This review discusses strategies for the identification of metabolites in complex biological mixtures, as encountered in metabolomics, which have emerged in the recent past. These include NMR database-assisted approaches for the identification of commonly known metabolites as well as novel combinations of NMR and MS analysis methods for the identification of unknown metabolites. The use of certain chemical additives to the NMR tube can permit identification of metabolites with specific physical chemical properties. A fundamental characteristic of all living systems is their extraordinarily high complexity at the molecular level [1,2]. This includes both large and small molecules, most of which are part of complex biochemical reaction networks [3][4][5]. The footprint of all small biological molecules, or metabolites, provides unique information about the state of a living organism, which is a prerequisite for the understanding of the activity of biochemical pathways and their consequences for homeostasis, health and disease, aging, as well as for elucidation of the effect of mutations and other biological, chemical or physical perturbations [6][7][8][9]. Over the past few years, the field of metabolomics (also referred to as 'metabonomics') has assumed a critical role in the comprehensive characterization of the metabolites of biological systems and their relationship to the biological state of an organism [10][11][12][13]. Specifically, metabolomics is providing new insights into the metabolite makeup of biofluids, such as serum and urine, cells, tissues and organs and their role in biochemical pathways [14][15][16]. Metabolomics allows the identification of biomarkers that are characteristic for particular phenotypes, such as a specific disease, even before the 'classical' symptoms occur [17][18][19]. Metabolomics also promises to be useful for monitoring the treatment of many different health conditions and opens up the prospect for new approaches to wellness and personalized medicine [20,21]. Therefore, the biomedical implications of metabolomics are of paramount significance and are expected to continue to rapidly grow in importance due to the high likelihood within this decade of routine applications for diagnosis and treatment of various conditions and diseases based on a wide range of metabolomics tools [22,23].MS and NMR spectroscopy are the two major experimental analysis techniques in metabolomics [24,25]. This is primarily because of the exceptional resolution power of both of these techniques to detect individual metabolites in complex mixtures while requiring little or no purification or physical separation of mixture components [26][27][28] H TOCSY trace displayed as green cross-section is extracted (upper panel). Next, its cross-peaks are queried against the database using the webserver [61]. The query correctly and exclusively assigned the trace to the nicotinamide ring portion of NADP + (see lower panel depicting a snapshot of the web server).future science groupEmerging new strategies for succ...

Protein function depends critically on intrinsic internal dynamics, which is manifested in distinct ways, such as loop motions that regulate protein recognition and catalysis. Under physiological conditions, dynamic processes occur on a wide range of time scales from subpicoseconds to seconds. Commonly used NMR spin relaxation in solution provides valuable information on very fast and slow motions but is insensitive to the intermediate nanosecond to microsecond range that exceeds the protein tumbling correlation time. Presently, very little is known about the nature and functional role of these motions. It is demonstrated here how transverse spin relaxation becomes exquisitely sensitive to these motions at atomic resolution when studying proteins in the presence of nanoparticles. Application of this novel cross-disciplinary approach reveals large-scale dynamics of loops involved in functionally critical protein-protein interactions and protein-calcium ion recognition that were previously unobservable.

Elucidation of the driving forces that govern interactions between nanoparticles and intrinsically disordered proteins (IDP) is important for the understanding of the effect of nanoparticles in living systems and for the design of new nanoparticle-based assays to monitor health and combat disease. The quantitative interaction profile of the intrinsically disordered transactivation domain of p53 and its mutants with anionic silica nanoparticles is reported at atomic resolution using nuclear magnetic spin relaxation experiments. These profiles are analyzed with a novel interaction model that is based on a quantitative nanoparticle affinity scale separately derived for the 20 natural amino acids. The results demonstrate how the interplay of attractive and repulsive Coulomb interactions with hydrophobic effects is responsible for the sequence-dependent binding of a disordered protein to nanoparticles.

Metabolomics aims at a complete characterization of all metabolites in biological samples both in terms of their identities and concentrations. Because changes of metabolites and their concentrations are a direct reflection of cellular activity, it allows a better understanding of cellular processes and function. Although NMR spectroscopy is routinely applied to complex biological mixtures without purification, overlapping NMR peaks often pose a challenge for the comprehensive and accurate identification of the underlying metabolites. To address this problem, we present a novel nanoparticle-based strategy that differentiates between metabolites based on their electric charge. By adding electrically charged silica nanoparticles to the solution NMR sample, metabolites of opposite charge bind to the nanoparticles and their NMR signals are weakened or entirely suppressed due to peak broadening caused by the slow rotational tumbling of the nanometer sized nanoparticles. Comparison of the edited with the original spectrum facilitates analysis significantly and reduces ambiguities in the identification of metabolites. This method makes NMR directly sensitive to the detection of molecular charges at constant pH as is demonstrated here both for model mixtures and human urine. The simplicity of the approach should make it useful for a wide range of metabolomics applications.

The quantitative and comprehensive description of the internal dynamics of proteins is critical for understanding their function. Nanoparticle-assisted 15 N NMR spin relaxation spectroscopy is a new method for the observation of picosecond to microsecond dynamics of proteins when transiently interacting with the surface of the nanoparticles (NPs). The method is applied here to the protein ubiquitin in the presence of anionic and cationic silica NPs (SNPs) of different sizes. The backbone dynamics profiles are reproducible and strikingly similar to each other, indicating that specific protein-SNP interactions are unimportant. The dynamics profiles closely match the sub-nanosecond dynamics S 2 values observed by model-free analysis of standard 15 N relaxation of ubiquitin in free solution, indicating that the bulk of the ubiquitin backbone dynamics in solution is confined to sub-nanosecond timescales and, hence, it is dynamically more restrained than previous NMR studies have suggested.