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With best regards,
Thomas Szyperski, Professor of Chemistry
Sriram Sankaran, IT Specialist
Dear NMR friends,
In support of the central mission of the NMR 2.0 site, which is to enable the efficient sharing and dissemination of NMR knowledge using ‘Web 2.0’ capabilities, our site was enhanced significantly since the end of 2009.
1) A search algorithm was implemented to ‘filter’ records by keywords in individual sections.
2) Tagging of records is now optional for their improved organization.
3) Subscribed users are now able to comment on individual records to share their experiences.
4) The “Google custom search engine” was incorporated and searches both NMR 2.0 and a complementary NMR wiki (http://nmrwiki.org).
5) Each record is now displayed along with an icon indicating the file type of the record (e.g., wmv, gif, jpeg, pdf, or Microsoft Word, Excel, or Powerpoint).
6) A ‘share bookmarking button’ was introduced for all records located in Resources, Links, Blog and the NESG NMR Wiki. This allows users to email records, or to share them on networking portals such as Facebook.
7) The Jobs section in Resources now also allows researchers looking for a job (‘job seekers’) to post their professional profile along with a description what kind of job they are looking for.
8) The NMR Wiki of the Northeast Structural Genomics Consortium (http://www.nesg.org) was integrated into the NMR 2.0 portal. This enables subscribed users to access both sites with a single login.
The NMR Wiki is based on the open-source Mediawiki package (http://www.mediawiki.org/wiki/MediaWiki) and comprises contributions written by NMR scientists of the Northeast Structural Genomics Consortium (NESG; http:www.nesg.org) working at Miami University (OH, USA), Rutgers University (NJ, USA), the State University of New York at Buffalo (NY, USA), University of Georgia (GA, USA), and the University of Toronto (ON, Canada). It was launched in January 2010 at the Keystone meeting on Structural Genomics.
The NESG NMR wiki serves to efficiently disseminate established protocols of the NESG high-throughput NMR structure determination pipeline, including those for protein sample preparation, NMR data acquisition, NMR data processing, NMR resonance assignment, and structure calculation, validation and deposition in the Protein Data Bank (PDB; http://www.pdb.org.
In an article (http://sbkb.org/update/2010/03/full/th_psisgkb.2010.09.html) recently posted on the Structural Biology Knowledgebase, the NESG NMR Wiki was highlighted by Maria Hodges, and the complementary nature with the ‘NMR Wiki’ project was discussed by her in a second blog article (http://woodforthetrees.wordpress.com/2010/02/22/a-tale-of-two-wikis/).
We look forward to your contributions to NMR 2.0 (which requires registration), and we welcome articles from experienced researchers for the ‘Blog’ on any issue they consider to be of importance for the NMR community. To contribute articles to the Blog, please send a brief notification to email@example.com and firstname.lastname@example.org.
Last but not least, we truly appreciate your proposals for future improvements which can be posted at http://www.nmr2.buffalo.edu/feedback.
With best regards,
Thomas Szyperski, Professor of Chemistry
Sriram Sankaran, IT Specialist
Residual dipolar couplings (RDCs) had been observed as early as 1963  in nematic environments. A number of recent applications [2-7] have reignited their wide use in application to a broad spectrum of biomolecules. RDCs have been used in studies of carbohydrates [8-10], nucleic acids [11-13] and proteins [14-16] to mention a few. Residual dipolar couplings can be acquired very rapidly and accurately by a number of techniques including direct measurement of splittings in coupled heteronuclear single quantum coherence spectra (HSQC) [17-19] and provide simultaneous structural [4;15;20] and motional [5;7;13;21-23] information.
RDCs arise from the interaction of two magnetically active nuclei in the presence of the external magnetic field of a NMR instrument [3;4]. This interaction is normally reduced to zero due to the isotropic tumbling of molecules in their aqueous environment. The introduction of a partial order to the molecular alignment by minutely limiting their isotropic tumbling will resurrect the RDC observable. This partial order can be introduced by either magnetic anisotropy of the molecule , a crystalline aqueous solution  as illustrated in Figure1 or incorporation of artificial tags with magnetic anisotropy susceptibility such as Lanthanide . Equation 1 describes the time average observable of the RDC interaction between a pair of spin ½ nuclei.
Here, Dij denotes the residual dipolar coupling in units of Hz between nuclei i and j, γi and γj are nuclear magnetogyric ratios, rij is the internuclear distance (assumed fixed for directly bonded atoms) and θij(t) is the time dependent angle of the internuclear vector with respect to the external magnetic field. The angle brackets signify the time average of the quantity.
Simple algebraic manipulation of equation 1 produces the more familiar formulation of RDC interaction shown in Equation 2.
The indexes k and l in Eq 2 denote the orthonormal basis sets that span the Cartesian space and . Entities skl in this equation represent various components of anisotropy, are referred to as the elements of the Saupe order tensor matrix, and are defined by Eq 3. Note that the entities represent the direction cosine of the vector connecting nuclei i and j to the k-th axis of the molecular frame. Equation 4 illustrates a more familiar form of this equation after expansion of the two embedded summations in Eq 2.
 Saupe, A & Englert, G. Phys. rev. lett;high-resolution nuclear magnetic resonance spectra of orientated molecules. Phys. Rev. Lett (1963) 11: pp. 462-464.
 Zhou, H J, Vermeulen, A, Jucker, F M & Pardi, A. Biopolymers;incorporating residual dipolar couplings into the nmr solution structure determination of nucleic acids. Biopolymers (1999) 52: pp. 168-180.
 Prestegard JH AH&TJ. Nmr structures of biomolecules using field oriented media and residual dipolar couplings. Q. Rev. Biophys. (2000) 33: p. pp. 371-424.
 Bax A, Kontaxis G & Tjandra N. Dipolar couplings in macromolecular structure determination. In Nuclear Magnetic Resonance of Biological Macromolecules, Pt B. . 2001. p. pp. 127-174.
 Tolman JR. Dipolar couplings as a probe of molecular dynamics and structure in solution. Curr. Opin. Struct. Biol. (2001) 11: pp. 532-539.
 de Alba, E & Tjandra, N. Progress in nuclear magnetic resonance spectroscopy;nmr dipolar couplings for the structure determination of biopolymers in solution. Progress in Nuclear Magnetic Resonance Spectroscopy (2002) 40: pp. 175-197.
 Blackledge M. Recent progress in the study of biomolecular structure and dynamics in solution from residual dipolar couplings. Progress in Nuclear Magnetic Resonance Spectroscopy (2005) 46: pp. 23-61.
 Azurmendi HF, Martin-Pastor M & Bush CA. Conformational studies of lewis x and lewis a trisaccharides using nmr residual dipolar couplings. Biopolymers (2002) 63: pp. 89-98.
 Azurmendi HF & Bush CA. Conformational studies of blood group a and blood group b oligosaccharides using nmr residual dipolar couplings. Carbohydr. Res. (2002) 337: p. pp. 905-915.
 Tian F, Al-Hashimi HM, Craighead JL & Prestegard JH. Conformational analysis of a flexible oligosaccharide using residual dipolar couplings. J. Am. Chem. Soc. (2001) 123: p. pp. 485-492.
 Tjandra N, Tate S, Ono A, Kainosho M & Bax A. The nmr structure of a dna dodecamer in an aqueous dilute liquid crystalline phase. J. Am. Chem. Soc. (2000) 122: p. pp. 6190-6200.
 Vermeulen, A, Zhou, H J & Pardi, A. ;determining dna global structure and dna bending by application of nmr residual dipolar couplings. J. Am. Chem. Soc. (2000) 122: pp. 9638-9647.
 Al-Hashimi HM, Gosser Y, Gorin A, Hu WD, Majumdar A & Patel DJ. Concerted motions in hiv-1 tar rna may allow access to bound state conformations: rna dynamics from nmr residual dipolar couplings. J. Mol. Biol. (2002) 315: p. pp. 95-102.
 Tian F, Valafar H & Prestegard JH. A dipolar coupling based strategy for simultaneous resonance assignment and structure determination of protein backbones. J. Am. Chem. Soc. (2001) 123: pp. 11791-11796.
 Cornilescu G, Delaglio F & Bax A. Protein backbone angle restraints from searching a database for chemical shift and sequence homology. J. Biomol. NMR (1999) 13: pp. 289-302.
 Clore GM & Bewley CA. Using conjoined rigid body/torsion angle simulated annealing to determine the relative orientation of covalently linked protein domains from dipolar couplings. Journal of Magnetic Resonance (2002) 154: p. pp. 329-335.
 Bodenhausen, G & Ruben, DJ. Chemical physics letters;natural abundance n-15 nmr by enhanced heteronuclear spectroscopy. Chemical Physics Letters (1980) 69: pp. 185-189.
 Bax, A, Vuister, G W, Grzesiek, S, Delaglio, F, Wang, A C, Tschudin, R & Zhu, G. Measurement of homonuclear and heteronuclear j-couplings from quantitative j-correlation. In Nuclear Magnetic Resonance, Pt C. . 1994. p. pp. 79-105.
 Tolman, J R & Prestegard, JH. Journal of magnetic resonance series b;measurement of amide n-15-h-1 one-bond couplings in proteins using accordion heteronuclear-shift-correlation experiments. Journal of Magnetic Resonance Series B (1996) 112: pp. 269-274.
 Delaglio F, Kontaxis G & Bax A. Protein structure determination using molecular fragment replacement and nmr dipolar couplings. J. Am. Chem. Soc. (2000) 122: pp. 2142-2143.
 Bernado P & Blackledge M. Local dynamic amplitudes on the protein backbone from dipolar couplings: toward the elucidation of slower motions in biomolecules. J. Am. Chem. Soc. (2004) 126: pp. 7760-7761.
 Al-Hashimi HM, Gosser Y, Gorin A, Hu WD, Majumdar A & Patel DJ. Concerted motions in hiv-1 tar rna may allow access to bound state conformations: rna dynamics from nmr residual dipolar couplings. J. Mol. Biol. (2002) 315: pp. 95-102.
 Yi X, Venot A, Glushka J & Prestegard JH. Glycosidic torsional motions in a bicelle-associated disaccharide from residual dipolar couplings. J. Am. Chem. Soc. (2004) 126: pp. 13636-13638.
 Bax A. Weak alignment offers new nmr opportunities to study protein structure and dynamics. Protein Science (2003) 12: pp. 1-16.
 Prestegard JH, al-Hashimi HM & Tolman JR. Nmr structures of biomolecules using field oriented media and residual dipolar couplings. Q. Rev. Biophys. (2000) 33: pp. 371-424.
 Prestegard JH & Kishore A. Current opinion in structural biology;partial alignment of biomolecules: an aid to nmr characterization. Curr. Opin. Struct. Biol. (2001) 5: pp. 584-590.
 Nitz M, Sherawat M, Franz KJ, Peisach E, Allen KN & Imperiali B. Structural origin of the high affinity of a chemically evolved lanthanide-binding peptide. Angewandte Chemie-International Edition (2004) 43: pp. 3682-3685.
 Valafar, H. & Prestegard, J.H.. Redcat: a residual dipolar coupling analysis tool. J. Magn. Reson. (2004) 167: p. p. p. 228-41..
 Losonczi J, Andrec M, Fischer M & Prestegard J. Order matrix analysis of residual dipolar couplings using singular value decomposition. Journal of Magnetic Resonance (1999) 138: pp. 334-342.
 Bryson M, Tian F, Prestegard JH & Valafar H. Redcraft: a tool for simultaneous characterization of protein backbone structure and motion from rdc data. J. Magn. Reson. (2008) 191: pp. 322-334.
 Miao X, Mukhopadhyay R & Valafar H. Estimation of relative order tensors, and reconstruction of vectors in space using unassigned rdc data and its application. Journal of Magnetic Resonance (2008) 194: pp. 202-211.
I would like to point our a unique resource for the biological NMR community, the Structural Genomics Knowledgebase (http://kb.psi-structuralgenomics.org/KB/index.jsp).
This resource is organized by Prof. Helen Berman (Director of the PDB) in collaboration with the the United States Protein Structure Initiative (PSI) and the Nature publishing group.
The KB provides comprehensive information on various aspects of structural genomics. A unique feature of the PSI-KB is the ability to blast a protein sequence against the target lists of all PSI Centers. This provides information on expression vectors, which are freely available, protocols for sample production, experimental structures, and 3D models of the target protein as well as for many homologous proteins. This is a tremendous resource for obtaining information and reagents for hypothesis-driven biology and structural biology projects.
The PSI KB also provides a portal for nominating proteins targets for structure determination by the PSI Centers: (http://kb.psi-structuralgenomics.org/KB/targetlogin.jsp) This represents a unique opportunity for biologists, or structural biologists, to obtain three-dimensional structural information on proteins they are specifically interested in.
The site also highlights recent papers from the structural biology literature, as well as papers describing recent technical advances.
Another unique feature is access to a collection of protein NMR data sets for the ongoing NMR-Critical Assessment of Protein Structure Determination Methods (NMR-CASD) project. New NMR structures are placed on hold for 8 weeks in the PDB and the corresponding chemical shift, NOESY peak list, and other data are made publicly available for testing new methods for automated NMR data analysis and/or protein structure prediction.http://kb.psi-structuralgenomics.org/KB/datasets.html
The PSI Technology Portal, linked under PSI Resources, provides descriptions of many new technologies that have been developed by the PSI project. http://kb.psi-structuralgenomics.org/KB/index1.jsp?pageshow=41
Other PSI-KB modules include Models – a data base of hundreds of thousands of homology models of protein structures, Annotation – a database of functional annotations of proteins solved in PSI project, and Metrics – a summary of metrics of success of the PSI project.
The BioMedical Themes module of the PSI-KB http://kb.psi-structuralgenomics.org/KB/index1.jsp?pageshow=85 describes the biomedical themes of the four large PSI Structure Production Centers; e.g. the primary biomedical themes of the NESG Consortium include the the network of human proteins associated with cancer biology, the several Ub and Ub-like pathways in higher eukaryotes, and the repertoires of membrane-associated lipoproteins in E coli and B subtilis, which are important antibiotic drug targets.
The PSI Knowledge Base, with links to the PSI Reagent Repository of protein expression vectors, provides a valuable resource of information and reagents that are highly enabling to protein biochemistry, cell biology, immunology, neurobiology, infectious disease, as well as proteomics and structural biology.
“The application of system biology to drug discovery presents a powerful tool to find out toxicity and efficacy problems prior to initiating clinical trials. As a disease state reflects a certain perturbation in the operation of a network at the cellular level, the comparison of these healthy and diseased networks identifies critical intersection points that are associated with disease markers and drug activity.”1 So how can we analyze the states of these networks? One solution is the analysis of the metabolome, a study of the complete set of small molecules along with the associated biological networks within a living cell.
The perturbation of cellular metabolism can be affected by many approaches such as the use of chemical, biological, or environmental factors. For example, the function of an enzyme may be affected by drugs or genetic mutations, measuring changes in metabolite concentrations provides direct information on changes in the cellular activity of the affected enzyme.2 Other factor that may perturb an enzyme’s activity and induce variations in the metabolome include environmental factors such as temperature, time (cell phase), pH, oxygen levels, nutrient concentration or nutrient limitations.
We use NMR to detect these metabolome perturbations by following changes in the intensities of NMR resonances resulting from metabolite concentrations fluxes in cell lysates or biofluids. There are three methods that we are commonly using to follow changes in a series of NMR spectra caused by metabolome perturbations: subtraction of an average 1D 1H NMR spectra collected between two or more different cellular states, the comparison of crosspeak intensity differences between 2D 1H TOCSY or 2D 1H-13C HSQC spectra from cell lysates, and the principal component analysis (PCA) of a collection of 1D 1H NMR spectra from cell lysates.3 The first two approaches allow us to identify the metabolites, and thus the metabolic pathways, that incur a significant change in concentration (≥ 5-fold) as a result of the environmental stimulus. Specifically, wild-type cells under normal growth conditions are compared against cells grown under various environmental conditions or mutant cell lines.
Alternatively, PCA highlights global differences and similarities between NMR spectra obtain from cells grown under these various conditions. Our differential NMR metabolomics method compares NMR spectra from cell lysates collected from wild-type and mutant cells to determine if an environmental factor or drug has the same impact on the metabolome as a genetically inactivated protein. In effect, we are monitoring the cellular mechanism of the drug. Does it demonstrate in vivo efficacy and selectivity? Does it exhibit possible toxic side-effects? In a similar manner, we can follow cellular processes and address system biology questions such as: is there a metabolic signaling pathway that controls biofilm formation?
PCA data is presented as a 2D scores plot where the coordinate axis corresponds to the principal components representing the directions of the two largest variations in the NMR data set (PC1, PC2). PCA reduces a multivariable NMR spectrum into a single point in the 2D scores plot, where similar spectra will cluster together in the plot.1 Thus, NMR spectra collected from cell lysates for a wild-type cell line will cluster distinctly from NMR spectra obtained from mutant cells because the protein target of a drug has been inactivated. The NMR spectra are different because the metabolome for the mutant cells has changed because of the loss of protein activity. Conversely, NMR spectra collected for wild-type cells treated with the drug would be expected to cluster together with NMR spectra obtained from the mutant cells if the drug is active and selective. In this case the two metabolomes would be similar because the same protein was inactivated, either genetically or chemically. Different clustering patterns in the 2D scores plot are observed for inactive drugs, non-selective binding drugs and drugs that exhibit potential toxic side-effects.
You could find out more about our differential NMR metabolomics technique and access our related publications at the Powers’ Group web site ( http://bionmr-c1.unl.edu/).
1. P. Forgue, S. Halouska, M. Werth, K. Xu, S. Harris and R. Powers (2006) “NMR Metabolic Profiling of Aspergillus nidulans to Monitor Drug and Protein Activity.”, Journal of Proteome Research, 5(8):1916-1923
2. S. Halouska, O. Chacon, R. Fenton, D. Zinniel, R. Barletta, and R. Powers (2007) “Use of NMR Metabolomics to Analyze the Targets of D-cycloserine in Mycobacteria: Role of D-Alanine Racemase.”, Journal of Proteome Research, 6(12):4608-4614.
3. M. R. Sadykov, M. E. Olson, S. Halouska, Y. Zhu, P. D. Fey, R. Powers, and G. A. Somerville (2008) “Tricarboxylic acid cycle dependent regulation of Staphylococcus epidermidis polysaccharide intercellular adhesin synthesis.” Journal of Bacteriology, 130(23):7621-7632
NMR spectroscopy has always been tagged as a method plagued with low sensitivity. This is no longer true, thanks to the recent methodological and technological developments, which have pushed sensitivity of NMR to new levels. Recent technological developments include new generation cryogenic probes affording more than four-fold gain in sensitivity (see http://www.varianinc.com/cgi-bin/nav?products/nmr/probes/liquids/cold_probes/index&cid=KMQKOINJFN and http://www.bruker-biospin.com/cryoprobe_micro.html). However, what has caught attention lately is the demonstration of high levels of sensitivity achieved using Dynamic Nuclear Polarization (DNP) (Ardenkjær-Larsen et al. Proc. Natl. Acad. Sci. USA 100, 10158-10163 (2003)). This method belongs to the general class of hyperpolarization methods, which were proposed more than five decades ago. DNP has been in use in solid-state NMR, but its demonstration in solution state and for MRI has opened new avenues for rapid data collection.
DNP is based on the idea of transferring the high electron spin polarization (600 times that of nucleus) onto nuclear spins. The mechanism requires unpaired electrons, which are added to the sample (such as a free radical). In order for the DNP process to be effective, the radical must be distributed homogenously throughout the sample. The high electron spin polarization is transferred to the nuclear spins by microwave irradiation over a long period of time (a few hours). This is carried out at low magnetic field strengths (3.5 T) and low temperatures (1-2 K) wherein the sample is in a solid form. After polarization the sample is rapidly dissolved in a solvent and immediately transferred to another magnet for high-resolution NMR measurements. A very high sensitivity (~700 times) arising from the increased polarization has been demonstrated which allows (1) the use of much smaller amounts of sample material and (2) faster data acquisition. Other applications include ability to acquire 13C spectra of molecules directly with high sensitivity, using the enhanced signal to carry out chemical kinetic experiments. Commercialization of this method has already begun with Oxford instruments coming out with a DNP polarizer called “Hypersense” (http://www.oxford-instruments.com/products/dnp/hyperSense/Pages/hyperSense.aspx)
Currently, a few constraints limit the widespread use of the method for multidimensional NMR spectroscopy. First, the dead time for the transfer of the sample from the polarizer to the high field magnet required for recording the spectra should be less than the T1 relaxation of the sample. Carrying out the polarization and the subsequent desired NMR experiment in the same magnet could minimize this dead time. Second, during signal averaging or multiple scans as required for acquiring multidimensional NMR spectra, the polarization decays rapidly. One elegant means to overcome this limitation is the use of ultrafast single-scan NMR method (Frydman and Blazina, Nature Physics 3, 415-419 (2007)). Further developments are required to achieve progress in this direction. Taken together, the DNP method will emerge in the forefront in coming years.
Welcome to the new NMR 2.0 web site which is supposed to help all scientists pursuing NMR-based research to share and compile information, and to foster exchange of knowledge.
It is possible to upload URLs as links, as well as files of various formats in three sections, i.e., ‘Resources’,'Links’ and ‘Entertainment’. The ‘Links’ section is eventually supposed to provide all web links which we routinely use. Since all registered users can provide links, this page may eventually provide all links that are now compile on ‘traditional’ link pages. Please note that links uploaded in the sections ‘Resources’ and ‘Entertainment’ are simultaneously introduced in the ‘Links’ section.
In addition NMR 2.0 offers ‘web 2.0′ features such as RSS feeds.
We hope that you appreciate this site and look forward to your contributions.
The blog of NMR 2.0 will be used by senior researchers to contribute articles outlining new developments, suggestions and information on issues that are of importance to the NMR Community.