Assessment of template-free modeling in CASP10 and ROLL

By Chin-Hsien Tai, Hongjun Bai, Todd J. Taylor, Byungkook Lee. 2013

88 citations recorded by the source corpus.

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. Proteins 2014; 82(Suppl 2):57–83. © 2013 Wiley Periodicals, Inc.

Subfields: Molecular Biology, Spectroscopy

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Citations in the corpus

I-TASSER server: new development for protein structure and function predictions (2015, background): “The community-wide blind CASP experiments have shown that many automated servers, such as I-TASSER (1,2), Rosetta (3) and HHpred (4), can now generate structural models with accuracy comparable to the best human-expert guided modeling (5–7).”
Improved Contact Predictions Using the Recognition of Protein Like Contact Patterns (2014, background): “However, it is also clear that these methods are still not generally applicable to large-scale prediction of protein structures at high accuracy [5,6].”
CASP10 results compared to those of previous CASP experiments (2013, methodology): “…together with the fraction of residues that can be aligned to a single template, dominate model quality. performed at the domain level.18 ,20,21 We adopt the same practice here, but use a somewhat different domain separation procedure from that used by the assessors.22 We required that…”
Challenging the state-of-the-art in protein structure prediction: Highlights of experimental target structures for the 10th Critical Assessment of Techniques for Protein Structure Prediction Experiment CASP10 (2014, methodology): “…methods themselves, techniques for their assessment also have to evolve to better reflect the issues important for structural biology research.8, 9,73,74 The examples presented in this article highlight a series of reoccurring themes that appear to be challenging for current methods and might…”
Template-based and free modeling of I-TASSER and QUARK pipelines using predicted contact maps in CASP12 (2017, background): “5,13,14,17,18 One of the primary reasons for the difficulty of ab initio modeling in predicting large proteins with complicated topologies is the lack of precise long-range contact interaction information in the force field during protein structure assembly simulation.”
Evaluation of free modeling targets in CASP11 and ROLL (2016, background): “7,8 While the relative success of such methodology over the past decade suggests some advances in evaluating model quality and perhaps refining tertiary structure, it highlights the fact that the structure-folding problem remains unsolved.”
Sixty-five years of the long march in protein secondary structure prediction: the final stretch? (2016, background): “However, it remains challenging to predict three-dimensional structures from protein sequences reliably without using known structures as templates [8, 9].”
Assessment of ligand binding site predictions in CASP10 (2014, background): “The accuracy of predictions of three-dimensional structures is assessed as part of the template-based (TBM) and free-modeling (FM) categories,13–16 which includes the accuracy of binding site coordinates.17 ,18 Function prediction (FN) was introduced as a new category in CASP6.”