Highlights of Model Quality Assessment in CASP16.

Alisia Fadini,Recep Adiyaman, Shaima N Alhaddad, Behnosh Behzadi,Jianlin Cheng, Xinyue Cui, Nicholas S Edmunds, Lydia Freddolino, Ahmet G Genc,Fang Liang,Dong Liu,Jian Liu, Quancheng Liu,Liam J McGuffin, Pawan Neupane, Chunxiang Peng, David R Shortle, Meng Sun, Haodong Wang,Qiqige Wuyun,Guijun Zhang, Xuanfeng Zhao,Wei Zheng,Randy J Read

Proteins: Structure, Function And Bioinformatics（2025）

Cambridge Institute for Medical Research

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摘要

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.

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关键词

computational molecular biology,molecular models,protein conformation,protein domains

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