Prediction of protein assemblies, the next frontier: The CASP14-CAPRI experiment.

Prediction of protein assemblies, the next frontier: The CASP14-CAPRI experiment.
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DOI:
10.1002/prot.26222
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发表时间:
2021-12
期刊:
影响因子:
2.9
通讯作者:
Wodak SJ
Wodak SJ
中科院分区:
生物学4区
文献类型:
--
作者:
Lensink MF;Brysbaert G;Mauri T;Nadzirin N;Velankar S;Chaleil RAG;Clarence T;Bates PA;Kong R;Liu B;Yang G;Liu M;Shi H;Lu X;Chang S;Roy RS;Quadir F;Liu J;Cheng J;Antoniak A;Czaplewski C;Giełdoń A;Kogut M;Lipska AG;Liwo A;Lubecka EA;Maszota-Zieleniak M;Sieradzan AK;Ślusarz R;Wesołowski PA;Zięba K;Del Carpio Muñoz CA;Ichiishi E;Harmalkar A;Gray JJ;Bonvin AMJJ;Ambrosetti F;Vargas Honorato R;Jandova Z;Jiménez-García B;Koukos PI;Van Keulen S;Van Noort CW;Réau M;Roel-Touris J;Kotelnikov S;Padhorny D;Porter KA;Alekseenko A;Ignatov M;Desta I;Ashizawa R;Sun Z;Ghani U;Hashemi N;Vajda S;Kozakov D;Rosell M;Rodríguez-Lumbreras LA;Fernandez-Recio J;Karczynska A;Grudinin S;Yan Y;Li H;Lin P;Huang SY;Christoffer C;Terashi G;Verburgt J;Sarkar D;Aderinwale T;Wang X;Kihara D;Nakamura T;Hanazono Y;Gowthaman R;Guest JD;Yin R;Taherzadeh G;Pierce BG;Barradas-Bautista D;Cao Z;Cavallo L;Oliva R;Sun Y;Zhu S;Shen Y;Park T;Woo H;Yang J;Kwon S;Won J;Seok C;Kiyota Y;Kobayashi S;Harada Y;Takeda-Shitaka M;Kundrotas PJ;Singh A;Vakser IA;Dapkūnas J;Olechnovič K;Venclovas Č;Duan R;Qiu L;Xu X;Zhang S;Zou X;Wodak SJ

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我们展示了CAPRI第50轮的结果,这是第4次CASP - CAPRI蛋白质组装预测联合挑战赛。该轮共有12个目标,包括6个二聚体、3个三聚体和3个高阶寡聚体。其中4个是容易的目标,对于这些目标,无论是整个组装体,还是(高阶寡聚体的)主要界面,都有良好的结构模板可用。8个是困难目标,对于这些目标,仅能找到与单个亚基有远缘关系的模板。25个CAPRI小组(包括8个自动服务器)每个目标提交了约1250个模型。20个小组(包括6个服务器)参加了CAPRI评分挑战赛,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。通过一个加权评分方案来衡量预测性能,该方案考虑了每个小组作为其排名前5的模型的一部分所提交的质量合格或更高的模型数量。与之前的CASP - CAPRI挑战赛相比,表现最佳的小组在本轮中为更大比例(70 - 75%)的目标提交了此类模型,但这些模型中高精度的较少。评分小组表现更强,更多小组为70 - 80%的目标提交了正确模型或实现了高精度预测。服务器总体表现较差,但MDOCKPP和LZERD服务器除外,它们的表现与人类小组相当。除了这些结果,还讨论了方法学上的重大进展,对蛋白质组装预测的现状提供了一个内容丰富的概述。
We present the results for CAPRI Round 50, the 4th joint CASP-CAPRI protein assembly prediction challenge. The Round comprised a total of 12 targets, including 6 dimers, 3 trimers, and 3 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 8 automatic servers submitted ~1250 models per target. Twenty groups including 6 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 5 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.
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