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Evaluation of template-based modeling in CASP13.

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Peer-reviewed

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Abstract

Performance in the template-based modeling (TBM) category of CASP13 is assessed here, using a variety of metrics. Performance of the predictor groups that participated is ranked using the primary ranking score that was developed by the assessors for CASP12. This reveals that the best results are obtained by groups that include contact predictions or inter-residue distance predictions derived from deep multiple sequence alignments. In cases where there is a good homolog in the wwPDB (TBM-easy category), the best results are obtained by modifying a template. However, for cases with poorer homologs (TBM-hard), very good results can be obtained without using an explicit template, by deep learning algorithms trained on the wwPDB. Alternative metrics are introduced, to allow testing of aspects of structural models that are not addressed by traditional CASP metrics. These include comparisons to the main-chain and side-chain torsion angles of the target, and the utility of models for solving crystal structures by the molecular replacement method. The alternative metrics are poorly correlated with the traditional metrics, and it is proposed that modeling has reached a sufficient level of maturity that the best models should be expected to satisfy this wider range of criteria.

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Keywords

CASP, molecular replacement, structure prediction, template-based modeling, Algorithms, Computational Biology, Computer Simulation, Databases, Protein, Models, Molecular, Protein Conformation, Protein Folding, Proteins, Sequence Analysis, Protein

Journal Title

Proteins

Conference Name

Journal ISSN

0887-3585
1097-0134

Volume Title

87

Publisher

Wiley
Sponsorship
European Commission Horizon 2020 (H2020) Marie Sklodowska-Curie actions (790122)
Wellcome Trust (209407/Z/17/Z)
Wellcome Trust (082961/Z/07/A)