Rapid identification of protein-protein interfaces for the construction of a complex model based on multiple unassigned signals by using time-sharing NMR measurements |
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Authors: | Kodama Yuya Reese Michael L Shimba Nobuhisa Ono Katsuki Kanamori Eiji Dötsch Volker Noguchi Shuji Fukunishi Yoshifumi Suzuki Ei-Ichiro Shimada Ichio Takahashi Hideo |
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Affiliation: | Japan Biological Informatics Consortium (JBIC), Koto-ku, Tokyo, Japan. |
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Abstract: | Protein-protein interactions are necessary for various cellular processes, and therefore, information related to protein-protein interactions and structural information of complexes is invaluable. To identify protein-protein interfaces using NMR, resonance assignments are generally necessary to analyze the data; however, they are time consuming to collect, especially for large proteins. In this paper, we present a rapid, effective, and unbiased approach for the identification of a protein-protein interface without resonance assignments. This approach requires only a single set of 2D titration experiments of a single protein sample, labeled with a unique combination of an (15)N-labeled amino acid and several amino acids (13)C-labeled on specific atoms. To rapidly obtain high resolution data, we applied a new pulse sequence for time-shared NMR measurements that allowed simultaneous detection of a ω(1)-TROSY-type backbone (1)H-(15)N and aromatic (1)H-(13)C shift correlations together with single quantum methyl (1)H-(13)C shift correlations. We developed a structure-based computational approach, that uses our experimental data to search the protein surfaces in an unbiased manner to identify the residues involved in the protein-protein interface. Finally, we demonstrated that the obtained information of the molecular interface could be directly leveraged to support protein-protein docking studies. Such rapid construction of a complex model provides valuable information and enables more efficient biochemical characterization of a protein-protein complex, for instance, as the first step in structure-guided drug development. |
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