Highlights of Model Quality Assessment in CASP16.

Model quality assessment (MQA) remains a critical component of structural bioinformatics for both structure predictors and experimentalists seeking to use predictions for downstream applications. In CASP16, the Evaluation of Model Accuracy (EMA) category featured both global and local quality estimation for multimeric assemblies (QMODE1 and QMODE2), as well as a novel QMODE3 challenge-requiring predictors to identify the best five models from thousands generated by MassiveFold. This paper presents detailed results from several leading CASP16 EMA methods, highlighting the strengths and limitations of the approaches.

Description

Publication status: Published

Funder: Pioneer and Leading Goose R&D Program of Zhejiang

Funder: Republic of Turkey Ministry of National Education

Funder: National Institutes of Health (USA); doi: https://doi.org/10.13039/100000002

Funder: Kuwaiti Government

Funder: David R Shortle Protein Research Fund

Keywords

computational molecular biology, molecular models, protein conformation, protein domains, Computational Biology, Protein Conformation, Nucleic Acid Conformation, Models, Molecular, Sequence Alignment, Protein Folding

Journal Title

Proteins

Journal ISSN

0887-3585
1097-0134

Publisher

Wiley

Publisher DOI

https://doi.org/10.1002/prot.70035

Rights and licensing

Except where otherwised noted, this item's license is described as http://creativecommons.org/licenses/by/4.0/

Sponsorship

BBSRC (BB/Y009398/1)
Wellcome Trust (209407/Z/17/Z)

There is a long list of non-UK funding sources from other authors on this collaborative papers.

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