Division of Bioinformatics, Department of Physics, Chemistry and Biology, Linköping University, SE-581 83 Linköping, Sweden.
Acta Crystallogr D Struct Biol. 2020 Mar 1;76(Pt 3):285-290. doi: 10.1107/S2059798320000972. Epub 2020 Mar 3.
Model quality assessment programs estimate the quality of protein models and can be used to estimate local error in protein models. ProQ3D is the most recent and most accurate version of our software. Here, it is demonstrated that it is possible to use local error estimates to substantially increase the quality of the models for molecular replacement (MR). Adjusting the B factors using ProQ3D improved the log-likelihood gain (LLG) score by over 50% on average, resulting in significantly more successful models in MR compared with not using error estimates. On a data set of 431 homology models to address difficult MR targets, models with error estimates from ProQ3D received an LLG of >50 for almost half of the models 209/431 (48.5%), compared with 175/431 (40.6%) for the previous version, ProQ2, and only 74/431 (17.2%) for models with no error estimates, clearly demonstrating the added value of using error estimates to enable MR for more targets. ProQ3D is available from http://proq3.bioinfo.se/ both as a server and as a standalone download.
模型质量评估程序可评估蛋白质模型的质量,并可用于估计蛋白质模型的局部误差。ProQ3D 是我们软件的最新和最准确版本。在这里,证明了使用局部误差估计可以显著提高分子替换 (MR) 模型的质量。使用 ProQ3D 调整 B 因子,平均可将对数似然增益 (LLG) 得分提高 50%以上,与不使用误差估计相比,MR 中成功的模型明显更多。在一组 431 个同源模型的数据集中,用于解决困难的 MR 靶标,ProQ3D 的误差估计模型的 LLG 大于 50 的有近一半,即 209/431(48.5%),而前一版本 ProQ2 为 175/431(40.6%),没有误差估计的模型只有 74/431(17.2%),这清楚地表明了使用误差估计来为更多的靶标启用 MR 的附加值。ProQ3D 可从 http://proq3.bioinfo.se/ 获得,既可以作为服务器,也可以作为独立下载。