Energetics-based discovery of protein-ligand interactions on a proteomic scale |
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Authors: | Liu Pei-Fen Kihara Daisuke Park Chiwook |
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Affiliation: | 1 Department of Medicinal Chemistry and Molecular Pharmacology, Purdue University, West Lafayette, IN 47907, USA2 Interdisciplinary Life Science Program, Purdue University, West Lafayette, IN 47907, USA3 Department of Biological Sciences, Purdue University, West Lafayette, IN 47907, USA4 Department of Computational Science, Purdue University, West Lafayette, IN 47907, USA5 Markey Center for Structural Biology, Purdue University, West Lafayette, IN 47907, USA6 Bindley Bioscience Center, Purdue University, West Lafayette, IN 47907, USA |
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Abstract: | Biochemical functions of proteins in cells frequently involve interactions with various ligands. Proteomic methods for the identification of proteins that interact with specific ligands such as metabolites, signaling molecules, and drugs are valuable in investigating the regulatory mechanisms of cellular metabolism, annotating proteins with unknown functions, and elucidating pharmacological mechanisms. Here we report an energetics-based target identification method in which target proteins in a cell lysate are identified by exploiting the effect of ligand binding on their stabilities. Urea-induced unfolding of proteins in cell lysates is probed by a short pulse of proteolysis, and the effect of a ligand on the amount of folded protein remaining is monitored on a proteomic scale. As proof of principle, we identified proteins that interact with ATP in the Escherichia coli proteome. Literature and database mining confirmed that a majority of the identified proteins are indeed ATP-binding proteins. Four identified proteins that were previously not known to interact with ATP were cloned and expressed to validate the result. Except for one protein, the effects of ATP on urea-induced unfolding were confirmed. Analyses of the protein sequences and structure models were also employed to predict potential ATP binding sites in the identified proteins. Our results demonstrate that this energetics-based target identification approach is a facile method to identify proteins that interact with specific ligands on a proteomic scale. |
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Keywords: | 2D, two-dimensional ATPγS, adenosine 5&prime -[γ-thio]triphosphate GAPDH, glyceraldehyde-3-phosphate dehydrogenase GO, Gene Ontology E3, dihydrolipoamide dehydrogenase FAD, flavin adenine dinucleotide PDB, Protein Data Bank EDTA, ethylenediaminetetraacetic acid TCEP, tris(2-carboxyethyl)phosphine |
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