MraY (phospho-MurNAc-pentapeptide translocase) is an integral membrane enzyme that catalyzes an essential step of bacterial cell wall biosynthesis: the transfer of the peptidoglycan precursor phospho-MurNAc-pentapeptide to the lipid carrier undecaprenyl phosphate. MraY has long been considered a promising target for the development of antibiotics, but the lack of a structure has hindered mechanistic understanding of this critical enzyme and the enzyme superfamily in general. The superfamily includes enzymes involved in bacterial lipopolysaccharide/teichoic acid formation and eukaryotic N-linked glycosylation, modifications that are central in many biological processes. We present the crystal structure of MraY from Aquifex aeolicus (MraYAA) at 3.3 Å resolution, which allows us to visualize the overall architecture, locate Mg2+ within the active site, and provide a structural basis of catalysis for this class of enzyme.

For template‐based modeling in the CASP8 Critical Assessment of Techniques for Protein Structure Prediction, this work develops and applies six new full‐model metrics. They are designed to complement and add value to the traditional template‐based assessment by the global distance test (GDT) and related scores (based on multiple superpositions of Cα atoms between target structure and predictions labeled “Model 1”). The new metrics evaluate each predictor group on each target, using all atoms of their best model with above‐average GDT. Two metrics evaluate how “protein‐like” the predicted model is: the MolProbity score used for validating experimental structures, and a mainchain reality score using all‐atom steric clashes, bond length and angle outliers, and backbone dihedrals. Four other new metrics evaluate match of model to target for mainchain and sidechain hydrogen bonds, sidechain end positioning, and sidechain rotamers. Group‐average Z‐score across the six full‐model measures is averaged with group‐average GDT Z‐score to produce the overall ranking for full‐model, high‐accuracy performance. Separate assessments are reported for specific aspects of predictor‐group performance, such as robustness of approximately correct template or fold identification, and self‐scoring ability at identifying the best of their models. Fold identification is distinct from but correlated with group‐average GDT Z‐score if target difficulty is taken into account, whereas self‐scoring is done best by servers and is uncorrelated with GDT performance. Outstanding individual models on specific targets are identified and discussed. Predictor groups excelled at different aspects, highlighting the diversity of current methodologies. However, good full‐model scores correlate robustly with high Cα accuracy. Proteins 2009. © 2009 Wiley‐Liss, Inc.

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