7 research outputs found

    Comparative 3-D Modeling of tmRNA

    Get PDF
    BACKGROUND: Trans-translation releases stalled ribosomes from truncated mRNAs and tags defective proteins for proteolytic degradation using transfer-messenger RNA (tmRNA). This small stable RNA represents a hybrid of tRNA- and mRNA-like domains connected by a variable number of pseudoknots. Comparative sequence analysis of tmRNAs found in bacteria, plastids, and mitochondria provides considerable insights into their secondary structures. Progress toward understanding the molecular mechanism of template switching, which constitutes an essential step in trans-translation, is hampered by our limited knowledge about the three-dimensional folding of tmRNA. RESULTS: To facilitate experimental testing of the molecular intricacies of trans-translation, which often require appropriately modified tmRNA derivatives, we developed a procedure for building three-dimensional models of tmRNA. Using comparative sequence analysis, phylogenetically-supported 2-D structures were obtained to serve as input for the program ERNA-3D. Motifs containing loops and turns were extracted from the known structures of other RNAs and used to improve the tmRNA models. Biologically feasible 3-D models for the entire tmRNA molecule could be obtained. The models were characterized by a functionally significant close proximity between the tRNA-like domain and the resume codon. Potential conformational changes which might lead to a more open structure of tmRNA upon binding to the ribosome are discussed. The method, described in detail for the tmRNAs of Escherichia coli, Bacillus anthracis, and Caulobacter crescentus, is applicable to every tmRNA. CONCLUSION: Improved molecular models of biological significance were obtained. These models will guide in the design of experiments and provide a better understanding of trans-translation. The comparative procedure described here for tmRNA is easily adopted for the modeling the members of other RNA families

    A biological sequence comparison algorithm using quantum computers

    Full text link
    Genetic information is encoded in a linear sequence of nucleotides, represented by letters ranging from thousands to billions. Mutations refer to changes in the DNA or RNA nucleotide sequence. Thus, mutation detection is vital in all areas of biology and medicine. Careful monitoring of virulence-enhancing mutations is essential. However, an enormous amount of classical computing power is required to analyze genetic sequences of this size. Inspired by human perception of vision and pixel representation of images on quantum computers, we leverage these techniques to implement a pairwise sequence analysis. The methodology has a potential advantage over classical approaches and can be further applied to identify mutations and other modifications in genetic sequences. We present a method to display and analyze the similarity between two genome sequences on a quantum computer where a similarity score is calculated to determine the similarity between nucleotides.Comment: 14 pages, 8 figures, 3 tables New version: typo in figure 7 New version because of a missing information in affiliations in footer, page

    The tmRDB and SRPDB resources

    Get PDF
    Maintained at the University of Texas Health Science Center at Tyler, Texas, the tmRNA database (tmRDB) is accessible at the URL with mirror sites located at Auburn University, Auburn, Alabama () and the Royal Veterinary and Agricultural University, Denmark (). The signal recognition particle database (SRPDB) at is mirrored at and the University of Goteborg (). The databases assist in investigations of the tmRNP (a ribonucleoprotein complex which liberates stalled bacterial ribosomes) and the SRP (a particle which recognizes signal sequences and directs secretory proteins to cell membranes). The curated tmRNA and SRP RNA alignments consider base pairs supported by comparative sequence analysis. Also shown are alignments of the tmRNA-associated proteins SmpB, ribosomal protein S1, alanyl-tRNA synthetase and Elongation Factor Tu, as well as the SRP proteins SRP9, SRP14, SRP19, SRP21, SRP54 (Ffh), SRP68, SRP72, cpSRP43, Flhf, SRP receptor (alpha) and SRP receptor (beta). All alignments can be easily examined using a new exploratory browser. The databases provide links to high-resolution structures and serve as depositories for structures obtained by molecular modeling

    tmRDB (tmRNA database)

    No full text
    Maintained at the University of Texas Health Science Center at Tyler, Texas, the tmRNA database (tmRDB) is accessible at the URL http://psyche.uthct.edu/dbs/tmRDB/tmRDB.html with mirror sites located at Auburn University, Auburn, Alabama (http://www.ag.auburn.edu/mirror/tmRDB/) and the Bioinformatics Research Center, Aarhus, Denmark (http://www.bioinf.au.dk/tmRDB/). The tmRDB collects and distributes information relevant to the study of tmRNA. In trans-translation, this molecule combines properties of tRNA and mRNA and binds several proteins to form the tmRNP. Related RNPs are likely to be functional in all bacteria. In this release of tmRDB, 186 new entries from 10 bacterial groups for a total of 274 tmRNA sequences have been added. Lists of the tmRNAs and the corresponding tmRNA-encoded tag-peptides are presented in alphabetical and phylogenetic order. The tmRNA sequences are aligned manually, assisted by computational tools, to determine base pairs supported by comparative sequence analysis. The tmRNA alignment, available in a variety of formats, provides the basis for the secondary and tertiary structure of each tmRNA molecule. Three-dimensional models of the tmRNAs and their associated proteins in PDB format give evidence for the recent progress that has been made in the understanding of tmRNP structure and function

    tmRDB (tmRNA database)

    No full text
    corecore