An automated system designed for large scale NMR data deposition and annotation: application to over 600 assigned chemical shift data entries to the BioMagResBank from the Riken Structural Genomics/Proteomics Initiative internal database
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Biomolecular NMR chemical shift data are key information for the functional analysis of biomolecules and the development of new techniques for NMR studies utilizing chemical shift statistical information. Structural genomics projects are major contributors to the accumulation of protein chemical shift information. The management of the large quantities of NMR data generated by each project in a local database and the transfer of the data to the public databases are still formidable tasks because of the complicated nature of NMR data. Here we report an automated and efficient system developed for the deposition and annotation of a large number of data sets including 1H, 13C and 15N resonance assignments used for the structure determination of proteins. We have demonstrated the feasibility of our system by applying it to over 600 entries from the internal database generated by the RIKEN Structural Genomics/Proteomics Initiative (RSGI) to the public database, BioMagResBank (BMRB). We have assessed the quality of the deposited chemical shifts by comparing them with those predicted from the PDB coordinate entry for the corresponding protein. The same comparison for other matched BMRB/PDB entries deposited from 2001–2011 has been carried out and the results suggest that the RSGI entries greatly improved the quality of the BMRB database. Since the entries include chemical shifts acquired under strikingly similar experimental conditions, these NMR data can be expected to be a promising resource to improve current technologies as well as to develop new NMR methods for protein studies.
KeywordsNMR Chemical shift Proteomics Database BMRB
This work was partially supported by National Bioscience Database Center (NBDC) in Japan Science and Technology Agency (JST). We are grateful to Prof. Haruki Nakamura for intensive encouragement to us and for contribution to discussions about this study. We thank Dr. J. Doreleijers for many valuable comments, suggestions and proofreading of the manuscripts and Dr. F. Delaglio for help in establishing the macro-file library for the NMR-Pipe data process. We also thank Mr. T. Iwata for his work in preparing the web-page for downloading the BMRB related tools.
- Fogh R, Ionides J, Ulrich E, Boucher W, Vranken W, Linge JP, Habeck M, Rieping W, Bhat TN, Westbrook J, Henrick K, Gilliland G, Berman H, Thornton J, Nilges M, Markley J, Laue E (2002) The CCPN project: an interim report on a data model for the NMR community. Nat Struct Biol 9:416–418CrossRefGoogle Scholar
- Shen Y, Oliver L, Delaglio F, Rossi P, Aramini J, Liu G, Eletsky A, Wu Y, Singarapu KK, Lemak A, Ignatchenko A, Cheryl H, Arrowsmith CH, Szyperski T, Gaetano T, Montelione GT, Baker D, Bax A (2008) Consistent blind protein structure generation from NMR chemical shift data. Proc Natl Acad Sci USA 105:4685–4690ADSCrossRefGoogle Scholar
- Ulrich EL, Markley JL, Kyogoku Y (1989) Creation of a nuclear magnetic resonance data repository and literature database. Protein Seq Data Anal 2:23–37Google Scholar