Computational Library\nEnables Pattern Recognition\nof Noncovalent Interactions and Application as a Modern Linear Free\nEnergy Relationship

A quantitative\nand predictive understanding of how attractive\nnoncovalent\ninteractions (NCIs) influence functional outcomes is a long-standing\ngoal in mechanistic chemistry. In that context, better comprehension\nof how substituent effects influence NCI strengths, and the origin\nof those effects, is still needed. We sought to build a resource capable\nof elucidating fundamental origins of substituent effects in NCIs\nand diagnosing NCIs in chemical systems. To accomplish this, a library\nof 893 NCI energies was calculated encompassing cation−π,\nanion−π, CH−π, and π–π\ninteractions across 60 different arenes and heteroarenes. The interaction\nenergies (IEs) were calculated using symmetry-adapted perturbation\ntheory (SAPT), which identifies electrostatic, inductive, exchange-repulsive,\nand dispersive contributions to total IE. This descriptor library\nprovides a comprehensive platform for evaluating substituent effect\ntrends beyond traditional molecular descriptors such as Hammett values,\nfrontier molecular orbital energies, and electrostatic potential,\nthereby expanding the tools available to analyze modern chemical processes\nthat involve NCIs. To demonstrate the application of this library,\nthree case studies in asymmetric catalysis and supramolecular chemistry\nare presented. These case studies informed the development of an automated\nNCI analysis tool, which employs statistical analyses to diagnose\na particular NCI in a chemical system of interest.