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      NMRFAM-SPARKY: enhanced software for biomolecular NMR spectroscopy

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      * , , *
      Bioinformatics
      Oxford University Press

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          Abstract

          Summary: SPARKY (Goddard and Kneller, SPARKY 3) remains the most popular software program for NMR data analysis, despite the fact that development of the package by its originators ceased in 2001. We have taken over the development of this package and describe NMRFAM-SPARKY, which implements new functions reflecting advances in the biomolecular NMR field. NMRFAM-SPARKY has been repackaged with current versions of Python and Tcl/Tk, which support new tools for NMR peak simulation and graphical assignment determination. These tools, along with chemical shift predictions from the PACSY database, greatly accelerate protein side chain assignments. NMRFAM-SPARKY supports automated data format interconversion for interfacing with a variety of web servers including, PECAN , PINE, TALOS-N, CS-Rosetta, SHIFTX2 and PONDEROSA-C/S.

          Availability and implementation: The software package, along with binary and source codes, if desired, can be downloaded freely from http://pine.nmrfam.wisc.edu/download_packages.html. Instruction manuals and video tutorials can be found at http://www.nmrfam.wisc.edu/nmrfam-sparky-distribution.htm.

          Contact: whlee@ 123456nmrfam.wisc.edu or markley@ 123456nmrfam.wisc.edu

          Supplementary information: Supplementary data are available at Bioinformatics online.

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          Most cited references13

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          Knowledge-based protein secondary structure assignment.

          We have developed an automatic algorithm STRIDE for protein secondary structure assignment from atomic coordinates based on the combined use of hydrogen bond energy and statistically derived backbone torsional angle information. Parameters of the pattern recognition procedure were optimized using designations provided by the crystallographers as a standard-of-truth. Comparison to the currently most widely used technique DSSP by Kabsch and Sander (Biopolymers 22:2577-2637, 1983) shows that STRIDE and DSSP assign secondary structural states in 58 and 31% of 226 protein chains in our data sample, respectively, in greater agreement with the specific residue-by-residue definitions provided by the discoverers of the structures while in 11% of the chains, the assignments are the same. STRIDE delineates every 11th helix and every 32nd strand more in accord with published assignments.
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            BioMagResBank

            The BioMagResBank (BMRB: www.bmrb.wisc.edu) is a repository for experimental and derived data gathered from nuclear magnetic resonance (NMR) spectroscopic studies of biological molecules. BMRB is a partner in the Worldwide Protein Data Bank (wwPDB). The BMRB archive consists of four main data depositories: (i) quantitative NMR spectral parameters for proteins, peptides, nucleic acids, carbohydrates and ligands or cofactors (assigned chemical shifts, coupling constants and peak lists) and derived data (relaxation parameters, residual dipolar couplings, hydrogen exchange rates, pKa values, etc.), (ii) databases for NMR restraints processed from original author depositions available from the Protein Data Bank, (iii) time-domain (raw) spectral data from NMR experiments used to assign spectral resonances and determine the structures of biological macromolecules and (iv) a database of one- and two-dimensional 1H and 13C one- and two-dimensional NMR spectra for over 250 metabolites. The BMRB website provides free access to all of these data. BMRB has tools for querying the archive and retrieving information and an ftp site (ftp.bmrb.wisc.edu) where data in the archive can be downloaded in bulk. Two BMRB mirror sites exist: one at the PDBj, Protein Research Institute, Osaka University, Osaka, Japan (bmrb.protein.osaka-u.ac.jp) and the other at CERM, University of Florence, Florence, Italy (bmrb.postgenomicnmr.net/). The site at Osaka also accepts and processes data depositions.
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              The PSIPRED protein structure prediction server.

              The PSIPRED protein structure prediction server allows users to submit a protein sequence, perform a prediction of their choice and receive the results of the prediction both textually via e-mail and graphically via the web. The user may select one of three prediction methods to apply to their sequence: PSIPRED, a highly accurate secondary structure prediction method; MEMSAT 2, a new version of a widely used transmembrane topology prediction method; or GenTHREADER, a sequence profile based fold recognition method. Freely available to non-commercial users at http://globin.bio.warwick.ac.uk/psipred/
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                Author and article information

                Journal
                Bioinformatics
                Bioinformatics
                bioinformatics
                bioinfo
                Bioinformatics
                Oxford University Press
                1367-4803
                1367-4811
                15 April 2015
                12 December 2014
                12 December 2014
                : 31
                : 8
                : 1325-1327
                Affiliations
                National Magnetics Resonance Facility at Madison, Biochemistry Department, University of Wisconsin-Madison, Madison, WI 53706, USA
                Author notes
                *To whom correspondence should be addressed.

                Associate Editor: Anna Tramontano

                Article
                btu830
                10.1093/bioinformatics/btu830
                4393527
                25505092
                1e980280-7ce3-4e82-82ab-bd7dbf9f050f
                © The Author 2014. Published by Oxford University Press.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com

                History
                : 22 October 2014
                : 22 October 2014
                : 08 December 2014
                Page count
                Pages: 3
                Categories
                Applications Notes
                Structural Bioinformatics

                Bioinformatics & Computational biology
                Bioinformatics & Computational biology

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