Evaluation of free modeling targets in CASP11 and ROLL

By Lisa N. Kinch, Wenlin Li, Bohdan Monastyrskyy, Andriy Kryshtafovych, Nick V. Grishin. 2016

73 citations recorded by the source corpus.

We present an assessment of ‘template‐free modeling’ (FM) in CASP11and ROLL. Community‐wide server performance suggested the use of automated scores similar to previous CASPs would provide a good system of evaluating performance, even in the absence of comprehensive manual assessment. The CASP11 FM category included several outstanding examples, including successful prediction by the Baker group of a 256‐residue target (T0806‐D1) that lacked sequence similarity to any existing template. The top server model prediction by Zhang's Quark, which was apparently selected and refined by several manual groups, encompassed the entire fold of target T0837‐D1. Methods from the same two groups tended to dominate overall CASP11 FM and ROLL rankings. Comparison of top FM predictions with those from the previous CASP experiment revealed progress in the category, particularly reflected in high prediction accuracy for larger protein domains. FM prediction models for two cases were sufficient to provide functional insights that were otherwise not obtainable by traditional sequence analysis methods. Importantly, CASP11 abstracts revealed that alignment‐based contact prediction methods brought about much of the CASP11 progress, producing both of the functionally relevant models as well as several of the other outstanding structure predictions. These methodological advances enabled de novo modeling of much larger domain structures than was previously possible and allowed prediction of functional sites. Proteins 2016; 84(Suppl 1):51–66. © 2015 Wiley Periodicals, Inc.

Subfields: Materials Chemistry, Molecular Biology

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Citations in the corpus

Critical Assessment of Methods of Protein Structure Prediction (CASP) – Round XII (2017, methodology): “Assessment of model accuracy estimates has been included in CASP since CASP7 (2006) 16 and steady improvement in the accuracy of the methods was reported in CASPs 8, 9, 10, and 11.”
Assessment of hard target modeling in CASP12 reveals an emerging role of alignment‐based contact prediction methods (2018, methodology): “It was suggested in the CASP11 assessment that such methods were beneficial for FM prediction, 6 and the CASP12 contact assessment article [https://www.ncbi.nlm.nih.gov/ pubmed/29071738] and we here showed that such methods were helpful for modeling many hard targets in CASP12 as well.”
Topology Evaluation of Models for Difficult Targets in the 14th Round of the Critical Assessment of Protein Structure Prediction (CASP14) (2021, methodology): “5,6 This ranking scheme was compared to similar schemes where we varied different individual components: replace FM and FM/TBM targets with FM-only targets, use best models instead of first models, and replace chosen scores with FM formula from CASP13, or TBM formula for CASP13.”
Ensembling multiple raw coevolutionary features with deep residual neural networks for contact-map prediction in CASP13 (2019, background): “Significant progress has been recently witnessed on ab initio 3D structure prediction,(4-7) which is mainly due to the success of sequence-based contact predictions.(8,9) Due to its significant importance to protein structure prediction, the problem of contact-map prediction has drawn an increasing ”
Deep-learning contact-map guided protein structure prediction in CASP13 (2019, methodology): “7,8 In previous Critical Assessment of Protein Structure Prediction (CASP) experiments, we developed and tested two pipelines, “ Zhang-Server ” and “ QUARK ” , in the TBM and FM categories, respectively.”
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.”