Back to Search Start Over

PONDEROSA, an automated 3D-NOESY peak picking program, enables automated protein structure determination.

Authors :
Lee, Woonghee
Kim, Jin Hae
Westler, William M.
Markley, John L.
Source :
Bioinformatics. Jun2011, Vol. 27 Issue 12, p1727-1728. 2p.
Publication Year :
2011

Abstract

Summary: PONDEROSA (Peak-picking Of Noe Data Enabled by Restriction of Shift Assignments) accepts input information consisting of a protein sequence, backbone and sidechain NMR resonance assignments, and 3D-NOESY (13C-edited and/or 15N-edited) spectra, and returns assignments of NOESY crosspeaks, distance and angle constraints, and a reliable NMR structure represented by a family of conformers. PONDEROSA incorporates and integrates external software packages (TALOS+, STRIDE and CYANA) to carry out different steps in the structure determination. PONDEROSA implements internal functions that identify and validate NOESY peak assignments and assess the quality of the calculated three-dimensional structure of the protein. The robustness of the analysis results from PONDEROSA's hierarchical processing steps that involve iterative interaction among the internal and external modules. PONDEROSA supports a variety of input formats: SPARKY assignment table (.shifts) and spectrum file formats (.ucsf), XEASY proton file format (.prot), and NMR-STAR format (.star). To demonstrate the utility of PONDEROSA, we used the package to determine 3D structures of two proteins: human ubiquitin and Escherichia coli iron-sulfur scaffold protein variant IscU(D39A). The automatically generated structural constraints and ensembles of conformers were as good as or better than those determined previously by much less automated means.Availability: The program, in the form of binary code along with tutorials and reference manuals, is available at http://ponderosa.nmrfam.wisc.edu/.Contact: whlee@nmrfam.wisc.edu; markley@nmrfam.wisc.eduSupplementary information: Supplementary data are available at Bioinformatics online. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
13674803
Volume :
27
Issue :
12
Database :
Academic Search Index
Journal :
Bioinformatics
Publication Type :
Academic Journal
Accession number :
61150959
Full Text :
https://doi.org/10.1093/bioinformatics/btr200