In-silico-assisted derivatization of triarylboranes for the catalytic reductive functionalization of aniline-derived amino acids and peptides with H2.

Cheminformatics-based machine learning (ML) has been employed to determine optimal reaction conditions, including catalyst structures, in the field of synthetic chemistry. However, such ML-focused strategies have remained largely unexplored in the context of catalytic molecular transformations using Lewis-acidic main-group elements, probably due to the absence of a candidate library and effective guidelines (parameters) for the prediction of the activity of main-group elements. Here, the construction of a triarylborane library and its application to an ML-assisted approach for the catalytic reductive alkylation of aniline-derived amino acids and C-terminal-protected peptides with aldehydes and H2 is reported. A combined theoretical and experimental approach identified the optimal borane, i.e., B(2,3,5,6-Cl4-C6H)(2,6-F2-3,5-(CF3)2-C6H)2, which exhibits remarkable functional-group compatibility toward aniline derivatives in the presence of 4-methyltetrahydropyran. The present catalytic system generates H2O as the sole byproduct.

Impact of helical elongation of symmetric oxa[n]helicenes on their structural, photophysical, and chiroptical characteristics.

The adjustment of the main helical scaffold in helicenes is a fundamental strategy for modulating their optical features, thereby enhancing their potential for diverse applications. This work explores the influence of helical elongation (n = 5-9) on the structural, photophysical, and chiroptical features of symmetric oxa[n]helicenes. Crystal structure analyses revealed structural variations with helical extension, impacting torsion angles, helical pitch, and packing arrangements. Through theoretical investigations using density functional theory (DFT) calculations, the impact of helical extension on aromaticity, planarity distortion, and heightened chiral stability were discussed. Photophysical features were studied through spectrophotometric analysis, with insights gained through time-dependent DFT (TD-DFT) calculations. Following optical resolution via chiral high-performance liquid chromatography (HPLC), the chiroptical properties of both enantiomers of oxa[7]helicene and oxa[9]helicene were investigated. A slight variation in the main helical scaffold of oxa[n]helicenes from [7] to [9] induced an approximately three-fold increase in dissymmetry factors with the biggest values of|glum| of oxa[9]helicene (2.2 × 10-3) compared to|glum|of oxa[7]helicene (0.8 × 10-3), findings discussed and supported by TD-DFT calculations.

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.

Synthesis and Structural and Optical Behavior of Dehydrohelicene-Containing Polycyclic Compounds.

Dehydrohelicene-based molecules stand out as highly promising scaffolds and captivating chiroptical materials, characterized by their unique chirality. Their quasi-helical π-conjugated molecular architecture, featuring successively ortho-annulated aromatic rings, endows them with remarkable thermal stability and optical properties. Over the past decade, diverse approaches have emerged for synthesizing these scaffolds, reinvigorating this field, with anticipated increased attention in the coming years. This review provides a comprehensive overview of the historical evolution of dehydrohelicene chemistry since the pioneering work of Zander and Franke in 1969 and highlights recent advancements in the synthesis of various molecules incorporating dehydrohelicene motifs. We elucidate the intriguing structural features and optical merits of these molecules, occasionally drawing comparisons with their helicene or circulene analogs to underscore the significance of the bond between the helical termini.