To better understand biological systems regulation at the molecular scale, Professors Mitchell and Torres will develop new predictive features and a machine learning model to identify regions within Instrinsically Disordered Regions (IDRs) able to undergo structural transitions following Post-Translational Modification (PTM). Our study of PTMs will initially focus on phosphorylation and use available protein structures for phosphorylated isoforms. We will pursue a machine learning approach based on evolutionary and sequence-based features. We will experimentally validate phospho-regulated IDR predictions. In vitro, candidate proteins expressed in recombinant form will be analyzed in comparison to established controls using experimental spectroscopic methods. In vivo, candidate IDR-containing proteins will be genetically engineered to control their phosphorylation and order/disorder states, and tested for impact on biological function. From this work, we expect to learn how PTMs can modulate protein function by minimizing the ensemble of potential IDR structural states, and reveal features of proteins that make this possible.