The use of computed interaction energies and distances as parameters in multivariate correlations is introduced for postulating non-covalent interactions. This new class of descriptors affords multivariate correlations for two diverse catalytic systems with unique non-covalent interactions at the heart of each process. The presented methodology is validated by directly connecting the non-covalent interactions defined through empirical data set analyses to the computationally derived transition states.
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Orlandi et al. (2017) studied this question.
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