@article{Zhai2026, 
author = {Jiaqi Zhai and Wenda Wang and Yixiang Huang and Xinqi Gong},
title = {Evaluation Metrics and Quality Assessment Methods for Predicted Protein Complex Structures},
year = {2026},
journal = {Tsinghua Science and Technology},
keywords = {evaluation metrics, predicted protein complex structures, Quality Assessment (QA)},
url = {https://www.sciopen.com/article/10.26599/TST.2025.9010068},
doi = {10.26599/TST.2025.9010068},
abstract = {Accurately evaluating predicted protein structures is crucial for improving protein structure prediction ability. With advancements in computational methods, particularly AlphaFold2, which has revolutionized the prediction of protein monomers, the focus has now shifted to protein quaternary structures. Accurately predicting protein complex structures is becoming increasingly important. Evaluating the quality of predicted protein complex structures has become essential, involving machine learning and other methods. This evaluation can be categorized into two aspects: Assessing predicted structures when the native protein structure is known to identify the best option, and guiding the structure prediction process when the native structure is unknown. Despite advancements, assessing protein quaternary structures is still in its early stages and faces many unresolved issues. This review explores common evaluation metrics and various quality assessment methods. At the same time, we highlight existing challenges in predicting protein multimers and outline potential future directions for further development.}
}