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.

[1]  S. Grzesiek,et al.  NMRPipe: A multidimensional spectral processing system based on UNIX pipes , 1995, Journal of biomolecular NMR.

[2]  J. Duus,et al.  Integration of spin-state-selective excitation into 2D NMR correlation experiments with the heteronuclear ZQ/2Q pi rotations for 1JXH- resolved E.COSY-type measurements of heteronuclear coupling constants in proteins. , 1997, Journal of biomolecular NMR.

[3]  C. Jaroniec,et al.  3D TEDOR NMR experiments for the simultaneous measurement of multiple carbon-nitrogen distances in uniformly (13)C,(15)N-labeled solids. , 2002, Journal of the American Chemical Society.

[4]  C. Jaroniec,et al.  Intermolecular alignment in Y145Stop human prion protein amyloid fibrils probed by solid-state NMR spectroscopy. , 2011, Journal of the American Chemical Society.

[5]  Guido Van Rossum,et al.  Python Tutorial , 1999 .

[6]  C. Jaroniec,et al.  Conformational flexibility of Y145Stop human prion protein amyloid fibrils probed by solid-state nuclear magnetic resonance spectroscopy. , 2010, Journal of the American Chemical Society.

[7]  Timothy Short,et al.  A covariance NMR toolbox for MATLAB and OCTAVE. , 2011, Journal of magnetic resonance.

[8]  Kurt Wüthrich,et al.  NMR studies of structure and function of biological macromolecules (Nobel Lecture)* , 2003, Journal of biomolecular NMR.

[9]  R. Brüschweiler,et al.  Covariance nuclear magnetic resonance spectroscopy. , 2004, The Journal of chemical physics.

[10]  Jay Vyas,et al.  CONNJUR spectrum translator: an open source application for reformatting NMR spectral data , 2011, Journal of biomolecular NMR.

[11]  C. Jaroniec,et al.  Amphiphilic self-assembly of an n-type nanotube. , 2010, Angewandte Chemie.

[12]  C. Jaroniec,et al.  Paramagnetic ions enable tuning of nuclear relaxation rates and provide long-range structural restraints in solid-state NMR of proteins. , 2009, Journal of the American Chemical Society.

[13]  Jacco D. van Beek,et al.  matNMR: A flexible toolbox for processing, analyzing and visualizing magnetic resonance data in Matlab® , 2007 .

[14]  Wyndham B Blanton,et al.  BlochLib: a fast NMR C++ tool kit. , 2003, Journal of magnetic resonance.

[15]  C. Jaroniec,et al.  Evaluation of the influence of intermolecular electron-nucleus couplings and intrinsic metal binding sites on the measurement of 15N longitudinal paramagnetic relaxation enhancements in proteins by solid-state NMR , 2011, Journal of biomolecular NMR.

[16]  I. Bertini,et al.  Transverse-dephasing optimized homonuclear j-decoupling in solid-state NMR spectroscopy of uniformly 13C-labeled proteins. , 2009, Journal of the American Chemical Society.

[17]  Mikhail Veshtort,et al.  SPINEVOLUTION: a powerful tool for the simulation of solid and liquid state NMR experiments. , 2006, Journal of magnetic resonance.

[18]  Dmitri I. Svergun,et al.  WeNMR: Structural Biology on the Grid , 2011, Journal of Grid Computing.

[19]  M Bak,et al.  SIMPSON: a general simulation program for solid-state NMR spectroscopy. , 2000, Journal of magnetic resonance.

[20]  M. Uesugi,et al.  [Discovering high-affinity ligands for proteins: SAR by NMR]. , 2007, Tanpakushitsu kakusan koso. Protein, nucleic acid, enzyme.

[21]  Marl A Delsuc,et al.  Spectral Representation of 2D NMR Spectra by Hypercomplex Numbers , 1988 .

[22]  P. Lauterbur.  All Science Is Interdisciplinary—From Magnetic Moments to Molecules to Men (Nobel Lecture) , 2005 .

[23]  Pearu Peterson,et al.  F2PY: a tool for connecting Fortran and Python programs , 2009, Int. J. Comput. Sci. Eng..

[24]  D. States,et al.  A two-dimensional nuclear overhauser experiment with pure absorption phase in four quadrants☆ , 1982 .

[25]  C. Jaroniec,et al.  Determination of methyl 13C-15N dipolar couplings in peptides and proteins by three-dimensional and four-dimensional magic-angle spinning solid-state NMR spectroscopy. , 2008, The Journal of chemical physics.

[26]  Wayne Boucher,et al.  The CCPN data model for NMR spectroscopy: Development of a software pipeline , 2005, Proteins.

[27]  John D. Hunter,et al.  Matplotlib: A 2D Graphics Environment , 2007, Computing in Science & Engineering.

[28]  Harald Schwalbe,et al.  Perspectives on NMR in drug discovery: a technique comes of age , 2008, Nature Reviews Drug Discovery.

[29]  Travis E. Oliphant,et al.  Python for Scientific Computing , 2007, Computing in Science & Engineering.

[30]  J. Lindon,et al.  'Metabonomics': understanding the metabolic responses of living systems to pathophysiological stimuli via multivariate statistical analysis of biological NMR spectroscopic data. , 1999, Xenobiotica; the fate of foreign compounds in biological systems.

[31]  M. Norman,et al.  yt: A MULTI-CODE ANALYSIS TOOLKIT FOR ASTROPHYSICAL SIMULATION DATA , 2010, 1011.3514.

[32]  J. Markley,et al.  rNMR: open source software for identifying and quantifying metabolites in NMR spectra , 2009, Magnetic resonance in chemistry : MRC.

[33]  D. Marquardt.  An Algorithm for Least-Squares Estimation of Nonlinear Parameters , 1963 .

[34]  Alan S. Stern,et al.  NMR Data Processing , 1996 .

[35]  Brian E. Granger,et al.  IPython: A System for Interactive Scientific Computing , 2007, Computing in Science & Engineering.

[36]  C. Jaroniec,et al.  13C and 15N chemical shift assignments and secondary structure of the B3 immunoglobulin-binding domain of streptococcal protein G by magic-angle spinning solid-state NMR spectroscopy , 2007, Biomolecular NMR assignments.

[37]  David M. Beazley,et al.  Automated scientific software scripting with SWIG , 2003, Future Gener. Comput. Syst..

[38]  Bartek Wilczynski,et al.  Biopython: freely available Python tools for computational molecular biology and bioinformatics , 2009, Bioinform..

[39]  C. Jaroniec,et al.  Molecular conformation and dynamics of the Y145Stop variant of human prion protein in amyloid fibrils , 2008, Proceedings of the National Academy of Sciences.

[40]  Kiyonori Takegoshi,et al.  13C–1H dipolar-assisted rotational resonance in magic-angle spinning NMR , 2001 .

[41]  T. Malliavin,et al.  Gifa V. 4: A complete package for NMR data set processing , 1996, Journal of biomolecular NMR.

[42]  Jonathan J. Helmus,et al.  Rapid acquisition of multidimensional solid-state NMR spectra of proteins facilitated by covalently bound paramagnetic tags. , 2010, Journal of the American Chemical Society.

[43]  Stefan Behnel,et al.  Cython: The Best of Both Worlds , 2011, Computing in Science & Engineering.

[44]  Tim J. Stevens,et al.  A software framework for analysing solid-state MAS NMR data , 2011, Journal of biomolecular NMR.

[45]  H. Scheraga,et al.  Phase-sensitive spectral analysis by maximum entropy extrapolation , 1986 .

[46]  Skipper Seabold,et al.  Statsmodels: Econometric and Statistical Modeling with Python , 2010, SciPy.

[47]  M. Baldus.  Correlation experiments for assignment and structure elucidation of immobilized polypeptides under magic angle spinning , 2002 .

[48]  Eric Jones,et al.  SciPy: Open Source Scientific Tools for Python , 2001 .

[49]  Ludwig,et al.  NMRLAB-Advanced NMR data processing in matlab , 2000, Journal of magnetic resonance.

[50]  R. Keller,et al.  The Computer Aided Resonance Assignment Tutorial , 2004 .

[51]  B. Meier,et al.  Computer Simulations in Magnetic Resonance. An Object-Oriented Programming Approach , 1994 .

[52]  C. Schwieters,et al.  Protein fold determined by paramagnetic magic-angle spinning solid-state NMR spectroscopy , 2012, Nature chemistry.

[53]  Gaël Varoquaux,et al.  Scikit-learn: Machine Learning in Python , 2011, J. Mach. Learn. Res..

[54]  Satrajit S. Ghosh,et al.  Nipype: A Flexible, Lightweight and Extensible Neuroimaging Data Processing Framework in Python , 2011, Front. Neuroinform..