CNRS UMR8576 UGSF, Institute for Structural and Functional Glycobiology, University of Lille, Lille, France.
Protein Data Bank in Europe (PDBe), European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Cambridge, UK.
Proteins. 2021 Dec;89(12):1800-1823. doi: 10.1002/prot.26222. Epub 2021 Sep 13.
We present the results for CAPRI Round 50, the fourth joint CASP-CAPRI protein assembly prediction challenge. The Round comprised a total of twelve targets, including six dimers, three trimers, and three higher-order oligomers. Four of these were easy targets, for which good structural templates were available either for the full assembly, or for the main interfaces (of the higher-order oligomers). Eight were difficult targets for which only distantly related templates were found for the individual subunits. Twenty-five CAPRI groups including eight automatic servers submitted ~1250 models per target. Twenty groups including six servers participated in the CAPRI scoring challenge submitted ~190 models per target. The accuracy of the predicted models was evaluated using the classical CAPRI criteria. The prediction performance was measured by a weighted scoring scheme that takes into account the number of models of acceptable quality or higher submitted by each group as part of their five top-ranking models. Compared to the previous CASP-CAPRI challenge, top performing groups submitted such models for a larger fraction (70-75%) of the targets in this Round, but fewer of these models were of high accuracy. Scorer groups achieved stronger performance with more groups submitting correct models for 70-80% of the targets or achieving high accuracy predictions. Servers performed less well in general, except for the MDOCKPP and LZERD servers, who performed on par with human groups. In addition to these results, major advances in methodology are discussed, providing an informative overview of where the prediction of protein assemblies currently stands.
我们呈现了 CAPRI 第 50 轮的结果,这是第四次 CASP-CAPRI 蛋白质组装预测挑战赛的联合赛。本轮共有 12 个目标,包括 6 个二聚体、3 个三聚体和 3 个更高阶的寡聚体。其中 4 个是简单的目标,对于这些目标,完整的组装或主要的界面(高阶寡聚体)都有良好的结构模板。8 个是困难的目标,对于这些目标,只发现了与单个亚基远相关的模板。25 个 CAPRI 组,包括 8 个自动服务器,每个目标提交了约 1250 个模型。20 个组,包括 6 个服务器,参加了 CAPRI 评分挑战,每个目标提交了约 190 个模型。使用经典的 CAPRI 标准评估预测模型的准确性。预测性能通过加权评分方案进行衡量,该方案考虑了每个组提交的可接受质量或更高的模型数量,作为其前 5 个排名模型的一部分。与之前的 CASP-CAPRI 挑战赛相比,表现最佳的组在本轮提交了更多的此类模型(70-75%),但这些模型的准确率较低。评分组的表现更强,更多的组提交了 70-80%的目标的正确模型,或实现了高精度的预测。服务器的表现一般较差,除了 MDOCKPP 和 LZERD 服务器,它们与人类组的表现相当。除了这些结果,还讨论了主要的方法学进展,为蛋白质组装的预测提供了一个信息丰富的概述。