W676 Nucleic Acids Research, 2009, Vol. 37, Web Server issue user-supplied NOE data to create its own set of H-bonding constraints. Another limitation to GeNMR is that it cannot calcu- late the structures for protein complexes (protein–protein, protein–nucleic acid or protein–small molecule com- plexes). Because of the requirement for customized atom designations, the lack of readily available test sets as well as the need for somewhat more complex workﬂows and input data requirements, we decided not to support these kinds of queries or calculations at this time. Eﬀorts are underway to add this feature to the server and it is expected that protein–protein complex structure genera- tion will be supported by the summer of 2009. Support for generating other kinds of complexes (DNA, RNA or small molecule ligands) should be available shortly there- after. It is perhaps worth noting that of the 5698 non- redundant protein structures in the PDB that have been solved by NMR, 89.9% are monomeric. So despite this single-chain limitation, GeNMR is still be able to handle the vast majority of today’s NMR queries. As with any program or web server there is the usual caveat that ‘garbage in = garbage out’. In particular, GeNMR assumes that the sequence, chemical shifts and NOE ﬁles that are submitted are mostly error-free. Nevertheless, a number of data integrity checks (including formatting checks, sequence length checks and chemical shift referencing checks) are performed to prevent data from being misprocessed or misinterpreted and to provide direct user feedback. Additionally, GeNMR performs a ‘Structure Sanity Check’ that is appended to GeNMR’s structure/energy evaluation output. This utility should allow users to identify possible misassignment (shift or NOE) errors. We have also developed criteria to provide warnings and to highlight residues or sequence regions that may need manual checking. Given the nature of exper- imental data and the large number of manual measure- ments and data entry tasks typically required in NMR- based structure determination, we also realized it was important to have some built-in tolerance for data mea- surement errors. Tests indicate that GeNMR can tolerate a certain level of chemical shift misassignments and/or NOE misassignments ( 5%), although this tolerance will vary depending on the type of query as well as the type of error or the extent of the misassignment. CONCLUSIONS We believe GeNMR provides a new and greatly simpliﬁed approach to determining protein structures from NMR data. For most of the past 20 years, NOE-based structure determination has required that users to become familiar with relatively large and complex, stand-alone programs. Often the learning curve for these programs is steep and the need for training/re-training, as well the ongoing eﬀorts needed to install, maintain and upgrade the soft- ware (and hardware) are quite considerable. By develop- ing a web server to perform NMR-based structure determination, we believe we have greatly simpliﬁed the process. GeNMR’s intuitive interface and simple ﬁle input makes the system easy to use and easy to learn. Its web accessibility means that users are not constrained by plat- form compatibility issues or the availability of dedicated CPUs. Indeed structure calculations can be performed by anyone, essentially anytime or from anywhere. Furthermore, GeNMR’s use of parallelism and ‘molecular replacement’ concepts means that calculations that used to take hours or days are typically completed within minutes. Finally, by moving the system to a web server format, many of the onerous tasks of local software maintenance and local software/hardware upgrading have been elimi- nated. While GeNMR is not without some limitations, overall we believe its simplicity, speed and accessibility should make it a very useful addition to the current arse- nal of structure generation and reﬁnement tools available to biomolecular NMR spectroscopists. FUNDING Alberta Prion Research Institute, PrioNet; NSERC; Genome Alberta. Funding for open access charge: PrioNet. Conﬂict of interest statement. None declared. REFERENCES 1. Berman,H., Henrick,K., Nakamura,H. and Markley,J.L. (2007) The worldwide Protein Data Bank (wwPDB): ensuring a single, uniform archive of PDB data. Nucleic Acids Res., 35(Database issue), D301–D303. 2. Wuthrich,K. (1995) NMR - this other method for protein and nucleic acid structure determination. Acta Crystallogr. D, 51, 249–270. 3. Gu¨ ntert,P., Mumenthaler,C. and Wu¨ thrich,K. (1997) Torsion angle dynamics for NMR structure calculation with the new program DYANA. J. Mol. Biol., 273, 283–298. 4. Gu¨ ntert,P. (2004) Automated NMR structure calculation with CYANA. Methods Mol. Biol., 278, 353–378. 5. Schwieters,C.D., Kuszewski,J.J., Tjandra,N. and Clore,G.M. (2003) The Xplor-NIH NMR molecular structure determination package. J. Magn. Reson., 160, 65–73. 6. Bru¨ nger,A.T., Adams,P.D., Clore,G.M., DeLano,W.L., Gros,P., Grosse-Kunstleve,R.W., Jiang,J.S., Kuszewski,J., Nilges,M., Pannu,N.S. et al. (1998) Crystallography & NMR system: a new software suite for macromolecular structure determination. Acta Crystallogr. D Biol. Crystallogr., 54(Pt 5), 905–921. 7. Nilges,M., Macias,M.J., O’Donoghue,S.I. and Oschkinat,H. (1997) Automated NOESY interpretation with ambiguous distance restraints: the reﬁned NMR solution structure of the pleckstrin homology domain from beta-spectrin. J. Mol. Biol., 269, 408–422. 8. Cavalli,A., Salvatella,X., Dobson,C.M. and Vendruscolo,M. (2007) Protein structure determination from NMR chemical shifts. Proc. Natl Acad. Sci. USA, 104, 9615–9620. 9. Shen,Y., Lange,O., Delaglio,F., Rossi,P., Aramini,J.M., Liu,G., Eletsky,A., Wu,Y., Singarapu,K.K., Lemak,A. et al. (2008) Consistent blind protein structure generation from NMR chemical shift data. Proc. Natl Acad. Sci. USA, 105, 4685–4690. 10. Wishart,D.S., Arndt,D., Berjanskii,M., Tang,P., Zhou,J. and Lin,G. (2008) CS23D: a web server for rapid protein structure generation using NMR chemical shifts and sequence data. Nucleic Acids Res., 36(Web Server issue), W496–W502. 11. Wishart,D.S. and Sykes,B.D. (1994) The 13C chemical-shift index: a simple method for the identiﬁcation of protein secondary structure using 13C chemical-shift data. J. Biomol. NMR, 4, 171–180. 12. Berjanskii,M.V., Neal,S. and Wishart,D.S. (2006) PREDITOR: a web server for predicting protein torsion angle restraints. Nucleic Acids Res., 34(Web Server issue), W63–W69.