FTIP: an accurate and efficient method for global protein surface comparison.
FTIP: an accurate and efficient method for global protein surface comparison.
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FTIP：一种准确有效的全局蛋白质表面比较方法。
DOI：
10.1093/bioinformatics/btaa076
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发表时间：
2020
期刊：
影响因子：
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通讯作者：
Zhang,Jinfeng
中科院分区：
文献类型：
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作者：
Zhang,Yuan;Sui,Xing;Stagg,Scott;Zhang,Jinfeng
与蛋白质结构比对/比较的其他研究工作相比，全球蛋白质表面比较(GPSC)的研究由于缺乏与GPSC相关的实际应用而受到限制。然而，冷冻电子断层扫描(CET)技术的进步使得从蛋白质表面形状识别蛋白质的方法变得非常有用。在这项研究中，我们介绍了一种新的方法，称为FTIP(最远点采样(FPS)-增强的基于三角剖分的迭代最近点(ICP))。我们将其应用于蛋白质分类，仅使用表面形状信息。我们首先进行FPS从蛋白质表面提取特征点，这些特征点表征蛋白质的表面形状。然后利用一种改进的基于三角剖分的高效ICP算法对两个待比对蛋白质的特征点进行比对。在一个包含2329个蛋白质的基准数据集上，FTIP显著优于3D Zernike描述符(3DZD)，3D Zernike描述符是用于GPSC的最先进方法。使用真实和模拟的低温电子显微镜数据，我们表明FTIP可以在未来应用于CET实验中的蛋白质识别问题。
Global protein surface comparison (GPSC) studies have been limited compared to other research works on protein structure alignment/comparison due to a lack of real applications associated with GPSC. However, the technology advances in cryo-electron tomography (CET) have made methods to identify proteins from their surface shapes extremely useful. In this study, we introduced a new method for GPSC called FTIP (Furthest point sampling (FPS)-enhanced Triangulation-based Iterative Closest Point (ICP)). We applied it to protein classification, using only surface shape information. We first performed FPS to extract feature points from protein surfaces that characterize the surface shapes of proteins. Then we used a modified triangulation based efficient ICP algorithm to align the feature points of the two proteins to be compared. FTIP significantly outperformed the 3D Zernike descriptor (3DZD), a state-of-the-art method for GPSC, on a benchmark dataset with 2329 proteins. Using real and simulated cryo-EM data, we show that FTIP could be applied in the future to address problems in protein identification in CET experiments.