ABSTRACT
The three-dimensional structure and the molecular interaction of proteins determine their roles in many cellular processes. Chemical protein painting with protein mass spectrometry can identify changes in structural conformations and molecular interactions of proteins including their binding sites. Nevertheless, most current protein painting techniques identify protein targets and binding sites of drugs in vitro using a cell lysate or purified protein. Here, we tested 11 membrane-permeable lysine-reactive chemical probes for intracellular covalent labeling of endogenous proteins, which reveals ortho-phthalaldehyde (OPA) as the most reactive probe in the intracellular environment. An MS workflow and a new data analysis strategy termed RAPID (Reactive Amino acid Profiling by Inverse Detection) was developed to enhance detection sensitivity. RAPID with OPA successfully identified structural changes induced by the allosteric drug TEPP-46 on its target protein PKM2 and was applied to profile the conformation change of the proteome occurring in cells during thermal denaturation. The application of RAPID-OPA on cells treated with geldanamycin, selumetinib, and staurosporine successfully revealed their binding sites on target proteins. Thus, RAPID-OPA for cellular protein painting enables the identification of ligand-binding sites and detection of protein structural changes occurring in cells.
ABSTRACT
Cellular activities are carried out vastly by protein complexes but large repertoire of protein complexes remains functionally uncharacterized which necessitate new strategies to delineate their roles in various cellular processes and diseases. Thermal proximity co-aggregation (TPCA) is readily deployable to characterize protein complex dynamics in situ and at scale. We develop a version termed Slim-TPCA that uses fewer temperatures increasing throughputs by over 3X, with new scoring metrics and statistical evaluation that result in minimal compromise in coverage and detect more relevant complexes. Less samples are needed, batch effects are minimized while statistical evaluation cost is reduced by two orders of magnitude. We applied Slim-TPCA to profile K562 cells under different duration of glucose deprivation. More protein complexes are found dissociated, in accordance with the expected downregulation of most cellular activities, that include 55S ribosome and respiratory complexes in mitochondria revealing the utility of TPCA to study protein complexes in organelles. Protein complexes in protein transport and degradation are found increasingly assembled unveiling their involvement in metabolic reprogramming during glucose deprivation. In summary, Slim-TPCA is an efficient strategy for characterization of protein complexes at scale across cellular conditions, and is available as Python package at https://pypi.org/project/Slim-TPCA/ .