ACLAME: A CLAssification of Mobile genetic Elements, update 2010

The ACLAME database is dedicated to the collection, analysis and classification of sequenced mobile genetic elements (MGEs, in particular phages and plasmids). In addition to providing information on the MGEs content, classifications are available at various levels of organization. At the gene/protein level, families group similar sequences that are expected to share the same function. Families of four or more proteins are manually assigned with a functional annotation using the GeneOntology and the locally developed ontology MeGO dedicated to MGEs. At the genome level, evolutionary cohesive modules group sets of protein families shared among MGEs. At the population level, networks display the reticulate evolutionary relationships among MGEs. To increase the coverage of the phage sequence space, ACLAME version 0.4 incorporates 760 high-quality predicted prophages selected from the Prophinder database. Most of the data can be downloaded from the freely accessible ACLAME web site (http://aclame.ulb.ac.be). The BLAST interface for querying the database has been extended and numerous tools for in-depth analysis of the results have been added

Tachyon search speeds up retrieval of similar sequences by several orders of magnitude

Summary: The usage of current sequence search tools becomes increasingly slower as databases of protein sequences continue to grow exponentially. Tachyon, a new algorithm that identifies closely related protein sequences ~200 times faster than standard BLAST, circumvents this limitation with a reduced database and oligopeptide matching heuristic

MINT, the molecular interaction database: 2009 update

MINT (http://mint.bio.uniroma2.it/mint) is a public repository for molecular interactions reported in peer-reviewed journals. Since its last report, MINT has grown considerably in size and evolved in scope to meet the requirements of its users. The main changes include a more precise definition of the curation policy and the development of an enhanced and user-friendly interface to facilitate the analysis of the ever-growing interaction dataset. MINT has adopted the PSI-MI standards for the annotation and for the representation of molecular interactions and is a member of the IMEx consortium

Verification of alternative splicing variants based on domain integrity, truncation length and intrinsic protein disorder

According to current estimations ∼95% of multi-exonic human protein-coding genes undergo alternative splicing (AS). However, for 4000 human proteins in PDB, only 14 human proteins have structures of at least two alternative isoforms. Surveying these structural isoforms revealed that the maximum insertion accommodated by an isoform of a fully ordered protein domain was 5 amino acids, other instances of domain changes involved intrinsic structural disorder. After collecting 505 minor isoforms of human proteins with evidence for their existence we analyzed their length, protein disorder and exposed hydrophobic surface. We found that strict rules govern the selection of alternative splice variants aimed to preserve the integrity of globular domains: alternative splice sites (i) tend to avoid globular domains or (ii) affect them only marginally or (iii) tend to coincide with a location where the exposed hydrophobic surface is minimal or (iv) the protein is disordered. We also observed an inverse correlation between the domain fraction lost and the full length of the minor isoform containing the domain, possibly indicating a buffering effect for the isoform protein counteracting the domain truncation effect. These observations provide the basis for a prediction method (currently under development) to predict the viability of splice variants

Reconstruction and analysis of genome-scale metabolic model of a photosynthetic bacterium

<p>Abstract</p> <p>Background</p> <p><it>Synechocystis </it>sp. PCC6803 is a cyanobacterium considered as a candidate photo-biological production platform - an attractive cell factory capable of using CO₂and light as carbon and energy source, respectively. In order to enable efficient use of metabolic potential of <it>Synechocystis </it>sp. PCC6803, it is of importance to develop tools for uncovering stoichiometric and regulatory principles in the <it>Synechocystis </it>metabolic network.</p> <p>Results</p> <p>We report the most comprehensive metabolic model of <it>Synechocystis </it>sp. PCC6803 available, <it>i</it>Syn669, which includes 882 reactions, associated with 669 genes, and 790 metabolites. The model includes a detailed biomass equation which encompasses elementary building blocks that are needed for cell growth, as well as a detailed stoichiometric representation of photosynthesis. We demonstrate applicability of <it>i</it>Syn669 for stoichiometric analysis by simulating three physiologically relevant growth conditions of <it>Synechocystis </it>sp. PCC6803, and through <it>in silico </it>metabolic engineering simulations that allowed identification of a set of gene knock-out candidates towards enhanced succinate production. Gene essentiality and hydrogen production potential have also been assessed. Furthermore, <it>i</it>Syn669 was used as a transcriptomic data integration scaffold and thereby we found metabolic hot-spots around which gene regulation is dominant during light-shifting growth regimes.</p> <p>Conclusions</p> <p><it>i</it>Syn669 provides a platform for facilitating the development of cyanobacteria as microbial cell factories.</p

Catalytic residues in hydrolases: analysis of methods designed for ligand-binding site prediction

The comparison of eight tools applicable to ligand-binding site prediction is presented. The methods examined cover three types of approaches: the geometrical (CASTp, PASS, Pocket-Finder), the physicochemical (Q-SiteFinder, FOD) and the knowledge-based (ConSurf, SuMo, WebFEATURE). The accuracy of predictions was measured in reference to the catalytic residues documented in the Catalytic Site Atlas. The test was performed on a set comprising selected chains of hydrolases. The results were analysed with regard to size, polarity, secondary structure, accessible solvent area of predicted sites as well as parameters commonly used in machine learning (F-measure, MCC). The relative accuracies of predictions are presented in the ROC space, allowing determination of the optimal methods by means of the ROC convex hull. Additionally the minimum expected cost analysis was performed. Both advantages and disadvantages of the eight methods are presented. Characterization of protein chains in respect to the level of difficulty in the active site prediction is introduced. The main reasons for failures are discussed. Overall, the best performance offers SuMo followed by FOD, while Pocket-Finder is the best method among the geometrical approaches