-resistant, respectively) suggests that our palladium derivatives presumably act with a mechanism of action different than that of the clinically approved platinum drugs. For comparison, we also synthesized Pd-ƞ3-allyl derivatives, which generally showed a slightly higher activity towards ovarian cancer cells and lower activity towards breast cancer cells with respect to their Pd-indenyl congeners.

Dataset Design for Building Models of Chemical Reactivity

Models can codify our understanding of chemical reactivity and serve a useful purpose in the development of new synthetic processes via, for example, evaluating hypothetical reaction conditions or in silico substrate tolerance. Perhaps the most determining factor is the composition of the training data and whether it is sufficient to train a model that can make accurate predictions over the full domain of interest. Here, we discuss the design of reaction datasets in ways that are conducive to data-driven modeling, emphasizing the idea that training set diversity and model generalizability rely on the choice of molecular or reaction representation. We additionally discuss the experimental constraints associated with generating common types of chemistry datasets and how these considerations should influence dataset design and model building.

Visible light-induced palladium-carbon bond weakening in catalytically relevant T-shaped complexes

Triggering one-electron redox processes during palladium catalysis holds the potential to unlock new reaction mechanisms and synthetic methods not previously accessible in the typical two-electron reaction manifolds that dominate palladium catalysis. We report that T-shaped organopalladium(ii) complexes coordinated by a bulky monophosphine, a class of organometallic intermediate featured in a range of contemporary catalytic reactions, undergo blue light-promoted bond weakening leading to mild and efficient homolytic cleavage of strong Pd(ii)-C(sp3) bonds under ambient conditions. The origin of light-triggered radical formation in these systems, which lack an obvious ligand-based chromophore (i.e., π-systems), was investigated using a combination of DFT calculations, photoactinometry, and transient absorption spectroscopy. The available data suggest T-shaped organopalladium(ii) complexes manifest unusual blue light-accessible Pd-to-C(sp3) transition. The quantum efficiency and excited state lifetime of this process were unexpectedly superior compared to a prototypical (α-diimine)Pd(ii) complex featuring a low-lying, ligand-centered LUMO (π*). These results suggest coordinatively-unsaturated organopalladium(ii) compounds, catalysts in myriad catalytic processes, have untapped potential for one-electron reactivity under visible light excitation.

A deep learning framework for accurate reaction prediction and its application on high-throughput experimentation data

In recent years, it has been seen that artificial intelligence (AI) starts to bring revolutionary changes to chemical synthesis. However, the lack of suitable ways of representing chemical reactions and the scarceness of reaction data has limited the wider application of AI to reaction prediction. Here, we introduce a novel reaction representation, GraphRXN, for reaction prediction. It utilizes a universal graph-based neural network framework to encode chemical reactions by directly taking two-dimension reaction structures as inputs. The GraphRXN model was evaluated by three publically available chemical reaction datasets and gave on-par or superior results compared with other baseline models. To further evaluate the effectiveness of GraphRXN, wet-lab experiments were carried out for the purpose of generating reaction data. GraphRXN model was then built on high-throughput experimentation data and a decent accuracy (R2 of 0.712) was obtained on our in-house data. This highlights that the GraphRXN model can be deployed in an integrated workflow which combines robotics and AI technologies for forward reaction prediction.

Stereospecific Transformations of Alkylboronic Esters Enabled by Direct Boron-to-Zinc Transmetalation

Chiral secondary organoboronic esters, when activated with t-butyllithium, are shown to undergo efficient stereoretentive transmetalation with either zinc acetate or zinc chloride. This reaction provides chiral secondary alkylzinc reagents that are configurationally stable under practical experimental conditions. The organozinc compounds were found to engage in stereospecific reactions with difluorocarbene, catalytic cross-couplings with palladium-based catalysts, and trifluoromethylation with a copper(III) complex. Mechanistic and computational studies shed light on the inner workings of the transmetalation event.

Desymmetrization of Vicinal Bis(boronic) Esters by Enantioselective Suzuki-Miyaura Cross-Coupling Reaction

The development of an enantioselective catalytic Suzuki-Miyaura reaction that applies to meso 1,2-diborylcycloalkanes is described. This reaction provides a modular route to enantiomerically enriched substituted carbocycles and heterocycles that retain a synthetically versatile boronic ester. With appropriately constructed substrates, compounds bearing additional stereogenic centers and fully substituted carbon atoms can be generated in a straightforward fashion. Preliminary mechanistic experiments suggest that substrate activation arises from the cooperative effect of vicinal boronic esters during the transmetalation step.

Directed Asymmetric Nickel-Catalyzed Reductive 1,2-Diarylation of Electronically Unactivated Alkenes

Transition-metal catalyzed intermolecular 1,2-diarylation of electronically unactivated alkenes has emerged as an extensive research topic in organic synthesis. However, most examples are mainly limited to terminal alkenes. Furthermore, transition-metal catalyzed asymmetric 1,2-diarylation of unactivated alkenes still remains unsolved and is a formidable challenge. Herein, we describe a highly efficient directed nickel-catalyzed reductive 1,2-diarylation of unactivated internal alkenes with high diastereoselectivities. More importantly, our further effort towards enantioselective 1,2-diarylation of the unactivated terminal and challenging internal alkenes is achieved, furnishing various polyarylalkanes featuring benzylic stereocenters in high yields and with good to high enantioselectivities and high diastereoselectivities. Interestingly, the generation of cationic Ni-catalyst by adding alkali metal fluoride is the key to increased efficiency of this enantioselective reaction.

Stereospecific Acylative Suzuki–Miyaura Cross-Coupling: General Access to Optically Active α-Aryl Carbonyl Compounds

A novel strategy for the stereospecific Pd-catalyzed acylative cross-coupling of enantiomerically enriched alkylboron compounds has been developed. The protocol features an extremely high level of enantiospecificity to allow facile access to synthetically challenging and valuable chiral ketones and carboxylic acid derivatives. The use of a sterically encumbered and electron-rich phosphine ligand proved to be crucial for the success of the reaction. Furthermore, on the basis of experimental and computational studies, a unique mechanism for the transmetalation, assisted by the noncovalent interactions of the C(sp³)-based organoboron reagent, has been identified.

Computer-Driven Development of Ylide Functionalized Phosphines for Palladium-Catalyzed Hiyama Couplings

Palladium-catalyzed couplings of silicon enolates with aryl electrophiles are of great synthetic utility, but often limited to expensive bromide substrates. A comparative experimental study confirmed that none of the established ligand systems allows to couple inexpensive aryl chlorides with α-trimethylsilyl alkylnitriles. In contrast, ylide functionalized phosphines (YPhos) led to encouraging results. A statistical model was developed that correlates the reaction yields with ligand features. It was employed to predict catalyst structures with superior performance. With this cheminformatics approach, YPhos ligands were tailored specifically to the demands of Hiyama couplings. The newly synthesized ligands displayed record-setting activities, enabling the elusive coupling of aryl chlorides with α-trimethylsilyl alkyl nitriles. The preparative utility of the catalyst system was demonstrated by the synthesis of pharmaceutically meaningful α-aryl alkylnitriles, α-arylcarbonyls and biaryls.

TiCl4-Catalyzed Hydroboration of Ketones with Ammonia Borane

Investigation of a variety of Lewis acids for the hydroboration-hydrolysis (reduction) of ketones with amine-boranes has revealed that catalytic (10 mol %) titanium tetrachloride (TiCl₄) in diethyl ether at room temperature immensely accelerates the reaction of ammonia borane. The product alcohols are produced in good to excellent yields within 30 min, even with ketones which typically requires 24 h or longer to reduce under uncatalyzed conditions. Several potentially reactive functionalities are tolerated, and substituted cycloalkanones are reduced diastereoselectively to the thermodynamic product. A deuterium labeling study and ¹¹B NMR analysis of the reaction have been performed to verify the proposed hydroboration mechanism.

Sterically Controlled Late-Stage Functionalization of Bulky Phosphines

The fine-tuning of metal-phosphine-catalyzed reactions relies largely on accessing ever more precisely tuned phosphine ligands by de-novo synthesis. Late-stage C-H functionalization and diversification of commercial phosphines offers rapid access to entire libraries of derivatives based on privileged scaffolds. But existing routes, relying on phosphorus-directed transformations, only yield functionalization of Csp 2 -H bonds in a specific position relative to phosphorus. In contrast to phosphorus-directed strategies, herein we disclose an orthogonal functionalization strategy capable of introducing a range of substituents into previously inaccessible positions on arylphosphines. The strongly coordinating phosphine group acts solely as a bystander in the sterically controlled borylation of bulky phosphines, and the resulting borylated phosphines serve as the supporting ligands for palladium during diversification through phosphine self-assisted Suzuki-Miyaura reactions.

Homogeneity of Supported Single-Atom Active Sites Boosting the Selective Catalytic Transformations

Selective conversion of specific functional groups to desired products is highly important but still challenging in industrial catalytic processes. The adsorption state of surface species is the key factor in modulating the conversion of functional groups, which is correspondingly determined by the uniformity of active sites. However, the non-identical number of metal atoms, geometric shape, and morphology of conventional nanometer-sized metal particles/clusters normally lead to the non-uniform active sites with diverse geometric configurations and local coordination environments, which causes the distinct adsorption states of surface species. Hence, it is highly desired to modulate the homogeneity of the active sites so that the catalytic transformations can be better confined to the desired direction. In this review, the construction strategies and characterization techniques of the uniform active sites that are atomically dispersed on various supports are examined. In particular, their unique behavior in boosting the catalytic performance in various chemical transformations is discussed, including selective hydrogenation, selective oxidation, Suzuki coupling, and other catalytic reactions. In addition, the dynamic evolution of the active sites under reaction conditions and the industrial utilization of the single-atom catalysts are highlighted. Finally, the current challenges and frontiers are identified, and the perspectives on this flourishing field is provided.

Nickel-catalysed diversification of phosphine ligands by formal substitution at phosphorus

We report a diversification strategy that enables the direct substituent exchange of tertiary phosphines. Alkylated phosphonium salts, prepared by standard alkylation of phosphines, are selectively dearylated in a nickel-catalysed process to access alkylphosphine products via a formal substitution at the phosphorus center. The reaction can be used to introduce a wide range of alkyl substituents into both mono- and bisphosphines. We also show that the alkylation and dearylation steps can be conducted in a one-pot sequence, enabling accelerated access to derivatives of the parent ligand. The phosphine products of the reaction are converted in situ to air-stable borane adducts for isolation, and versatile derivatisation reactions of these adducts are demonstrated.

Phosphine substituents can be exchanged by standard alkylation of a phosphine and a subsequent dearylation of the resulting phosphonium salt. A wide variety of alkyl groups can be introduced into both mono- and bidentate ligands using this method.

Copper-Catalyzed Stereospecific Transformations of Alkylboronic Esters

Copper-catalyzed stereospecific cross-couplings of boronic esters are reported. Boron "ate" complexes derived from pinacol boronic esters and tert-butyl lithium undergo stereospecific transmetalation to copper cyanide, followed by coupling with alkynyl bromides, allyl halides, propargylic halides, β-haloenones, hydroxylamine esters, and acyl chlorides. Through this simple transformation, commercially available inexpensive compounds can be employed to convert primary and secondary alkylboronic esters to a wide array of synthetically useful compounds.

Ligand-Based Control of Nickel Catalysts: Switching Chemoselectivity from One-Electron to Two-Electron Pathways in Competing Reactions of 4-Halotetrahydropyrans

Development of nickel-catalyzed transformations would be facilitated by an improved ability to predict which ligands promote and suppress competing mechanisms. We evaluate ligand-based modulation of catalyst preference for one- or two-electron pathways employing 4-halotetrahydropyrans as model substrates that can undergo divergent reaction pathways. Chemoselectivity for one- or two-electron oxidative addition is predicted by ligand class. Phosphine-ligated nickel catalysts favor closed-shell oxidative addition. In contrast, nitrogen-ligated nickel catalysts prefer the one-electron pathway, initiating with halogen atom transfer.

Selective Coupling of 1,2-Bis-Boronic Esters at the more Substituted Site through Visible-Light Activation of Electron Donor-Acceptor Complexes

1,2-Bis-boronic esters are useful synthetic intermediates particularly as the two boronic esters can be selectively functionalized. Usually, the less hindered primary boronic ester reacts, but herein, we report a coupling reaction that enables the reversal of this selectivity. This is achieved through the formation of a boronate complex with an electron-rich aryllithium which, in the presence of an electron-deficient aryl nitrile, leads to the formation of an electron donor-acceptor complex. Following visible-light photoinduced electron transfer, a primary radical is generated which isomerizes to the more stable secondary radical before radical-radical coupling with the arene radical-anion, giving β-aryl primary boronic ester products. The reactions proceed under catalyst-free conditions. This method also allows stereodivergent coupling of cyclic cis-1,2-bis-boronic esters to provide trans-substituted products, complementing the selectivity observed in the Suzuki-Miyaura reaction.

Emerging Landscape of Computational Modeling in Pharmaceutical Development

Computational chemistry applications have become an integral part of the drug discovery workflow over the past 35 years. However, computational modeling in support of drug development has remained a relatively uncharted territory for a significant part of both academic and industrial communities. This review considers the computational modeling workflows for three key components of drug preclinical and clinical development, namely, process chemistry, analytical research and development, as well as drug product and formulation development. An overview of the computational support for each step of the respective workflows is presented. Additionally, in context of solid form design, special consideration is given to modern physics-based virtual screening methods. This covers rational approaches to polymorph, coformer, counterion, and solvent virtual screening in support of solid form selection and design.

Cooperative Pd/Cu Catalysis for Alkene Arylboration: Opportunities for Divergent Reactivity

A preeminent challenge in alkene difunctionalization is the control of regio-, diastereo-, and enantioselectivity. In this Perspective, a Pd/Cu-cooperative catalytic system for alkene arylboration is highlighted that allows for the controlled introduction of substituents. In particular, examples that allowed for divergent reactivity from a single substrate based on the tuning of catalysts and reaction conditions are emphasized.

A Comprehensive Discovery Platform for Organophosphorus Ligands for Catalysis

The design of molecular catalysts typically involves reconciling multiple conflicting property requirements, largely relying on human intuition and local structural searches. However, the vast number of potential catalysts requires pruning of the candidate space by efficient property prediction with quantitative structure-property relationships. Data-driven workflows embedded in a library of potential catalysts can be used to build predictive models for catalyst performance and serve as a blueprint for novel catalyst designs. Herein we introduce kraken, a discovery platform covering monodentate organophosphorus(III) ligands providing comprehensive physicochemical descriptors based on representative conformer ensembles. Using quantum-mechanical methods, we calculated descriptors for 1558 ligands, including commercially available examples, and trained machine learning models to predict properties of over 300000 new ligands. We demonstrate the application of kraken to systematically explore the property space of organophosphorus ligands and how existing data sets in catalysis can be used to accelerate ligand selection during reaction optimization.

Volcano Plots of Reaction Yields in Cross-Coupling Catalysis

It is critical to identify the influence of phosphine ligands on cross-coupling reactions to obtain a higher yield. In order to reveal ligands' effects, many descriptors have been proposed, which allow statistical analysis to be implemented in mining the structure-property relationship and providing mechanistic insights. This work combines the steric and electronic effects into a descriptor, %V_bur (min) - 3·HOMO-LUMO gap (eV) where %V_bur (min) is the minimum percent buried volume and the Boltzmann averaged gap is used. Volcano plots were well presented by yields (y-axis) and the descriptor (x-axis) for Ni- and Pd-catalyzed cross-coupling reactions. In addition, volcano peaks in these plots can be located to optimize reaction yields for experiments. Our work sheds light on the reaction mechanisms of phosphine ligands and delivers a strategy for choosing ligands in cross-coupling catalysis.

Harvesting the fragment-based nature of bifunctional organocatalysts to enhance their activity

Enhancing the activity of bifunctional organocatalysts: a fragment-based approach coupled with activity maps helps identifying better-performing catalytic motifs.

Auto-QChem: an automated workflow for the generation and storage of DFT calculations for organic molecules

This perspective describes Auto-QChem, an automatic, high-throughput and end-to-end DFT calculation workflow that computes chemical descriptors for organic molecules.

Seeking the Optimal Descriptor for SN2 Reactions through Statistical Analysis of Density Functional Theory Results

Bimolecular nucleophilic substitution is one of the fundamental reactions in organic chemistry, yet there is still knowledge to be gained on the role of the nucleophile and the substrate. A statistical treatment of over 600 density functional theory (DFT)-computed barriers for bimolecular nucleophilic substitution at methyl derivatives (S_N2@C) leads to the identification of numerical descriptors that best represent the entering and leaving ability of 26 different nucleophiles. The treatment is based on singular value decomposition (SVD) of a matrix of computed energy barriers. The current work represents the extension to a problem of reactivity of the hidden descriptor methodology that we had previously developed for the thermodynamic problem of bond dissociation energies in transition-metal complexes. The analysis of the results shows that a single descriptor is sufficient. This hidden descriptor has different values for nucleophilic and leaving abilities and, contrary to expectation, does not correlate especially well with either frontier molecular orbital descriptors or solvation descriptors. In contrast, it correlates with other thermodynamic and geometric parameters. This statistical procedure can be in principle extended to additional chemical fragments and other reactions.

Origin of Ligand Effects on Stereoinversion in Pd-Catalyzed Synthesis of Tetrasubstituted Olefins

The mechanism and origin of ligand effects on stereoinversion of Pd-catalyzed synthesis of tetrasubstituted olefins were investigated using DFT calculations and the approach of energy decomposition analysis (EDA). The results reveal that the stereoselectivity-determining steps are different when employing different phosphine ligands. This is mainly due to the steric properties of ligands. With the bulkier Xantphos ligand, the syn/anti-to-Pd 1,2-migrations determine the stereoselectivity. While using the less hindered P(o-tol)₃ ligand, the 1,3-migration is the stereoselectivity-determining step. The EDA results demonstrate that Pauli repulsion and polarization are the dominant factors for controlling the stereochemistry in 1,2- and 1,3-migrations, respectively. The origins of differences of Pauli repulsion and polarization between the two stereoselective transition states are further identified.

The Open Reaction Database

Chemical reaction data in journal articles, patents, and even electronic laboratory notebooks are currently stored in various formats, often unstructured, which presents a significant barrier to downstream applications, including the training of machine-learning models. We present the Open Reaction Database (ORD), an open-access schema and infrastructure for structuring and sharing organic reaction data, including a centralized data repository. The ORD schema supports conventional and emerging technologies, from benchtop reactions to automated high-throughput experiments and flow chemistry. The data, schema, supporting code, and web-based user interfaces are all publicly available on GitHub. Our vision is that a consistent data representation and infrastructure to support data sharing will enable downstream applications that will greatly improve the state of the art with respect to computer-aided synthesis planning, reaction prediction, and other predictive chemistry tasks.

Saturated Boronic Acids, Boronates, and Trifluoroborates: An Update on Their Synthetic and Medicinal Chemistry

This review discusses recent advances in the chemistry of saturated boronic acids, boronates, and trifluoroborates. Applications of the title compounds in the design of boron-containing drugs are surveyed, with special emphasis on α-amino boronic derivatives. A general overview of saturated boronic compounds as modern tools to construct C(sp³ )-C and C(sp³ )-heteroatom bonds is given, including recent developments in the Suzuki-Miyaura and Chan-Lam cross-couplings, single-electron-transfer processes including metallo- and organocatalytic photoredox reactions, and transformations of boron "ate" complexes. Finally, an attempt to summarize the current state of the art in the synthesis of saturated boronic acids, boronates, and trifluoroborates is made, with a brief mention of the "classical" methods (transmetallation of organolithium/magnesium reagents with boron species, anti-Markovnikov hydroboration of alkenes, and the modification of alkenyl boron compounds) and a special focus on recent methodologies (boronation of alkyl (pseudo)halides, derivatives of carboxylic acids, alcohols, and primary amines, boronative C-H activation, novel approaches to alkene hydroboration, and 1,2-metallate-type rearrangements).