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评估 CASP14 中蛋白质模型结构准确性估计:新老挑战。

Assessment of protein model structure accuracy estimation in CASP14: Old and new challenges.

机构信息

Department of Chemistry, Seoul National University, Seoul, Republic of Korea.

Galux Inc., Seoul, Republic of Korea.

出版信息

Proteins. 2021 Dec;89(12):1940-1948. doi: 10.1002/prot.26192. Epub 2021 Aug 5.

Abstract

In CASP, blind testing of model accuracy estimation methods has been conducted on models submitted by tertiary structure prediction servers. In CASP14, model accuracy estimation results were evaluated in terms of both global and local structure accuracy, as in the previous CASPs. Unlike the previous CASPs that did not show pronounced improvements in performance, the best single-model method (from the Baker group) showed an improved performance in CASP14, particularly in evaluating global structure accuracy when compared to both the best single-model methods in previous CASPs and the best multi-model methods in the current CASP. Although the CASP14 experiment on model accuracy estimation did not deal with the structures generated by AlphaFold2, new challenges that have arisen due to the success of AlphaFold2 are discussed.

摘要

在 CASP 中,针对提交的三级结构预测服务器模型,对模型准确性评估方法进行了盲测。在 CASP14 中,模型准确性评估结果从全局和局部结构准确性两方面进行了评估,与之前的 CASP 相同。与之前的 CASP 没有明显性能提升不同,最好的单模型方法(来自 Baker 小组)在 CASP14 中的表现有所提升,尤其是在评估全局结构准确性方面,与之前 CASP 中最好的单模型方法和当前 CASP 中最好的多模型方法相比。虽然 CASP14 对模型准确性评估的实验并未涉及由 AlphaFold2 生成的结构,但由于 AlphaFold2 的成功所带来的新挑战也在讨论之列。

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