Computational Large-Scale Screening of Bioorthogonal 1,2,4,5-Tetrazine/trans-Cyclooctene Cycloadditions

Abstract

Bioorthogonal reactions between 1,2,4,5-tetrazines and trans-cyclooctenes have emerged as valuable chemical tools in the fields of chemical biology and material science, and they hold significant potential for medical applications. The most critical attribute of such reactions is their rate. Experimental investigations into the reactivity of 1,2,4,5-tetrazines are time-consuming and costly. In contrast, computational screenings can rapidly identify reactants that exhibit desired reactivity. In this study, we introduce a tool for automated computational screening that assesses the reactivity of a large pool of tetrazines. This effort has produced an initial dataset of 1,288 reaction barriers, which can be utilized to develop machine learning models.