Systematic analysis of the effect of multiple templates on the accuracy of comparative models of protein structure

<p>Abstract</p> <p>Background</p> <p>Although multiple templates are frequently used in comparative modeling, the effect of inclusion of additional template(s) on model accuracy (when compared to that of corresponding single-template based models) is not clear. To address this, we systematically analyze two-template models, the simplest case of multiple-template modeling. For an existing target-template pair (single-template modeling), a two-template based model of the target sequence is constructed by including an additional template without changing the original alignment to measure the effect of the second template on model accuracy.</p> <p>Results</p> <p>Even though in a large number of cases a two-template model showed higher accuracy than the corresponding one-template model, over the entire dataset only a marginal improvement was observed on average, as there were many cases where no change or the reverse change was observed. The increase in accuracy due to the structural complementarity of the templates increases at higher alignment accuracies. The combination of templates showing the highest potential for improvement is that where both templates share similar and low (less than 30%) sequence identity with the target, as well as low sequence identity with each other. The structural similarity between the templates also helps in identifying template combinations having a higher chance of resulting in an improved model.</p> <p>Conclusion</p> <p>Inclusion of additional template(s) does not necessarily improve model quality, but there are distinct combinations of the two templates, which can be selected <it>a priori</it>, that tend to show improvement in model quality over the single template model. The benefit derived from the structural complementarity is dependent on the accuracy of the modeling alignment. The study helps to explain the observation that a careful selection of templates together with an accurate target:template alignment are necessary to the benefit from using multiple templates in comparative modeling and provides guidelines to maximize the benefit from using multiple templates. This enables formulation of simple template selection rules to rank targets of a protein family in the context of structural genomics.</p

RNA sequencing of cancer reveals novel splicing alterations

Breast cancer transcriptome acquires a myriad of regulation changes, and splicing is critical for the cell to “tailor-make” specific functional transcripts. We systematically revealed splicing signatures of the three most common types of breast tumors using RNA sequencing: TNBC, non-TNBC and HER2-positive breast cancer. We discovered subtype specific differentially spliced genes and splice isoforms not previously recognized in human transcriptome. Further, we showed that exon skip and intron retention are predominant splice events in breast cancer. In addition, we found that differential expression of primary transcripts and promoter switching are significantly deregulated in breast cancer compared to normal breast. We validated the presence of novel hybrid isoforms of critical molecules like CDK4, LARP1, ADD3, and PHLPP2. Our study provides the first comprehensive portrait of transcriptional and splicing signatures specific to breast cancer sub-types, as well as previously unknown transcripts that prompt the need for complete annotation of tissue and disease specific transcriptome

Systematic analysis of the effect of multiple templates on the accuracy of comparative models of protein structure-4

�� -1 Å; or neutral: 1 Å > Δ RMSD > -1 Å. In all plots only models based on template combinations for which S1–S2 is less than 5% are included. The ratio between the number of Good and Bad STR models as a function of S3, the sequence identity between the templates. The good/bad ratio as a function of the RMSD between the two templates. The good/bad ratio as a function of the RMSD between the two templates; in these plots the additional restriction of S3 < 30% is imposed on all selected models with the aim of showing the complementarity between S3 and template RMSD selection.<p><b>Copyright information:</b></p><p>Taken from "Systematic analysis of the effect of multiple templates on the accuracy of comparative models of protein structure"</p><p>http://www.biomedcentral.com/1472-6807/8/31</p><p>BMC Structural Biology 2008;8():31-31.</p><p>Published online 16 Jul 2008</p><p>PMCID:PMC2483983.</p><p></p

Systematic analysis of the effect of multiple templates on the accuracy of comparative models of protein structure-5

S2 less than 5%, S1 < 30%, S3 < 30% and template RMSD between 3.5 and 5.5 Å are shown here. The dark bars correspond to Good models (see figure 6 legend), the empty bars to Bad models, the light bars to Neutral models. Fraction of Neutral (unchanged), Good and Bad models in the dataset before and after applying the template selection criteria described above.<p><b>Copyright information:</b></p><p>Taken from "Systematic analysis of the effect of multiple templates on the accuracy of comparative models of protein structure"</p><p>http://www.biomedcentral.com/1472-6807/8/31</p><p>BMC Structural Biology 2008;8():31-31.</p><p>Published online 16 Jul 2008</p><p>PMCID:PMC2483983.</p><p></p

Systematic analysis of the effect of multiple templates on the accuracy of comparative models of protein structure-6

of selected SEQ models (empty circles) is shown as a function of SEQ alignment accuracy. The curve for all SEQ models from Figure 4A (black circles) is shown for comparison. Difference between observed structural complementarity in SEQ models (ΔRMSD) and maximum achievable structural complementarity (ΔRMSD) as a function of SEQ alignment accuracy is shown for the selected models (empty circles) and for all models (black circles).<p><b>Copyright information:</b></p><p>Taken from "Systematic analysis of the effect of multiple templates on the accuracy of comparative models of protein structure"</p><p>http://www.biomedcentral.com/1472-6807/8/31</p><p>BMC Structural Biology 2008;8():31-31.</p><p>Published online 16 Jul 2008</p><p>PMCID:PMC2483983.</p><p></p

Systematic analysis of the effect of multiple templates on the accuracy of comparative models of protein structure-7

Es (top). The Target segment corresponding to the box has no structural information in absence of Template2. ALN stands for alignment type (SEQuence or STRucture). The total improvement of multiple template models over single template models is a combination of decreasing alignment errors and structural complementarity.<p><b>Copyright information:</b></p><p>Taken from "Systematic analysis of the effect of multiple templates on the accuracy of comparative models of protein structure"</p><p>http://www.biomedcentral.com/1472-6807/8/31</p><p>BMC Structural Biology 2008;8():31-31.</p><p>Published online 16 Jul 2008</p><p>PMCID:PMC2483983.</p><p></p

Systematic analysis of the effect of multiple templates on the accuracy of comparative models of protein structure-0

Es (top). The Target segment corresponding to the box has no structural information in absence of Template2. ALN stands for alignment type (SEQuence or STRucture). The total improvement of multiple template models over single template models is a combination of decreasing alignment errors and structural complementarity.<p><b>Copyright information:</b></p><p>Taken from "Systematic analysis of the effect of multiple templates on the accuracy of comparative models of protein structure"</p><p>http://www.biomedcentral.com/1472-6807/8/31</p><p>BMC Structural Biology 2008;8():31-31.</p><p>Published online 16 Jul 2008</p><p>PMCID:PMC2483983.</p><p></p

Comparative analysis of SARS-CoV- 2 neutralization titers reveals consistency between human and animal model serum and across assays

The evolution of severe acute respiratory syndrome coronavirus 2 (SARS-CoV- 2) requires ongoing monitoring to judge the ability of newly arising variants to escape the immune response. A surveillance system necessitates an understanding of differences in neutralization titers measured in different assays and using human and animal serum samples. We compared 18 datasets generated using human, hamster, and mouse serum and six different neutralization assays. Datasets using animal model serum samples showed higher titer magnitudes than datasets using human serum samples in this comparison. Fold change in neutralization of variants compared to ancestral SARS-CoV- 2, immunodominance patterns, and antigenic maps were similar among serum samples and assays. Most assays yielded consistent results, except for differences in fold change in cytopathic effect assays. Hamster serum samples were a consistent surrogate for human first-infection serum samples. These results inform the transition of surveillance of SARS-CoV-2 antigenic variation from dependence on human first-infection serum samples to the utilization of serum samples from animal models.</p