SPOT-Disorder2: Improved Protein Intrinsic Disorder Prediction by Ensembled Deep Learning
SPOT-Disorder2: Improved Protein Intrinsic Disorder Prediction by Ensembled Deep Learning
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DOI：
10.1016/j.gpb.2019.01.004
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发表时间：
2019-12-01
影响因子：
9.5
通讯作者：
Zhou, Yaoqi
中科院分区：
文献类型：
--
作者：
Hanson, Jack;Paliwal, Kuldip K.;Zhou, Yaoqi
已经发现，蛋白质内的无序或非结构化蛋白质（或蛋白质中的区域）在广泛的生物学功能中是重要的，并且与许多疾病有关。由于实验测定内在无序的高成本和低效率以及未注释的蛋白质序列的指数增加，开发互补的计算预测方法几十年来一直是一个活跃的研究领域。在这里，我们采用了深度挤压和激发残差初始和长短期记忆（LSTM）网络的集合，用于预测蛋白质内在无序，并从进化信息和预测一维结构特性中输入。该方法被称为SPOT-Disorder 2，不仅比我们以前单独基于LSTM网络的技术提供了实质性和一致的改进，而且在三个独立的测试中也比其他最先进的技术提供了实质性和一致的改进，这些测试具有不同的无序与有序氨基酸残基的比例，以及具有丰富或有限进化信息的序列。更重要的是，在SPOT-Disorder 2中预测的半无序区域在识别分子识别特征（MoRFs）方面比直接设计用于MoRFs预测的方法更准确。SPOT-Disorder 2作为Web服务器和独立程序在https://sparks-lab.org/server/spot-disorder2/上提供。
Intrinsically disordered or unstructured proteins (or regions in proteins) have been found to be important in a wide range of biological functions and implicated in many diseases. Due to the high cost and low efficiency of experimental determination of intrinsic disorder and the exponential increase of unannotated protein sequences, developing complementary computational prediction methods has been an active area of research for several decades. Here, we employed an ensemble of deep Squeeze-and-Excitation residual inception and long short-term memory (LSTM) networks for predicting protein intrinsic disorder with input from evolutionary information and predicted one-dimensional structural properties. The method, called SPOT-Disorder2, offers substantial and consistent improvement not only over our previous technique based on LSTM networks alone, but also over other state-of-the-art techniques in three independent tests with different ratios of disordered to ordered amino acid residues, and for sequences with either rich or limited evolutionary information. More importantly, semi-disordered regions predicted in SPOT-Disorder2 are more accurate in identifying molecular recognition features (MoRFs) than methods directly designed for MoRFs prediction. SPOT-Disorder2 is available as a web server and as a standalone program at https://sparks-lab.org/server/spot-disorder2/.