Parametrization of Non-covalent Interactions for Transition State Interrogation Applied to Asymmetric Catalysis

Abstract

The use of computed interaction energies and distances as parameters in multivariate correlations is introduced for postulating noncovalent interactions. This new class of descriptors affords multivariate correlations for two diverse catalytic systems with unique noncovalent interactions at the heart of each process. The presented methodology is validated by directly connecting the noncovalent interactions defined through empirical dataset analyses to the computationally derived transition states.

Combining traditional 2D and modern physical organic-derived descriptors to predict enhanced enantioselectivity for the key aza-Michael conjugate addition in the synthesis of Prevymis™ (letermovir)

“…Once identified, QSAR models can rapidly provide activity and selectivity estimates for new structures, thus enabling high-throughput virtual assessment of key structural components for the target of interest. Furthermore, highly weighted descriptors in the QSAR model may indicate structural features that influence the desired activity 2,3…”

A Universal Quantitative Descriptor of the Dispersion Interaction Potential

“…Recently, Sigman and co‐workers introduced computed interaction energies and distances as parameters for NCIs between aromatic rings and applied them successfully to several case studies . We wanted to test whether P int values could replace Sigman's energy parameters, which he termed Eπ, for the same type of multiple linear free‐energy relationship (MLFER) analysis. Hence, we reanalyzed the data of the palladium‐catalyzed enantioselective 1,1‐diarylation of benzyl acrylates with varying benzyl groups (Scheme ) .…”

“…However, it is not clear whether the increments are rather a measure of size as they correlated both with polarizabilities and surface areas. Additionally, Sigman and co‐workers proposed interaction parameters of substituted aromatic rings obtained from computed interaction energies, and successfully applied them to predict stereoselectivity in a number of catalytic reactions . Their main drawbacks are that they are quite expensive to compute, limited to aromatic systems, and account for more than just dispersion.…”

Mechanistic Investigations of the Pd(0)-Catalyzed Enantioselective 1,1-Diarylation of Benzyl Acrylates

“…17 Specifically, parameters derived from stacked complexes of benzene, the probe representing the PA’s anthracenyl group, and the requisite arenes, representing the substrate’s benzyl moiety, were computed (Figure 7A). 18 A trend was identified between the interaction energy of such stacked complexes ( S E π ) and the observed enantioselectivity from 17 benzyl acrylates (R 2 = 0.58, see Figure S11), supporting the hypothesis that a π stacking interaction could be influencing the stereodefining step.…”

“…With the hypothesis that these two NCIs contribute to the origin of the stereodiscrimination, we turned to computational analysis of the TS to provide further evidence for these hypotheses. 15b,15c,15e,15f,15h,17,21 …”