Biological Magnetic Resonance Databank: Metabolomics / Small Molecule Activities

University Of Wisconsin-Madison, Madison WI

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Linked publications & trials

Abstract

DESCRIPTION (provided by applicant): This request responds to Notice Number (NOT-OD-09-058) / Notice Title (NIH Announces the Availability of Recovery Act Funds for Competitive Revision Applications). It is a competitive revision to P41 LM005799. BioMagResBank (BMRB) is the unique worldwide resource that provides free access to the wealth of information on biomolecules derived from nuclear magnetic resonance (NMR) spectroscopy. The community BMRB serves includes scientists in the fields of structural biology, structural genomics, biology, biochemistry, metabolomics, protein and nucleic acid chemistry, natural products, drug design, bioinformatics, and software development. BMRB maintains an open architecture and a defined and flexible data model that makes it possible to respond rapidly to changes in standards for data exchange and NMR technology. Data archived at BMRB include primary data sets and derived results, such as chemical shifts, couplings, and cross relaxations associated with covalent structure and conformation. The original focus for BMRB was on proteins and nucleic acids;however, in response to the 2004 NIH Roadmap Initiative in metabolomics, BMRB began the development of an archive and associated bioinformatics tools for small molecules. In addition, with encouragement from the Worldwide Protein Data Bank, BMRB began accepting NMR structures of small biomolecules. Because of a new funding cap, the current BMRB budget will be reduced by 30% starting on 9/15/2009. Funds requested here will enable BMRB to continue its metabolomics and small molecule work until a new funding mechanism can be found. Metabolomics of high interest to clinicians as a method for determining functional states of cells and tissues and for identifying effects of drugs. NMR spectroscopy provides a non-biased survey of small molecules, but spectral interpretation relies critically on the availability of highly reliable data from model compounds. Software developers use the BMRB metabolomics archive to create automated methods for identifying and quantifying compounds in complex mixtures. A powerful approach to metabolomics combines mass spectrometry (MS) data with NMR data, and BMRB is collaborating with scientists who are generating MS data on standard compounds.