We present the assessment of predictions for Template-Free Modeling in CASP10 and a report on the first ROLL experiment wherein predictions are collected year round for review at the regular CASP season. Models were first clustered so that duplicated or very similar ones were grouped together and represented by one model in the cluster. The representatives were then compared with targets using GDT_TS, QCS, and three additional superposition-independent score functions newly developed for CASP10. For each target, the top 15 representatives by each score were pooled to form the Top15Union set. All models in this set were visually inspected by four of us independently using the new plugin, EvalScore, which we developed with the UCSF Chimera group. The best models were selected for each target after extensive debate among the four examiners. Groups were ranked by the number of targets (hits) for which a group's model was selected as one of the best models. The Keasar group had most hits in both categories, with four of 19 FM and eight of 36 ROLL targets. The most successful prediction servers were QUARK from Zhang's group for FM category with three hits and Zhang-server for the ROLL category with seven hits. As observed in CASP9, many successful groups were not true "template-free" modelers but used remote templates and/or server models to obtain their winning models. The results of the first ROLL experiment were broadly similar to those of the CASP10 FM exercise.
Background There is a considerable literature on the source of the thermostability of proteins from thermophilic organisms. Understanding the mechanisms for this thermostability would provide insights into proteins generally and permit the design of synthetic hyperstable biocatalysts.Results We have systematically tested a large number of sequence and structure derived quantities for their ability to discriminate thermostable proteins from their non-thermostable orthologs using sets of mesophile-thermophile ortholog pairs. Most of the quantities tested correspond to properties previously reported to be associated with thermostability. Many of the structure related properties were derived from the Delaunay tessellation of protein structures.Conclusions Carefully selected sequence based indices discriminate better than purely structure based indices. Combined sequence and structure based indices improve performance somewhat further. Based on our analysis, the strongest contributors to thermostability are an increase in ion pairs on the protein surface and a more strongly hydrophobic interior.
For the 10th experiment on Critical Assessment of the techniques of protein Structure Prediction (CASP) the prediction target proteins were broken into independent evaluation units (EUs), which were then classified into template-based modeling (TBM) or free modeling (FM) categories. We describe here how the EUs were defined and classified, what issues arose in the process, and how we resolved them. Evaluation units are frequently not the whole target proteins but the constituting structural domains. However, the assessors from CASP7 on combined more than one domain into one evaluation unit for some targets, which implied that the assessment also included evaluation of the prediction of the relative position and orientation of these domains. In CASP10, we followed and expanded this notion by defining multi-domain evaluation units for a number of targets. These included three EUs, each made of two domains of familiar fold but arranged in a novel manner and for which the focus of evaluation was the inter-domain arrangement. An EU was classified to the TBM category if a template could be found by sequence similarity searches and to FM if a structural template could not be found by structural similarity searches. The EUs that did not fall cleanly in either of these cases were classified case-by-case, often including consideration of the overall quality and characteristics of the predictions.
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