W670–W677 Nucleic Acids Research, 2009, Vol. 37, Web Server issue doi:10.1093/nar/gkp280 Published online 30 April 2009 GeNMR: a web server for rapid NMR-based protein structure determination Mark Berjanskii1, Peter Tang 1 , Jack Liang 1 , Joseph A. Cruz1, Jianjun Zhou 1 , You Zhou1, Edward Bassett1, Cam MacDonell1, Paul Lu1, Guohui Lin1 and David S. Wishart1,2,3,* 1Department of Computing Science, 2Department of Biological Sciences, University of Alberta and 3National Research Council, National Institute for Nanotechnology (NINT), Edmonton, AB, Canada T6G 2E8 Received February 9, 2009; Revised April 2, 2009; Accepted April 14, 2009 ABSTRACT GeNMR (GEnerate NMR structures) is a web server for rapidly generating accurate 3D protein struc- tures using sequence data, NOE-based dis- tance restraints and/or NMR chemical shifts as input. GeNMR accepts distance restraints in XPLOR or CYANA format as well as chemical shift files in either SHIFTY or BMRB formats. The web server produces an ensemble of PDB coordinates for the protein within 15–25 min, depending on model complexity and completeness of experimen- tal restraints. GeNMR uses a pipeline of several pre-existing programs and servers to calculate the actual protein structure. In particular, GeNMR com- bines genetic algorithms for structure optimization along with homology modeling, chemical shift threading, torsion angle and distance predictions from chemical shifts/NOEs as well as ROSETTA- based structure generation and simulated annealing with XPLOR-NIH to generate and/or refine protein coordinates. GeNMR greatly simplifies the task of protein structure determination as users do not have to install or become familiar with complex stand-alone programs or obscure format conver- sion utilities. Tests conducted on a sample of 90 proteins from the BioMagResBank indicate that GeNMR produces high-quality models for all protein queries, regardless of the type of NMR input data. GeNMR was developed to facilitate rapid, user- friendly structure determination of protein struc- tures via NMR spectroscopy. GeNMR is accessible at http://www.genmr.ca. INTRODUCTION Nuclear magnetic resonance (NMR) spectroscopy, along with X-ray crystallography, is one of only two methods that can be used to determine the 3D structures of proteins to atomic resolution. To date, nearly 8000 peptide and protein structures have been determined by NMR and deposited into the PDB (1). The standard route to deter- mine protein structures by NMR involves three basic steps: (i) determining the chemical shift assignments of the target protein; (ii) measuring the inter- and intra- residue 1H NOEs (nuclear Overhauser enhancements) to generate distance constraints; and (iii) using the NOE- derived constraints to perform simulated annealing or dis- tance geometry to calculate the 3D structure of the protein (2). The last step in this process is very computationally demanding and requires very specialized software and sig- niﬁcant computational resources. Over the past 20 years, a number of stand-alone programs have been speciﬁcally developed to facilitate these calculations including, DYANA (3), CYANA (4), XPLOR-NIH (5), CNS (6) and ARIA (7). All of these programs are excellent at what they do, and all have been extensively tested. However, they are also somewhat unwieldy, platform- speciﬁc software packages that are diﬃcult to learn or use. Furthermore, these programs work almost exclusively with NOE data and most of them do not take advantage of chemical shift information in their structure reﬁnement process. Likewise, they do not incorporate a number of widely used structural informatics techniques such as threading, fragment-based assembly or homology model- ing to accelerate the structure determination process. Consequently, these programs often require many CPU hours of dedicated calculation and reﬁnement to complete their tasks. *To whom correspondence should be addressed. Tel: +780 492 0383; Fax: +780 492 5305; Email: david.wishart@ualberta.ca 2009 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.