EZ-ASSIGN, a program for exhaustive NMR chemical shift assignments of large proteins from complete or incomplete triple-resonance data

Erik R.P. Zuiderweg, Ireena Bagai, Paolo Rossi, Eric B. Bertelsen

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

Abstract

For several of the proteins in the BioMagRes-Bank larger than 200 residues, 60% or fewer of the backbone resonances were assigned. But how reliable are those assignments? In contrast to complete assignments, where it is possible to check whether every triple-resonance Generalized Spin System (GSS) is assigned once and only once, with incomplete data one should compare all possible assignments and pick the best one. But that is not feasible: For example, for 200 residues and an incomplete set of 100 GSS, there are 1.6 × 10 260 possible assignments. In "EZ-ASSIGN", the protein sequence is divided in smaller unique fragments. Combined with intelligent search approaches, an exhaustive comparison of all possible assignments is now feasible using a laptop computer. The program was tested with experimental data of a 388-residue domain of the Hsp70 chaperone protein DnaK and for a 351-residue domain of a type III secretion ATPase. EZ-ASSIGN reproduced the hand assignments. It did slightly better than the computer program PINE (Bahrami et al. in PLoS Comput Biol 5(3):e1000307, 2009) and significantly outperformed SAGA (Crippen et al. in J Biomol NMR 46:281-298, 2010), AUTOASSIGN (Zimmerman et al. in J Mol Biol 269:592-610, 1997), and IBIS (Hyberts and Wagner in J Biomol NMR 26:335-344, 2003). Next, EZ-ASSIGN was used to investigate how well NMR data of decreasing completeness can be assigned. We found that the program could confidently assign fragments in very incomplete data. Here, EZ-ASSIGN dramatically outperformed all the other assignment programs tested.

Original languageEnglish (US)
Pages (from-to)179-191
Number of pages13
JournalJournal of biomolecular NMR
Volume57
Issue number2
DOIs
StatePublished - Oct 2013

Bibliographical note

Funding Information:
Acknowledgments E.R.P.Z. acknowledges support from National Institutes of Health grant NS059690 (to G.E. Gestwicki, P.I.). I.B. was supported by National Institutes of Health grant HL 102662 (to S. Ragdale, P.I.); P.R. was supported by National Institutes of Health grant AI094623 (to C. G. Kalodimos, P.I.). The authors acknowledge N.K. Khanra (Rutgers) for the type III ATPAse sample preparation and helpful discussions.

Keywords

  • Assignment verification
  • Computer assignment
  • Large protein NMR

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