Nna1 is a recently described gene product that has sequence similarity with metallocarboxypeptidases. In the present study, five additional Nna1-like genes were identified in the mouse genome and named cytosolic carboxypeptidase (CCP) 2 through 6. Modeling suggests that the carboxypeptidase domain folds into a structure that resembles metallocarboxypeptidases of the M14 family, with all necessary residues for catalytic activity and broad substrate specificity. All CCPs are abundant in testis and also expressed in brain, pituitary, eye, and other mouse tissues. In brain, Nna1/CCP1, CCP5, and CCP6 are broadly distributed, whereas CCP2 and 3 exhibit restricted patterns of expression. Nna1/CCP1, CCP2, CCP5, and CCP6 were found to exhibit a cytosolic distribution, with a slight accumulation of CCP5 in the nucleus. Based on the above results, we hypothesized that Nna1/CCP1 and CCP2-6 function in the processing of cytosolic proteins such as alpha-tubulin, which is known to be modified by the removal of a C-terminal tyrosine. Analysis of the forms of alpha tubulin in the olfactory bulb of mice lacking Nna1/CCP1 showed the absence of the detyrosinylated form in the mitral cells. Taken together, these results are consistent with a role for Nna1/CCP1 and the related CCPs in the processing of tubulin.

Nna1 has some sequence similarity to metallocarboxypeptidases, but the biochemical characterization of Nna1 has not previously been reported. In this work we performed a detailed genomic scan and found >100 Nna1 homologues in bacteria, Protista, and Animalia, including several paralogs in most eukaryotic species. Phylogenetic analysis of the Nna1-like sequences demonstrates a major divergence between Nna1-like peptidases and the previously known metallocarboxypeptidases subfamilies: M14A, M14B, and M14C. Conformational modeling of representative Nna1-like proteins from a variety of species indicates an unusually open active site, a property that might facilitate its action on a wide variety of peptide and protein substrates. To test this, we expressed a recombinant form of one of the Nna1-like peptidases from Caenorhabditis elegans and demonstrated that this protein is a fully functional metallocarboxypeptidase that cleaves a range of C-terminal amino acids from synthetic peptides. The enzymatic activity is activated by ATP/ADP and salt-inactivated, and is preferentially inhibited by Z-Glu-Tyr dipeptide, which is without precedent in metallocarboxypeptidases and resembles tubulin carboxypeptidase functioning; this hypothesis is strongly reinforced by the results depicted in Kalinina et al. published as accompanying paper in this journal. Our findings demonstrate that the M14 family of metallocarboxypeptidases is more complex and diverse than expected, and that Nna1-like peptidases are functional variants of such enzymes, representing a novel subfamily (we propose the name M14D) that contributes substantially to such diversity.

QCloud is a cloud-based system to support proteomics laboratories in daily quality assessment using a userfriendly interface, easy setup, and automated data processing. Since its release, QCloud has facilitated automated quality control for proteomics experiments in many laboratories. QCloud provides a quick and effortless evaluation of instrument performance that helps to overcome many analytical challenges derived from clinical and translational research. Here we present an improved version of the system, QCloud2. This new version includes enhancements in the scalability and reproducibility of the quality-control pipelines, and it features an improved front end for data visualization, user management, and chart annotation. The QCloud2 system also includes programmatic access and a standalone local version.

Multitasking or moonlighting is the capability of some proteins to execute two or more biochemical functions. Usually, moonlighting proteins are experimentally revealed by serendipity. For this reason, it would be helpful that Bioinformatics could predict this multifunctionality, especially because of the large amounts of sequences from genome projects. In the present work, we analyze and describe several approaches that use sequences, structures, interactomics, and current bioinformatics algorithms and programs to try to overcome this problem. Among these approaches are (a) remote homology searches using Psi-Blast, (b) detection of functional motifs and domains, (c) analysis of data from protein–protein interaction databases (PPIs), (d) match the query protein sequence to 3D databases (i.e., algorithms as PISITE), and (e) mutation correlation analysis between amino acids by algorithms as MISTIC. Programs designed to identify functional motif/domains detect mainly the canonical function but usually fail in the detection of the moonlighting one, Pfam and ProDom being the best methods. Remote homology search by Psi-Blast combined with data from interactomics databases (PPIs) has the best performance. Structural information and mutation correlation analysis can help us to map the functional sites. Mutation correlation analysis can only be used in very specific situations – it requires the existence of multialigned family protein sequences – but can suggest how the evolutionary process of second function acquisition took place. The multitasking protein database MultitaskProtDB (), previously published by our group, has been used as a benchmark for the all of the analyses.

A structural classification of loops has been obtained from a set of 141 protein structures classified as kinases. A total of 1813 loops was classified into 133 subclasses (9 betabeta(links), 15 betabeta(hairpins), 31 alpha-alpha, 46 alpha-beta and 32 beta-alpha). Functional information and specific features relating subclasses and function were included in the classification. Functional loops such as the P-loop (shared by different folds) or the Gly-rich-loop, among others, were classified into structural motifs. As a result, a common mechanism of catalysis and substrate binding was proved for most kinases. Additionally, the multiple-alignment of loop sequences made within each subclass was shown to be useful for comparative modeling of kinase loops. The classification is summarized in a kinase loop database located at http://sbi.imim.es/archki.