Computational design of 3C-like protease substrate peptide for modular detection of protease activity of coronavirus

The severity of the recent Coronavirus Disease 2019 pandemic stresses the importance of analytical and biosensor research aimed at determining and curbing disease severity. It demanded an easy-to-adapt method to reflect the infectivity of viruses. The critical role of 3C-Like protease (3CL^Pro) in the replication cycle of coronaviruses, such as SARS-CoV-2, highlights its potential as an effective target correlated with viral activities. In this study, we aimed to develop a modular and orthogonal analytical tool for the detection and quantification of the essential protease component of coronaviruses, focusing on the enzymatic activity of the viral 3CL^Pro, a key component for coronavirus replication. Our approach leveraged the high sequence conservation of 3CL^Pro across global coronavirus strains, particularly in its substrate recognition pocket, to computationally design optimal substrate peptides. The designed sequences were orthogonal to any natural viral protein sequences. When incorporated into Gluc or FlipGFP proteins, our designs achieved modular gain-of-signal or loss-of-signal detections of 3CL^Pro expression levels. These antigen-focused molecular tools could facilitate the screening of effective treatments and quantitative visualization of virus-infected cells.