Homology modeling aims to build three-dimensional protein structure models using experimentally determined structures of related family members as templates. SWISS-MODEL workspace is an integrated Web-based modeling expert system. For a given target protein, a library of experimental protein structures is searched to identify suitable templates. On the basis of a sequence alignment between the target protein and the template structure, a three-dimensional model for the target protein is generated. Model quality assessment tools are used to estimate the reliability of the resulting models. Homology modeling is currently the most accurate computational method to generate reliable structural models and is routinely used in many biological applications. Typically, the computational effort for a modeling project is less than 2 h. However, this does not include the time required for visualization and interpretation of the model, which may vary depending on personal experience working with protein structures.

The allotetraploid plant Nicotiana tabacum (common tobacco) is a major crop species and a model organism, for which only very fragmented genomic sequences are currently available. Here we report high-quality draft genomes for three main tobacco varieties. These genomes show both the low divergence of tobacco from its ancestors and microsynteny with other Solanaceae species. We identify over 90,000 gene models and determine the ancestral origin of tobacco mosaic virus and potyvirus disease resistance in tobacco. We anticipate that the draft genomes will strengthen the use of N. tabacum as a versatile model organism for functional genomics and biotechnology applications.

BackgroundNicotiana sylvestris and Nicotiana tomentosiformis are members of the Solanaceae family that includes tomato, potato, eggplant and pepper. These two Nicotiana species originate from South America and exhibit different alkaloid and diterpenoid production. N. sylvestris is cultivated largely as an ornamental plant and it has been used as a diploid model system for studies of terpenoid production, plastid engineering, and resistance to biotic and abiotic stress. N. sylvestris and N. tomentosiformis are considered to be modern descendants of the maternal and paternal donors that formed Nicotiana tabacum about 200,000 years ago through interspecific hybridization. Here we report the first genome-wide analysis of these two Nicotiana species.ResultsDraft genomes of N. sylvestris and N. tomentosiformis were assembled to 82.9% and 71.6% of their expected size respectively, with N50 sizes of about 80 kb. The repeat content was 72-75%, with a higher proportion of retrotransposons and copia-like long terminal repeats in N. tomentosiformis. The transcriptome assemblies showed that 44,000-53,000 transcripts were expressed in the roots, leaves or flowers. The key genes involved in terpenoid metabolism, alkaloid metabolism and heavy metal transport showed differential expression in the leaves, roots and flowers of N. sylvestris and N. tomentosiformis.ConclusionsThe reference genomes of N. sylvestris and N. tomentosiformis represent a significant contribution to the SOL100 initiative because, as members of the Nicotiana genus of Solanaceae, they strengthen the value of the already existing resources by providing additional comparative information, thereby helping to improve our understanding of plant metabolism and evolution.

This manuscript presents the assessment of the template-based modeling category of the seventh Critical Assessment of Techniques for Protein Structure Prediction (CASP7). The accuracy of predicted protein models for 108 target domains was assessed based on a detailed comparison between the experimental and predicted structures. The assessment was performed using numerical measures for backbone and structural alignment accuracy, and by scoring correctly modeled hydrogen bond interactions in the predictions. Based on these criteria, our statistical analysis identified a number of groups whose predictions were on average significantly more accurate. Furthermore, the predictions for six target proteins were evaluated for the accuracy of their modeled cofactor binding sites. We also assessed the ability of predictors to improve over the best available single template structure, which showed that the best groups produced models closer to the target structure than the best single template for a significant number of targets. In addition, we assessed the accuracy of the error estimates (local confidence values) assigned to predictions on a per residue basis. Finally, we discuss some general conclusions about the state of the art of template-based modeling methods and their usefulness for practical applications.