A convolutional neural network based tool for predicting protein AMPylation sites from binary profile representation.

ABSTRACT: AMPylation is an emerging post-translational modification that occurs on the hydroxyl group of threonine, serine, or tyrosine via a phosphodiester bond. AMPylators catalyze this process as covalent attachment of adenosine monophosphate to the amino acid side chain of a peptide. Recent studies have shown that this post-translational modification is directly responsible for the regulation of neurodevelopment and neurodegeneration and is also involved in many physiological processes. Despite the importance of this post-translational modification, there is no peptide sequence dataset available for conducting computation analysis. Therefore, so far, no computational approach has been proposed for predicting AMPylation. In this study, we introduce a new dataset of this distinct post-translationa

SUBMITTER: Azim SM 

PROVIDER: S-EPMC9259580 | biostudies-literature | 2022 Jul

REPOSITORIES: biostudies-literature