Project PP14 aims to conduct a comprehensive (sub)proteome-wide analysis of lipid hydrolases by examining their 3D structures, focusing on active site properties and constellations. This approach will facilitate the prediction of functions for lipid hydrolases with unknown properties. Additionally, we will characterize intrinsically disordered regions using molecular dynamics simulations to generate functionally relevant ensembles and conformations, ultimately enhancing our understanding of the physiological roles of lipid hydrolases. The project will capitalize on recent advances in protein structure prediction to refine existing models and produce ensembles for further analysis. Machine learning techniques will be employed to correlate structural and functional data, enabling the prediction of properties for uncharacterized lipid hydrolases. Lastly, we will utilize molecular dynamics simulations to obtain physiologically relevant conformations of unstructured regions in these enzymes, with a particular focus on ATGL and its inhibitor, G0S2.
