Prediction and design of protease enzyme specificity using a structure-aware graph convolutional network.

ABSTRACT: Site-specific proteolysis by the enzymatic cleavage of small linear sequence motifs is a key posttranslational modification involved in physiology and disease. The ability to robustly and rapidly predict protease-substrate specificity would also enable targeted proteolytic cleavage by designed proteases. Current methods for predicting protease specificity are limited to sequence pattern recognition in experimentally derived cleavage data obtained for libraries of potential substrates and generated separately for each protease variant. We reasoned that a more semantically rich and robust model of protease specificity could be developed by incorporating the energetics of molecular interactions between protease and substrates into machine learning workflows. We present Protein Graph Convoluti

SUBMITTER: Lu C 

PROVIDER: S-EPMC10523478 | biostudies-literature | 2023 Sep

REPOSITORIES: biostudies-literature