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Bioinformatics Advance Access originally published online on December 12, 2008
Bioinformatics 2009 25(4):474-481; doi:10.1093/bioinformatics/btn638
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© 2008 The Author(s)
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

NOEnet–Use of NOE networks for NMR resonance assignment of proteins with known 3D structure

Dirk Stratmann , Carine van Heijenoort * and Eric Guittet *

Laboratoire de Chimie et Biologie Structurales, ICSN-CNRS, Gif-sur-Yvette, France

*To whom correspondence should be addressed.


  Abstract

Motivation: A prerequisite for any protein study by NMR is the assignment of the resonances from the 15N–1H HSQC spectrum to their corresponding atoms of the protein backbone. Usually, this assignment is obtained by analyzing triple resonance NMR experiments. An alternative assignment strategy exploits the information given by an already available 3D structure of the same or a homologous protein. Up to now, the algorithms that have been developed around the structure-based assignment strategy have the important drawbacks that they cannot guarantee a high assignment accuracy near to 100%.

Results: We propose here a new program, called NOEnet, implementing an efficient complete search algorithm that ensures the correctness of the assignment results. NOEnet exploits the network character of unambiguous NOE constraints to realize an exhaustive search of all matching possibilities of the NOE network onto the structural one. NOEnet has been successfully tested on EIN, a large protein of 28 kDa, using only NOE data. The complete search of NOEnet finds all possible assignments compatible with experimental data that can be defined as an assignment ensemble. We show that multiple assignment possibilities of large NOE networks are restricted to a small spatial assignment range (SAR), so that assignment ensembles, obtained from accessible experimental data, are precise enough to be used for functional proteins studies, like protein–ligand interaction or protein dynamics studies. We believe that NOEnet can become a major tool for the structure-based backbone resonance assignment strategy in NMR.

Availability: The NOEnet program will be available under: http://www.icsn.cnrs-gif.fr/download/nmr

Contact: carine{at}icsn.cnrs-gif.fr; eric.guittet{at}icsn.cnrs-gif.fr

Supplementary Information: Supplementary data are available at Bioinformatics online.

Associate Editor: Anna Tramontano

Received on September 11, 2008; revised on November 18, 2008; accepted on December 9, 2008

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