KUJIRA,a package of integrated modules for systematic and interactive analysis of NMR data directed to high-throughput NMR structure studies

The recent expansion of structural genomics has increased the demands for quick and accurate protein structure determination by NMR spectroscopy. The conventional strategy without an automated protocol can no longer satisfy the needs of high-throughput application to a large number of proteins, with each data set including many NMR spectra, chemical shifts, NOE assignments, and calculated structures. We have developed the new software KUJIRA, a package of integrated modules for the systematic and interactive analysis of NMR data, which is designed to reduce the tediousness of organizing and manipulating a large number of NMR data sets. In combination with CYANA, the program for automated NOE assignment and structure determination, we have established a robust and highly optimized strategy for comprehensive protein structure analysis. An application of KUJIRA in accordance with our new strategy was carried out by a non-expert in NMR structure analysis, demonstrating that the accurate assignment of the chemical shifts and a high-quality structure of a small protein can be completed in a few weeks. The high completeness of the chemical shift assignment and the NOE assignment achieved by the systematic analysis using KUJIRA and CYANA led, in practice, to increased reliability of the determined structure.     

Thermodynamic interpretation of protein dynamics from NMR relaxation measurements

Protein dynamics and thermodynamics can be characterized through measurements of relaxation rates of side chain (2)H and (13)C, and backbone (15)N nuclei using NMR spectroscopy. The rates reflect protein motions on timescales from picoseconds to milliseconds. Backbone and methyl side chain NMR relaxation measurements for several proteins are beginning to reveal the role of protein dynamics in protein stability and ligand binding.     

An introduction to biological nuclear magnetic resonance spectroscopy

Nuclear magnetic resonance (NMR) spectroscopy is one of the most powerful analytical techniques available to biology. This review is an introduction to the potential of this method and is aimed at readers who have little or no experience in acquiring or analyzing NMR spectra. We focus on spectroscopic applications of the magnetic resonance effect, rather than imaging ones, and explain how various aspects of the NMR phenomenon make it a versatile tool with which to address a number of biological problems. Using detailed examples, we discuss the use of ¹H NMR spectroscopy in mixture analysis and metabolomics, the use of ¹³C NMR spectroscopy in tracking isotopomers and determining the flux through metabolic pathways (‘fluxomics’) and the use of ³¹P NMR spectroscopy in monitoring ATP generation and intracellular pH homeotasis in vivo. Further examples demonstrate how NMR spectroscopy can be used to probe the physical environment of a cell by measuring diffusion and the tumbling rates of individual metabolites and how it can determine macromolecular structures by measuring the bonds and distances which separate individual atoms. We finish by outlining some of the key challenges which remain in NMR spectroscopy and we highlight how recent advances—such as increased magnet field strengths, cryogenic cooling, microprobes and hyperpolarisation—are opening new avenues for today's biological NMR spectroscopists.     

NMRDyn: A Program for NMR Relaxation Studies of Protein Association

Self-association is an important biological phenomenon that is associated with many cellular processes. NMR relaxation measurements provide data about protein molecular dynamics at the atomic level and are sensitive to changes induced by self-association. Thus, measurements and analysis of NMR relaxation data can provide structurally resolved information on self-association that would not be accessible otherwise. Here, we present a computer program, NMRdyn, which analyses relaxation data to provide parameters defining protein self-association. Unlike existing relaxation analysis software, NMRdyn can explicitly model the monomer-oligomer equilibrium while fitting measured relaxation data. Additionally, the program is packaged with a user-friendly interface, which is important because relaxation data can often be large and complex. NMRdyn is available from http://research1t.imb.uq.edu.au/nmr/NMRdyn.     

GUARDD: user-friendly MATLAB software for rigorous analysis of CPMG RD NMR data

Molecular dynamics are essential for life, and nuclear magnetic resonance (NMR) spectroscopy has been used extensively to characterize these phenomena since the 1950s. For the past 15 years, the Carr-Purcell Meiboom-Gill relaxation dispersion (CPMG RD) NMR experiment has afforded advanced NMR labs access to kinetic, thermodynamic, and structural details of protein and RNA dynamics in the crucial μs-ms time window. However, analysis of RD data is challenging because datasets are often large and require many non-linear fitting parameters, thereby confounding assessment of accuracy. Moreover, novice CPMG experimentalists face an additional barrier because current software options lack an intuitive user interface and extensive documentation. Hence, we present the open-source software package GUARDD (Graphical User-friendly Analysis of Relaxation Dispersion Data), which is designed to organize, automate, and enhance the analytical procedures which operate on CPMG RD data (). This MATLAB-based program includes a graphical user interface, permits global fitting to multi-field, multi-temperature, multi-coherence data, and implements χ ²-mapping procedures, via grid-search and Monte Carlo methods, to enhance and assess fitting accuracy. The presentation features allow users to seamlessly traverse the large amount of results, and the RD Simulator feature can help design future experiments as well as serve as a teaching tool for those unfamiliar with RD phenomena. Based on these innovative features, we expect that GUARDD will fill a well-defined gap in service of the RD NMR community.     

Characterizing monoclonal antibody formulations in arginine glutamate solutions using 1H NMR spectroscopy

Assessing how excipients affect the self-association of monoclonal antibodies (mAbs) requires informative and direct in situ measurements for highly concentrated solutions, without sample dilution or perturbation. This study explores the application of solution nuclear magnetic resonance (NMR) spectroscopy for characterization of typical mAb behavior in formulations containing arginine glutamate. The data show that the analysis of signal intensities in 1D ¹H NMR spectra, when compensated for changes in buffer viscosity, is invaluable for identifying conditions where protein-protein interactions are minimized. NMR-derived molecular translational diffusion rates for concentrated solutions are less useful than transverse relaxation rates as parameters defining optimal formulation. Furthermore, NMR reports on the solution viscosity and mAb aggregation during accelerated stability study assessment, generating data consistent with that acquired by size-exclusion chromatography. The methodology developed here offers NMR spectroscopy as a new tool providing complementary information useful to formulation development of mAbs and other large therapeutic proteins.     

INCA 2.0: A tool for integrated,dynamic modeling of NMR- and MS-based isotopomer measurements and rigorous metabolic flux analysis

Metabolic flux analysis (MFA) combines experimental measurements and computational modeling to determine biochemical reaction rates in live biological systems. Advancements in analytical instrumentation, such as nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry (MS), have facilitated chemical separation and quantification of isotopically enriched metabolites. However, no software packages have been previously described that can integrate isotopomer measurements from both MS and NMR analytical platforms and have the flexibility to estimate metabolic fluxes from either isotopic steady-state or dynamic labeling experiments. By applying physiologically relevant cardiac and hepatic metabolic models to assess NMR isotopomer measurements, we herein test and validate new modeling capabilities of our enhanced flux analysis software tool, INCA 2.0. We demonstrate that INCA 2.0 can simulate and regress steady-state ¹³C NMR datasets from perfused hearts with an accuracy comparable to other established flux assessment tools. Furthermore, by simulating the infusion of three different ¹³C acetate tracers, we show that MFA based on dynamic ¹³C NMR measurements can more precisely resolve cardiac fluxes compared to isotopically steady-state flux analysis. Finally, we show that estimation of hepatic fluxes using combined ¹³C NMR and MS datasets improves the precision of estimated fluxes by up to 50%. Overall, our results illustrate how the recently added NMR data modeling capabilities of INCA 2.0 can enable entirely new experimental designs that lead to improved flux resolution and can be applied to a wide range of biological systems and measurement time courses.     

Analysis of protein–ligand interactions from titrations and nuclear magnetic resonance relaxation dispersions

We present PLIS, a publicly available, open‐source software for the determination of protein–ligand dissociation constants that can be used to characterize biological processes or to shed light on biophysical aspects of interactions. PLIS can analyze data from titration experiments monitored by for instance fluorescence spectroscopy or from nuclear magnetic resonance relaxation dispersion experiments. In addition to analysis of experimental data, PLIS includes functionality for generation of synthetic data, useful for understanding how different parameters effect the data in order to better analyze experiments.     

Fast and robust two-dimensional inverse Laplace transformation of single-molecule fluorescence lifetime data

Fluorescence spectroscopy at the single-molecule scale has been indispensable for studying conformational dynamics and rare states of biological macromolecules. Single-molecule two-dimensional (2D) fluorescence lifetime correlation spectroscopy is an emerging technique that holds promise for the study of protein and nucleic acid dynamics, as the technique is 1) capable of resolving conformational dynamics using a single chromophore, 2) resolves forward and reverse transitions independently, and 3) has a dynamic window ranging from microseconds to seconds. However, the calculation of a 2D fluorescence relaxation spectrum requires an inverse Laplace transform (ILT), which is an ill-conditioned inversion that must be estimated numerically through a regularized minimization. Current methods for performing ILTs of fluorescence relaxation can be computationally inefficient, sensitive to noise corruption, and difficult to implement. Here, we adopt an approach developed for NMR spectroscopy (T1-T2 relaxometry) to perform one-dimensional (1D) and 2D-ILTs on single-molecule fluorescence spectroscopy data using singular-valued decomposition and Tikhonov regularization. This approach provides fast, robust, and easy to implement Laplace inversions of single-molecule fluorescence data. We compare this approach to the widely used maximal entropy method.     

Hydration and packing along the folding pathway of SH3 domains by pressure-dependent NMR

The volumetric properties associated with protein folding transitions reflect changes in protein packing and hydration of the states that participate in the folding reaction. Here, NMR spin relaxation techniques are employed to probe the folding-unfolding kinetics of two SH3 domains as a function of pressure so that the changes in partial molar volumes along the folding pathway can be measured. The two domains fold with rates that differ by approximately 3 orders of magnitude, so their folding dynamics must be probed using different NMR relaxation experiments. In the case of the drkN SH3 domain that folds via a two-state mechanism on a time scale of seconds, nitrogen magnetization exchange spectroscopy is employed, while for the G48M mutant of the Fyn SH3 domain where the folding occurs on the millisecond time scale (three-step reaction), relaxation dispersion experiments are utilized. The NMR methodology is extremely sensitive to even small changes in equilibrium and rate constants, so reliable estimates of partial molar volumes can be obtained using low pressures (1-120 bar), thus minimizing perturbations to any of the states along the folding reaction coordinate. The volumetric data that were obtained are consistent with a similar folding mechanism for both SH3 domains, involving early chain compaction to states that are at least partially hydrated. This work emphasizes the role of NMR spin relaxation in studying dynamic processes over a wide range of time scales.     

PINT: a software for integration of peak volumes and extraction of relaxation rates

We present the software Peak INTegration (PINT), designed to perform integration of peaks in NMR spectra. The program is very simple to run, yet powerful enough to handle complicated spectra. Peaks are integrated by fitting predefined line shapes to experimental data and the fitting can be customized to deal with, for instance, heavily overlapped peaks. The results can be inspected visually, which facilitates systematic optimization of the line shape fitting. Finally, integrated peak volumes can be used to extract parameters such as relaxation rates and information about low populated states. The utility of PINT is demonstrated by applications to the 59 residue SH3 domain of the yeast protein Abp1p and the 289 residue kinase domain of murine EphB2.     

Backbone dynamics of SDF-1alpha determined by NMR: interpretation in the presence of monomer-dimer equilibrium

SDF-1alpha is a member of the chemokine family implicated in various reactions in the immune system. The interaction of SDF-1alpha with its receptor, CXCR4, is responsible for metastasis of a variety of cancers. SDF-1alpha is also known to play a role in HIV-1 pathogenesis. The structures of SDF-1alpha determined by NMR spectroscopy have been shown to be monomeric while X-ray structures are dimeric. Biochemical data and in vivo studies suggest that dimerization is likely to be important for the function of chemokines. We report here the dynamics of SDF-1alpha determined through measurement of main chain (15)N NMR relaxation data. The data were obtained at several concentrations of SDF-1alpha and used to determine a dimerization constant of approximately 5 mM for a monomer-dimer equilibrium. The dimerization constant was subsequently used to extrapolate values for the relaxation data corresponding to monomeric SDF-1alpha. The experimental relaxation data and the extrapolated data for monomeric SDF-1alpha were analyzed using the model free approach. The model free analysis indicated that SDF-1alpha is rigid on the nano- to picosecond timescale with flexible termini. Several residues involved in the dimer interface display slow micro- to millisecond timescale motions attributable to chemical exchange such as monomer-dimer equilibrium. NMR relaxation measurements are shown to be applicable for studying oligomerization processes such as the dimerization of SDF-1alpha.     

Optimization of NMR analysis of biological fluids for quantitative accuracy

With the rising interest in the use of nuclear magnetic resonance (NMR) for the study of biological fluids such as urine and serum for metabonomic or diagnostic purposes, new challenges have arisen concerning the efficacy of NMR data acquisition and analysis. In particular the quantification of sample constituents such as metabolites is of great importance. This study compares five one-dimensional proton NMR pulse sequences using synthetic urine samples to determine appropriate acquisition parameters for reasonable sample throughput and accuracy. Each pulse sequence has its own advantages and limitations with respect to solvent suppression, stable baseline, exchangeable protons, and quantization of resonances near the residual water peak. Hardware issues such as low-pass filters, unique to each spectrometer, also impact quantitation accuracy. Metabolite concentrations were determined using integration referenced to an added internal standard, and using the Chenomx NMR Suite software package. Since nuclei in different metabolites and the internal standard all have different longitudinal relaxation rates (T ₁) we included a mathematical correction factor for quantitation.     

Nmrglue: an open source Python package for the analysis of multidimensional NMR data

Nmrglue, an open source Python package for working with multidimensional NMR data, is described. When used in combination with other Python scientific libraries, nmrglue provides a highly flexible and robust environment for spectral processing, analysis and visualization and includes a number of common utilities such as linear prediction, peak picking and lineshape fitting. The package also enables existing NMR software programs to be readily tied together, currently facilitating the reading, writing and conversion of data stored in Bruker, Agilent/Varian, NMRPipe, Sparky, SIMPSON, and Rowland NMR Toolkit file formats. In addition to standard applications, the versatility offered by nmrglue makes the package particularly suitable for tasks that include manipulating raw spectrometer data files, automated quantitative analysis of multidimensional NMR spectra with irregular lineshapes such as those frequently encountered in the context of biomacromolecular solid-state NMR, and rapid implementation and development of unconventional data processing methods such as covariance NMR and other non-Fourier approaches. Detailed documentation, install files and source code for nmrglue are freely available at http://nmrglue.com. The source code can be redistributed and modified under the New BSD license.     

On intrinsic equivalences of the finite helical axis,the instantaneous helical axis,and the SARA approach. A mathematical perspective

Accurate determination of joint axes is essential for understanding musculoskeletal function. Whilst numerous algorithms to compute such axes exist, the conditions under which each of the methods performs best remain largely unknown. Typically, algorithms are evaluated for specific conditions only limiting the external validity of conclusions regarding their performance. We derive exact mathematical relationships between three commonly used algorithms for computing joint axes from motion data: finite helical axes (FHA), instantaneous helical axes (IHA) and SARA (symmetrical axis of rotation approach), including relationships for an extension to the mean helical axes methods that facilitate determining joint centres and axes. Through the derivation of a sound mathematical framework to objectively compare the algorithms we demonstrate that the FHA and SARA approach are equivalent for the analysis of two time frames. Moreover, we show that the position of a helical axis derived from the IHA using positional data is affected by a systematic error perpendicular to the true axis direction, whereas the axis direction is identical to those computed with either the FHA or SARA approach (true direction). Finally, with an appropriate choice of weighting factors the mean FHA (MFHA) method is equivalent to the Symmetrical Centre of Rotation Estimation (SCoRE) algorithm for determination of a Centre of Rotation (CoR), and similarly, equivalent to the SARA algorithm for determination of an Axis of Rotation (AoR). The deep understanding of the equivalences between methods presented here enables readers to choose numerically efficient, robust methods for determining AoRs and CoRs with confidence.     

23Na and flame photometric studies of the NMR visibility of sodium in rat muscle.

23Na nuclear magnetic resonance spectroscopy (NMR) is increasingly being used to study Na+ gradients and fluxes in biological tissues. However, the quantitative aspects of 23Na NMR applied to living systems remain controversial. This paper compares sodium concentrations determined by 23Na NMR in intact rat hindlimb (n = 8) and excised rat gastrocnemius muscle (n = 4) with those obtained by flame photometric methods. In both types of samples, 90% of the sodium measured by flame photometry was found to be NMR-visible. This is much higher than previously reported values. The NMR measurements for intact hindlimb correlated linearly with the flame photometric measurements, implying that one pool of sodium, predominantly extracellular, is 100% visible. From measurements on excised muscle, in which extracellular space is more clearly defined, the NMR visibility of intracellular Na+ was calculated to be 70%, assuming an extracellular space of 12% of the total tissue water volume and an extracellular NMR visibility of 100%. 23Na transverse relaxation measurements were carried out using a Hahn spin echo on both intact hindlimb (n = 1) and excised muscle (n = 2) samples. These showed relaxation curves that could each be described adequately using two relaxation times. The rapidly relaxing component showed a T2 value of 3-4 ms and the slowly relaxing component a T2 of 21-37 ms. A spin lattice relaxation (T1) measurement on intact hindlimb yielded a value of 51 ms. These relatively long relaxation times show that the quadrupolar relaxation effect of Na+ complexing to large macromolecules or being otherwise motionally restricted is relatively weak. This is consistent with the high NMR visibilities reported here.     

Inhibition of metastatic potential by fucosidase: an NMR study identifies a cell surface metastasis marker

NMR spectroscopy is able to detect subtle changes to the surface chemistry of cells. We have previously shown that high-resolution 1H NMR methods can identify tumor cells with the capacity to metastasize, and we now report that the long T2 relaxation value (500-800 ms) observed in metastatic rat mammary adenocarcinoma cells is removed by treatment with fucosidase. Two-dimensional scalar-correlated NMR (COSY) spectra of fucosidase-treated cells show that a cross peak, consistent with scalar coupling between the methyl and methine groups on fucose and usually associated with malignancy and metastatic ability, is absent. Metastases were observed in only two out of ten rats injected subcutaneously with enzyme-treated cells compared to eight out of ten with untreated cells. NMR studies on isolated cellular lipids identified the long T2 relaxation value only in the ganglioside fraction. This fraction accounts for 51% of the total 14C-labelled fucose incorporated into the cells. We propose that fucogangliosides are an indicator of metastatic potential in rats. The observation that a cell surface metastasis marker has an NMR signal with a characteristically long relaxation value has important consequences for the future use of magnetic resonance imaging and spectroscopy in the cancer clinic.