Eickholt Jesse, Wang Zheng, Cheng Jianlin
Department of Computer Science, University of Missouri, Columbia, MO 65211, USA.
BMC Struct Biol. 2011 Oct 12;11:38. doi: 10.1186/1472-6807-11-38.
Protein residue-residue contact prediction is important for protein model generation and model evaluation. Here we develop a conformation ensemble approach to improve residue-residue contact prediction. We collect a number of structural models stemming from a variety of methods and implementations. The various models capture slightly different conformations and contain complementary information which can be pooled together to capture recurrent, and therefore more likely, residue-residue contacts.
We applied our conformation ensemble approach to free modeling targets from both CASP8 and CASP9. Given a diverse ensemble of models, the method is able to achieve accuracies of. 48 for the top L/5 medium range contacts and. 36 for the top L/5 long range contacts for CASP8 targets (L being the target domain length). When applied to targets from CASP9, the accuracies of the top L/5 medium and long range contact predictions were. 34 and. 30 respectively.
When operating on a moderately diverse ensemble of models, the conformation ensemble approach is an effective means to identify medium and long range residue-residue contacts. An immediate benefit of the method is that when tied with a scoring scheme, it can be used to successfully rank models.
蛋白质残基-残基接触预测对于蛋白质模型生成和模型评估很重要。在此，我们开发了一种构象集合方法来改进残基-残基接触预测。我们收集了许多源自各种方法和实现的结构模型。各种模型捕获了略有不同的构象，并包含可以汇集在一起以捕获反复出现的、因此更有可能的残基-残基接触的互补信息。
我们将构象集合方法应用于来自CASP8和CASP9的自由建模目标。给定一组多样的模型，该方法能够实现以下准确率：对于CASP8目标（L为目标域长度），前L/5中等范围接触的准确率为0.48，前L/5长范围接触的准确率为0.36。当应用于来自CASP9的目标时，前L/5中等和长范围接触预测的准确率分别为0.34和0.30。
当在一组适度多样的模型上运行时，构象集合方法是识别中等和长范围残基-残基接触的有效手段。该方法的一个直接好处是，当与评分方案结合使用时，它可以成功地对模型进行排名。
