Assessment of template-free modeling in CASP10 and ROLL

CASP10 和 ROLL 中无模板建模的评估

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Abstract

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.

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