Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Alberta, Canada.
Amino Acids. 2011 Mar;40(3):963-73. doi: 10.1007/s00726-010-0721-1. Epub 2010 Aug 21.
Several descriptors of protein structure at the sequence and residue levels have been recently proposed. They are widely adopted in the analysis and prediction of structural and functional characteristics of proteins. Numerous in silico methods have been developed for sequence-based prediction of these descriptors. However, many of them do not have a public web-server and only a few integrate multiple descriptors to improve the predictions. We introduce iFC² (integrated prediction of fold, class, and content) server that is the first to integrate three modern predictors of sequence-level descriptors. They concern fold type (PFRES), structural class (SCEC), and secondary structure content (PSSC-core). The server exploits relations between the three descriptors to implement a cross-evaluation procedure that improves over the predictions of the individual methods. The iFC² annotates fold and class predictions as potentially correct/incorrect. When tested on datasets with low-similarity chains, for the fold prediction iFC² labels 82% of the PFRES predictions as correct and the accuracy of these predictions equals 72%. The accuracy of the remaining 28% of the PFRES predictions equals 38%. Similarly, our server assigns correct labels for over 79% of SCEC predictions, which are shown to be 98% accurate, while the remaining SCEC predictions are only 15% accurate. These results are shown to be competitive when contrasted against recent relevant web-servers. Predictions on CASP8 targets show that the content predicted by iFC² is competitive when compared with the content computed from the tertiary structures predicted by three best-performing methods in CASP8. The iFC² server is available at http://biomine.ece.ualberta.ca/1D/1D.html .
最近提出了几个用于序列和残基水平的蛋白质结构描述符。它们广泛应用于蛋白质结构和功能特性的分析和预测。已经开发了许多基于序列的这些描述符的预测的计算方法。然而，其中许多方法没有公共网络服务器，只有少数方法集成了多个描述符以提高预测能力。我们引入了 iFC²（折叠类型、结构类别和二级结构含量的综合预测）服务器，该服务器是第一个集成三个现代序列水平描述符预测器的服务器。它们涉及折叠类型（PFRES）、结构类别（SCEC）和二级结构含量（PSSC-core）。该服务器利用这三个描述符之间的关系来实现交叉评估过程，从而提高了单个方法的预测能力。iFC² 将折叠和类别预测标记为潜在正确/不正确。在低相似度链数据集上进行测试时，对于折叠预测，iFC² 将 82%的 PFRES 预测标记为正确，这些预测的准确性为 72%。其余 28%的 PFRES 预测的准确性为 38%。类似地，我们的服务器为超过 79%的 SCEC 预测分配了正确的标签，这些预测被证明是 98%准确的，而其余的 SCEC 预测仅为 15%准确。与最近的相关网络服务器相比，这些结果具有竞争力。对 CASP8 目标的预测表明，与通过 CASP8 中表现最好的三种方法预测的三级结构计算的内容相比，iFC² 预测的内容具有竞争力。iFC² 服务器可在 http://biomine.ece.ualberta.ca/1D/1D.html 访问。
