Embracing enzyme promiscuity with activity-based compressed biosensing.

ABSTRACT: The development of protease-activatable drugs and diagnostics requires identifying substrates specific to individual proteases. However, this process becomes increasingly difficult as the number of target proteases increases because most substrates are promiscuously cleaved by multiple proteases. We introduce a method-substrate libraries for compressed sensing of enzymes (SLICE)-for selecting libraries of promiscuous substrates that classify protease mixtures (1) without deconvolution of compressed signals and (2) without highly specific substrates. SLICE ranks substrate libraries using a compression score (C), which quantifies substrate orthogonality and protease coverage. This metric is predictive of classification accuracy across 140 in silico (Pearson r = 0.71) and

SUBMITTER: Holt BA 

PROVIDER: S-EPMC9939361 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature