Ubiquitin (Ub) is a small protein that consists of 76 amino acids about 8.5 kDa. In ubiquitin conjugation, the ubiquitin is majorly conjugated on the lysine residue of protein by Ub-ligating (E3) enzymes. Three major enzymes participate in ubiquitin conjugation. They are – E1, E2 and E3 which are responsible for activating, conjugating and ligating ubiquitin, respectively. Ubiquitin conjugation in eukaryotes is an important mechanism of the proteasome-mediated degradation of a protein and regulating the activity of transcription factors. Motivated by the importance of ubiquitin conjugation in biological processes, this investigation develops a method, UbSite, which uses utilizes an efficient radial basis function (RBF) network to identify protein ubiquitin conjugation (ubiquitylation) sites. This work not only investigates the amino acid composition but also the structural characteristics, physicochemical properties, and evolutionary information of amino acids around ubiquitylation (Ub) sites. With reference to the pathway of ubiquitin conjugation, the substrate sites for E3 recognition, which are distant from ubiquitylation sites, are investigated. The measurement of F-score in a large window size (−20∼+20) revealed a statistically significant amino acid composition and position-specific scoring matrix (evolutionary information), which are mainly located distant from Ub sites. The distant information can be used effectively to differentiate Ub sites from non-Ub sites. As determined by five-fold cross-validation, the model that was trained using the combination of amino acid composition and evolutionary information performs best in identifying ubiquitin conjugation sites. The prediction sensitivity, specificity, and accuracy are 65.5%, 74.8%, and 74.5%, respectively. Although the amino acid sequences around the ubiquitin conjugation sites do not contain conserved motifs, the cross-validation result indicates that the integration of distant sequence features of Ub sites can improve predictive performance. Additionally, the independent test demonstrates that the proposed method can outperform other ubiquitylation prediction tools.

http://rbf.bioinfo.tw/~sachen/ttrbf.html

No abstract

Transporters are proteins that are involved in the movement of ions or molecules across biological membranes. Transporters are generally classified into channels/pores, electrochemical transporters, and active transporters. Discriminating the specific class of transporters and their subfamilies are essential tasks in computational biology for the advancement of structural and functional genomics. We have systematically analyzed the amino acid composition, residue pair preference and amino acid properties in six different families of transporters. Utilizing the information, we have developed a radial basis function (RBF) network method based on profiles obtained with position specific scoring matrices for discriminating transporters belonging to three different classes and six families. Our method showed a fivefold cross validation accuracy of 76%, 73%, and 69% for discriminating transporters and nontransporters, three different classes and six different families of transporters, respectively. Further, the method was tested with independent datasets, which showed similar level of accuracy. A web server has been developed for discriminating transporters based on three classes and six families, and it is available at http://rbf.bioinfo.tw/ approximately sachen/tcrbf.html. We suggest that our method could be effectively used to identify transporters and discriminating them into different classes and families.

A novel facultatively anaerobic, non-spore-forming, non-motile, catalase- and oxidase-positive, Gram-negative and rod-shaped bacterial strain, designated Y12T, was isolated from activated sludge of a wastewater bio-treatment facility. The strain was able to degrade about 90 % of added propanil (100 mg l−1) within 3 days of incubation. Growth occurred in the presence of 0–4.5 % (w/v) NaCl (optimum 0.5 %), at 10–40 °C (optimum 28 °C) and at pH 5.5–10.0 (optimum pH 7.0). Vesicular internal membrane structures and photoheterotrophic growth were not observed. The major respiratory quinone was ubiquinone-10 and the major cellular fatty acid was summed feature 8 (C18 : 1ω6c and/or C18 : 1ω7c). The genomic DNA G+C content of strain Y12T was 63.7 mol%. Phylogenetic analysis based on 16S rRNA gene sequence comparison revealed that strain Y12T was a member of the genus Catellibacterium, as it showed highest sequence similarities to Catellibacterium caeni DCA-1T (99.1 %) and <96.0 % similarities with other species of the genus Catellibacterium. Strain Y12T showed low DNA–DNA relatedness values with C. caeni DCA-1T. Based on phenotypic, genotypic and phylogenetic properties, strain Y12T represents a novel species of the genus Catellibacterium, for which the name Catellibacterium nanjingense sp. nov. is proposed. The type strain is Y12T ( = CCTCC AB 2010218T  = KCTC 23298T). An emended description of the genus Catellibacterium is also presented.