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Protein–protein interaction networks are the networks of protein complexes formed by biochemical events and/or electrostatic forces and that serve a distinct biological function as a complex. The protein interactome describes the full repertoire of a biological system’s protein–protein interactions (PPIs).
Deep interactome profiling by mass spectrometry (DIP-MS) combines affinity purification with native BN-PAGE fractionation and mass spectrometry to resolve protein complexes sharing the same target protein. The paper also presents PPIprophet, a data-driven neural network-based protein complex deconvolution approach.
ATGL is a key enzyme in intracellular lipolysis. Here, the authors use deep mutational scanning to define the determinants of protein interaction between ATGL and its regulatory partners, gaining insights into lipolysis mechanisms in cells.
A multidimensional proteomics analysis of the interactions between around 2,000 nuclear proteins and over 80 modified dinucleosomes representing promoter, enhancer and heterochromatin states provides insights into how chromatin states are decoded by chromatin readers.
The combination of mass spectroscopy-based proteomics with molecular dynamics enables the in-depth study of metallothioneine-Zn(II) binding mechanisms, critical to cell homeostasis and Zn(II) ion buffering.
Co-fractionation mass spectrometry (CF-MS) has the potential to measure thousands of protein complexes in a single experiment, but the field is still in its infancy. A meta-analysis of CF-MS data yields a core CF-MS interactome and a tool allowing researchers to align new results to published data.