Data-Driven Identification of Metal-free Orthogonal Bioorthogonal Cycloaddition Pairs

Mutually orthogonal bioorthogonal reactions are a thriving area of research in chemical biology. Here we present a predictive-driven approach to identify mutually orthogonal pairs among two bioorthogonal reactions: the metal-free 1,3-dipolar cycloaddition (1,3-DC) reaction and the inverse electron-demand Diels–Alder (IEDDA) reaction. Parametrization of both 1,3-dipoles and dipolarophiles structures allowed the development of statistically robust models for predicting the second order rate constants of 1,3-DC reactions. Combination of predictive models were used to identify potential mutually orthogonal reactions among sets of structurally different pairs.