Systematic analysis of non-structural protein features for the prediction of PTM function potential by artificial neural networks.

ABSTRACT: Post-translational modifications (PTMs) provide an extensible framework for regulation of protein behavior beyond the diversity represented within the genome alone. While the rate of identification of PTMs has rapidly increased in recent years, our knowledge of PTM functionality encompasses less than 5% of this data. We previously developed SAPH-ire (Structural Analysis of PTM Hotspots) for the prioritization of eukaryotic PTMs based on function potential of discrete modified alignment positions (MAPs) in a set of 8 protein families. A proteome-wide expansion of the dataset to all families of PTM-bearing, eukaryotic proteins with a representational crystal structure and the application of artificial neural network (ANN) models demonstrated the broader applicability of this approach. Althou

SUBMITTER: Dewhurst HM 

PROVIDER: S-EPMC5321281 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature