PEDS Advance Access originally published online on January 10, 2006
Protein Engineering Design and Selection 2006 19(2):67-75; doi:10.1093/protein/gzj002
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© The Author (2006). Published by Oxford University Press. All rights reserved.
An empirical approach for detecting nucleotide-binding sites on proteins
1Division of Biological Science, Graduate School of Science, Nagoya University, Furo-cho, Chikusa-ku, Nagoya 464-8603, Japan 2Ochanomizu University, 211 Otsuka, Bunkyo-ku, Tokyo 112-8601, Japan 3Department of Bioscience, Nagahama Institute of Bioscience and Technology, 1266 Tamura, Nagahama 526-0829, Japan 4Department of Computational Biology, Biomolecular Engineering Research Institute, 623 Furuedai, Suita, Osaka 565-0874, Japan 5Japan Science and Technology CorporationBioinformatics Research and Development
6 To whom correspondence should be addressed at Nagahama Institute of Bioscience and Technology. E-mail: t_shirai{at}nagahama-i-bio.ac.jp
Protein structure data in the PDB (Protein Data Bank) were used to construct empirical scores of nucleotideprotein interactions. A simple strategy to evaluate the spatial distribution of protein atoms around the base moieties of nucleotides was applied to categorize adenine, guanine, nicotinamide and flavin nucleotide-binding sites. In addition to the known nucleotide-binding motifs, the empirical scores detected several other features that were shared among proteins with different folds. The empirical scores were also used to predict the binding sites on protein molecules and a comprehensive test of the prediction system was performed. As a result, adenine, guanine, nicotinamide and flavin sites were detected with efficiencies of 31, 29, 32 and 40%, respectively. The predictions were judged to be successful if the predicted base with the best score was located within a 3.0 Å r.m.s.d. from the known ligand positions.
Received July 12, 2005; revised November 12, 2005; accepted November 12, 2005.
Edited by Haruki Nakamura