The zinc finger protein Ynr046w is plurifunctional and a component of the eRF1 methyltransferase in yeast.

UPR 9073 du CNRS, Institut de Biologie Physico-Chimique, 13 rue Pierre et Marie Curie, 75005 Paris, France.
Journal of Biological Chemistry (Impact Factor: 4.6). 12/2006; 281(47):36140-8. DOI: 10.1074/jbc.M608571200
Source: PubMed

ABSTRACT Protein release factor eRF1 in Saccharomyces cerevisiae, in complex with eRF3 and GTP, is methylated on a functionally crucial Gln residue by the S-adenosylmethionine-dependent methyltransferase Ydr140w. Here we show that eRF1 methylation, in addition to these previously characterized components, requires a 15-kDa zinc-binding protein, Ynr046w. Co-expression in Escherichia coli of Ynr046w and Ydr140w allows the latter to be recovered in soluble form rather than as inclusion bodies, and the two proteins co-purify on nickel-nitrilotriacetic acid chromatography when Ydr140w alone carries a His tag. The crystal structure of Ynr046w has been determined to 1.7 A resolution. It comprises a zinc-binding domain built from both the N- and C-terminal sequences and an inserted domain, absent from bacterial and archaeal orthologs of the protein, composed of three alpha-helices. The active methyltransferase is the heterodimer Ydr140w.Ynr046w, but when alone, both in solution and in crystals, Ynr046w appears to be a homodimer. The Ynr046w eRF1 methyltransferase subunit is shared by the tRNA methyltransferase Trm11p and probably by two other enzymes containing a Rossman fold.

  • [Show abstract] [Hide abstract]
    ABSTRACT: Inclusion of entropy is important and challenging for protein-protein binding prediction. Here, we present a statistical mechanics-based approach to empirically consider the effect of orientational entropy. Specifically, we globally sample the possible binding orientations based on a simple shape-complementarity scoring function using an FFT-type docking method. Then, for each generated orientation, we calculate the probability through the partition function of the ensemble of accessible states, which are assumed to be represented by the set of nearby binding modes. For each mode, the interaction energy is calculated using our ITScorePP scoring function that was developed in our laboratory based on principles of statistical mechanics. Using the above protocol, we present the results of our participation in Rounds 22-27 of the Critical Assessment of PRedicted Interactions (CAPRI) experiment for 10 targets (T46-T58). Additional experimental information, such as low-resolution small-angle X-ray scattering data, was used when available. In the prediction (or docking) experiments of the 10 target complexes, we achieved correct binding modes for six targets: one with high accuracy (T47), two with medium accuracy (T48 and T57), and three with acceptable accuracy (T49, T50, and T58). In the scoring experiments of seven target complexes, we obtained correct binding modes for six targets: one with high accuracy (T47), two with medium accuracy (T49 and T50), and three with acceptable accuracy (T46, T51, and T53). Proteins 2013; 81:2183-2191. © 2013 Wiley Periodicals, Inc.
    Proteins Structure Function and Bioinformatics 10/2013; 81(12). · 3.34 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: Bacterial translation termination is mediated by release factors RF1 and RF2, which recognize stop codons and catalyze hydrolysis of the peptidyl-tRNA ester bond. The catalytic mechanism has been debated. We proposed that the backbone amide NH group, rather than the side chain, of the glutamine of the universally conserved GGQ motif participates in catalysis by H-bonding to the tetrahedral transition-state intermediate and by product stabilization. This was supported by complete loss of RF1 catalytic activity when glutamine is replaced by proline, the only residue that lacks a backbone NH group. Here, we present the 3.4 Å crystal structure of the ribosome complex containing the RF2 Q253P mutant and find that its fold, including the GGP sequence, is virtually identical to that of wild-type RF2. This rules out proline-induced misfolding and further supports the proposal that catalytic activity requires interaction of the Gln-253 backbone amide with the 3' end of peptidyl-tRNA.
    Structure 06/2013; · 6.79 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: We present benchmark databases of Zn−ligand bond distances, bond angles, dipole moments, and bond dissociation energies for Zn-containing small molecules and Zn coordination compounds with H, CH3, C2H5, NH3, O, OH, H2O, F, Cl, S, and SCH3 ligands. The test set also includes clusters with Zn−Zn bonds. In addition, we calculated dipole moments and binding energies for Zn centers in coordination environments taken from zinc metalloenzyme X-ray structures, representing both structural and catalytic zinc centers. The benchmark values are based on relativistic-core coupled cluster calculations. These benchmark calculations are used to test the predictions of four density functionals, namely B3LYP and the more recently developed M05-2X, M06, and M06-2X levels of theory, and six semiempirical methods, including neglect of diatomic differential overlap (NDDO) calculations incorporating the new PM3 parameter set for Zn called ZnB, developed by Brothers and co-workers, and the recent PM6 parametrization of Stewart. We found that the best DFT method to reproduce dipole moments and dissociation energies of our Zn compound database is M05-2X, which is consistent with a previous study employing a much smaller and less diverse database and a much larger set of density functionals. Here we show that M05-2X geometries and single-point coupled cluster calculations with M05-2X geometries can also be used as benchmarks for larger compounds, where coupled cluster optimization is impractical, and in particular we use this strategy to extend the geometry, binding energy, and dipole moment databases to additional molecules, and we extend the tests involving crystal-site coordination compounds to two additional proteins. We find that the most predictive NDDO methods for our training set are PM3 and MNDO/d. Notably, we also find large errors in B3LYP for the coordination compounds based on experimental X-ray geometries.
    Journal of Chemical Theory and Computation 05/2009; 5(5). · 5.31 Impact Factor