American Chemical Society
ja1c12198_si_001.xlsx (50.93 kB)

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

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posted on 2022-01-24, 19:35 authored by Ryan C. Cammarota, Wenbin Liu, John Bacsa, Huw M. L. Davies, Matthew S. Sigman
Leveraging congested catalyst scaffolds has emerged as a key strategy for altering innate substrate site-selectivity profiles in C–H functionalization reactions. Similar to enzyme active sites, optimal small molecule catalysts often feature reactive cavities tailored for controlling substrate approach trajectories. However, relating three-dimensional catalyst shape to reaction output remains a formidable challenge, in part due to the lack of molecular features capable of succinctly describing complex reactive site topologies in terms of numerical inputs for machine learning applications. Herein, we present a new set of descriptors, “Spatial Molding for Approachable Rigid Targets” (SMART), which we have applied to quantify reactive site spatial constraints for an expansive library of dirhodium catalysts and to predict site-selectivity for C–H functionalization of 1-bromo-4-pentylbenzene via donor/acceptor carbene intermediates. Optimal site-selectivity for the terminal methylene position was obtained with Rh2(S-2-Cl-5-MesTPCP)4 (30.9:1 rr, 14:1 dr, 87% ee), while C–H functionalization at the electronically activated benzylic site was increasingly favored for Rh2(TPCP)4 catalysts lacking an ortho-Cl, Rh2(S-PTAD)4, and Rh2(S-TCPTAD)4, respectively. Intuitive global site-selectivity models for 25 disparate dirhodium catalysts were developed via multivariate linear regression to explicitly assess the contributing roles of steric congestion and dirhodium-carbene electrophilicity in controlling the site of C–H functionalization. The workflow utilizes spatial classification to extract descriptors only for reactive catalyst conformers, a nuance that may be widely applicable for establishing close correspondence between ground-state model systems and transition states. Broader still, SMART descriptors are amenable for delineating salient reactive site features to predict reactivity in other chemical and biological contexts.