Mechanistically Guided Workflow for Relating Complex Reactive Site Topologies to Catalyst Performance in C–H Functionalization Reactions

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.

Running Wild through Dirhodium Tetracarboxylate-Catalyzed Combined CH(C)-Functionalization/Cope Rearrangement Landscapes: Does Post-Transition-State Dynamic Mismatching Influence Product Distributions?

A special type of C-H functionalization can be achieved through C-H insertion combined with Cope rearrangement (CHCR) in the presence of dirhodium catalysts. This type of reaction was studied using density functional theory and ab initio molecular dynamics simulations, the results of which pointed to the dynamic origins of low yields observed in some experiments. These studies not only reveal intimate details of the complex reaction network underpinning CHCR reactions but also further cement the generality of the importance of nonstatistical dynamic effects in controlling Rh2L4-promoted reactions.

Deconvoluting Nonlinear Catalyst-Substrate Effects in the Intramolecular Dirhodium-Catalyzed C-H Insertion of Donor/Donor Carbenes Using Data Science Tools

Interactions between catalysts and substrates can be highly complex and dynamic, often complicating the development of models to either predict or understand such processes. A dirhodium(II)-catalyzed C-H insertion of donor/donor carbenes into 2-alkoxybenzophenone substrates to form benzodihydrofurans was selected as a model system to explore nonlinear methods to achieve a mechanistic understanding. We found that the application of traditional methods of multivariate linear regression (MLR) correlating DFT-derived descriptors of catalysts and substrates leads to poorly performing models. This inspired the introduction of nonlinear descriptor relationships into modeling by applying the sure independence screening and sparsifying operator (SISSO) algorithm. Based on SISSO-generated descriptors, a high-performing MLR model was identified that predicts external validation points well. Mechanistic interpretation was aided by the deconstruction of feature relationships using chemical space maps, decision trees, and linear descriptors. Substrates were found to have a strong dependence on steric effects for determining their innate cyclization selectivity preferences. Catalyst reactive site features can then be matched to product features to tune or override the resultant diastereoselectivity within the substrate-dictated ranges. This case study presents a method for understanding complex interactions often encountered in catalysis by using nonlinear modeling methods and linear deconvolution by pattern recognition.

Highly Selective C(sp3)-H Bond Oxygenation at Remote Methylenic Sites Enabled by Polarity Enhancement

A detailed study on the C(sp3)-H bond oxygenation reactions with H2O2 catalyzed by the [Mn(OTf)2(TIPSmcp)] complex at methylenic sites of cycloalkyl and 1-alkyl substrates bearing 19 different electron-withdrawing functional groups (EW FGs) was carried out. Oxidations in MeCN were compared to the corresponding ones in the strong hydrogen bond donating (HBD) solvents 1,1,1,3,3,3-hexafluoro-2-propanol (HFIP) and nonafluoro tert-butyl alcohol (NFTBA). Formation of the products deriving from oxygenation at the most remote methylenic sites was observed, with yields, product ratios (PR) for oxygenation at the most remote over the next methylenic sites, and associated site-selectivities that significantly increased going from MeCN to HFIP and NFTBA. Unprecedented site-selectivities were obtained in the oxidation of cyclohexyl, cycloheptyl, cyclooctyl, 1-pentyl, 1-hexyl, and 1-heptyl substrates, approaching >99%, >99%, 90%, >99%, 93%, and 88% (PR >99, >99, 9.4, >99, 14, and 7.5) with cyclohexyl-2-pyridinecarboxylate, cycloheptyl-2-pyridinecarboxylate, cyclooctyl-4-nitrobenzenesulfonamide, 1-pentyl-3,5-dinitrobenzoate, 1-hexyl-3,5-dinitrobenzoate, and 1-heptyl-3,5-dinitrobenzoate, respectively. The results are rationalized on the basis of a polarity enhancement effect via synergistic electronic deactivation of proximal methylenic sites imparted by the EWG coupled to solvent HB. Compared to previous procedures, polarity enhancement provides the opportunity to tune site-selectivity among multiple methylenes in different substrate classes, extending the strong electronic deactivation determined by native EWGs by two carbon atoms. This study uncovers a simple procedure for predictable, high-yielding, and highly site-selective oxidation at remote methylenes of cycloalkyl and 1-alkyl substrates that occurs under mild conditions, with a large substrate scope, providing an extremely powerful tool to be implemented in synthetically useful procedures.

A substrate descriptor based approach for the prediction and understanding of the regioselectivity in caged catalyzed hydroformylation

The use of data driven tools to predict the selectivity of homogeneous catalysts has received considerable attention in the past years. In these studies often the catalyst structure is varied, but the use of substrate descriptors to rationalize the catalytic outcome is relatively unexplored. To study whether this may be an effective tool, we investigated both an encapsulated and a non-encapsulated rhodium based catalyst in the hydroformylation reaction of 41 terminal alkenes. For the non-encapsulated catalyst, CAT2, the regioselectivity of the acquired substrate scope could be predicted with high accuracy using the Δ13C NMR shift of the alkene carbon atoms as a descriptor (R2 = 0.74) and when combined with a computed intensity of the CC stretch vibration (ICC stretch) the accuracy increased further (R2 = 0.86). In contrast, a substrate descriptor approach with an encapsulated catalyst, CAT1, appeared more challenging indicating a confined space effect. We investigated Sterimol parameters of the substrates as well as computer-aided drug design descriptors of the substrates, but these parameters did not result in a predictive formula. The most accurate substrate descriptor based prediction was made with the Δ13C NMR shift and ICC stretch (R2 = 0.52), suggestive of the involvement of CH-π interactions. To further understand the confined space effect of CAT1, we focused on the subset of 21 allylbenzene derivatives to investigate predictive parameters unique for this subset. These results showed the inclusion of a charge parameter of the aryl ring improved the regioselectivity predictions, which is in agreement with our assessment that noncovalent interactions between the phenyl ring of the cage and the aryl ring of the substrate are relevant for the regioselectivity outcome. However, the correlation is still weak (R2 = 0.36) and as such we are investigating novel parameters that should improve the overall regioselectivity outcome.

N-Phthalimide as a Site-Protecting and Stereodirecting Group in Rhodium-Catalyzed C-H Functionalization with Donor/Acceptor Carbenes

The rhodium-catalyzed enantioselective C-H functionalization of unactivated C-H bonds by means of donor/acceptor carbene-induced C-H insertion was extended to substrates containing nitrogen functionality. The rhodium-stabilized donor/acceptor carbenes were generated by rhodium-catalyzed decomposition of aryldiazoacetates. The phthalimido group was the optimum nitrogen protecting group. C-H functionalization at the most sterically accessible methylene site was achieved using Rh₂(S-2-Cl-5-BrTPCP)₄ as catalyst, whereas Rh₂(S-TPPTTL)₄ was the most effective catalyst for C-H functionalization at tertiary C-H bonds and for the desymmetrization of N-phthalimidocyclohexane.

Leveraging Regio- and Stereoselective C(sp3)-H Functionalization of Silyl Ethers to Train a Logistic Regression Classification Model for Predicting Site-Selectivity Bias

The C-H functionalization of silyl ethers via carbene-induced C-H insertion represents an efficient synthetic disconnection strategy. In this work, site- and stereoselective C(sp³)-H functionalization at α, γ, δ, and even more distal positions to the siloxy group has been achieved using donor/acceptor carbene intermediates. By exploiting the predilections of Rh₂(R-TCPTAD)₄ and Rh₂(S-2-Cl-5-BrTPCP)₄ catalysts to target either more electronically activated or more spatially accessible C-H sites, respectively, divergent desired products can be formed with good diastereocontrol and enantiocontrol. Notably, the reaction can also be extended to enable desymmetrization of meso silyl ethers. Leveraging the broad substrate scope examined in this study, we have trained a machine learning classification model using logistic regression to predict the major C-H functionalization site based on intrinsic substrate reactivity and catalyst propensity for overriding it. This model enables prediction of the major product when applying these C-H functionalization methods to a new substrate of interest. Applying this model broadly, we have demonstrated its utility for guiding late-stage functionalization in complex settings and developed an intuitive visualization tool to assist synthetic chemists in such endeavors.

Electronic control over site-selectivity in hydrogen atom transfer (HAT) based C(sp3)-H functionalization promoted by electrophilic reagents

The direct functionalization of C(sp³)-H bonds represents one of the most investigated approaches to develop new synthetic methodology. Among the available strategies for intermolecular C-H bond functionalization, increasing attention has been devoted to hydrogen atom transfer (HAT) based procedures promoted by radical or radical-like reagents, that offer the opportunity to introduce a large variety of atoms and groups in place of hydrogen under mild conditions. Because of the large number of aliphatic C-H bonds displayed by organic molecules, in these processes control over site-selectivity represents a crucial issue, and the associated factors have been discussed. In this review article, attention will be devoted to the role of electronic effects on C(sp³)-H bond functionalization site-selectivity. Through an analysis of the recent literature, a detailed description of the HAT reagents employed in these processes, the associated mechanistic features and the selectivity patterns observed in the functionalization of substrates of increasing structural complexity will be provided.