The dynamic NMR structure of the TψC-loop: Implications for the specificity of tRNA methylation

Letitia J. Yao, Thomas L. James, James T. Kealey, Daniel V. Santi, Uli Schmitz

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26 Scopus citations

Abstract

tRNA (m5U54)-methyltransferase (RUMT) catalyzes the S-adenosylmethionine-dependent methylation of uridine-54 in the TψC-loop of all transfer RNAs in E. coli to form the 54-ribosylthymine residue. However, in all tRNA structures, residue 54 is completely buried and the question arises as to how RUMT gains access to the methylation site. A 17-mer RNA hairpin consisting of nucleotides 49-65 of the Tψ-loop is a substrate for RUMT Homonuclear NMR methods in conjunction with restrained molecular dynamics (MD) methods were used to determine the solution structure of the 17-mer T-arm fragment. The loop of the hairpin exhibits enhanced flexibility which renders the conventional NMR average structure less useful compared to the more commonly found situation where a molecule exists in predominantly one major conformation. However, when resorting to softer refinement methods such as MD with time-averaged restraints, the conflicting restraints in the loop can be satisfied much better. The dynamic structure of the T-arm is represented as an ensemble of 10 time-clusters. In all of these, U54 is completely exposed. The flexibility of the Tψ-loop in solution in conjunction with extensive binding studies of RUMT with the TψC-loop and tRNA suggest that the specificity of the RUMT/ tRNA recognition is associated with tRNA tertiary structure elements. For the methylation, RUMT would simply have to break the tertiary interactions between the D- and T-loops, leading to a melting of the T-arm structure and making U54 available for methylation.

Original languageEnglish (US)
Pages (from-to)229-244
Number of pages16
JournalJournal of biomolecular NMR
Volume9
Issue number3
DOIs
StatePublished - 1997

Bibliographical note

Funding Information:
This research was supported by NIH Grant GM39247 to T.L.J., a UC Academic Senate Research Grant to U.S., and NRSA postdoctoral fellowship GM18337 from the National Institutes of Health to L.J.Y. We gratefully acknowledge the UCSF Computer Graphics laboratory supported by NIH Grant RR01081 and the use of the Pittsburgh Supercomputing Center as well as the Frederick Biomedical Supercomputing Center for project grants to T.L.J. (CHE880090P) and U.S. (162002), respectively.

Keywords

  • Dynamic NMR refinement
  • MD with time-averaged restraints
  • RNA/protein recognition
  • RUMT
  • TψC-loop

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