O'Brien Kevin T, Mooney Catherine, Lopez Cyril, Pollastri Gianluca, Shields Denis C
School of Medicine, University College Dublin, Dublin, Ireland.
Conway Institute of Biomolecular and Biomedical Research, University College Dublin, Dublin, Ireland.
R Soc Open Sci. 2020 Jan 15;7(1):191239. doi: 10.1098/rsos.191239. eCollection 2020 Jan.
The polyproline II helix (PPIIH) is an extended protein left-handed secondary structure that usually but not necessarily involves prolines. Short PPIIHs are frequently, but not exclusively, found in disordered protein regions, where they may interact with peptide-binding domains. However, no readily usable software is available to predict this state. We developed PPIIPRED to predict polyproline II helix secondary structure from protein sequences, using bidirectional recurrent neural networks trained on known three-dimensional structures with dihedral angle filtering. The performance of the method was evaluated in an external validation set. In addition to proline, PPIIPRED favours amino acids whose side chains extend from the backbone (Leu, Met, Lys, Arg, Glu, Gln), as well as Ala and Val. Utility for individual residue predictions is restricted by the rarity of the PPIIH feature compared to structurally common features. The software, available at http://bioware.ucd.ie/PPIIPRED, is useful in large-scale studies, such as evolutionary analyses of PPIIH, or computationally reducing large datasets of candidate binding peptides for further experimental validation.
多聚脯氨酸II螺旋（PPIIH）是一种伸展的蛋白质左手二级结构，通常但不一定涉及脯氨酸。短的PPIIH经常（但并非唯一）出现在无序蛋白质区域，在那里它们可能与肽结合结构域相互作用。然而，目前没有易于使用的软件可用于预测这种状态。我们开发了PPIIPRED，用于从蛋白质序列预测多聚脯氨酸II螺旋二级结构，使用基于已知三维结构并经过二面角过滤训练的双向递归神经网络。该方法的性能在外部验证集中进行了评估。除脯氨酸外，PPIIPRED还偏好侧链从主链伸出的氨基酸（亮氨酸、甲硫氨酸、赖氨酸、精氨酸、谷氨酸、谷氨酰胺），以及丙氨酸和缬氨酸。与结构上常见的特征相比，PPIIH特征的稀少性限制了其对单个残基预测的实用性。该软件可在http://bioware.ucd.ie/PPIIPRED获取，在大规模研究中很有用，例如对PPIIH的进化分析，或在计算上减少候选结合肽的大型数据集以进行进一步的实验验证。
