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/.

中文翻译：

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SPOT-Disorder2：通过集成深度学习改进的蛋白质固有疾病预测。

已经发现，内在无序或无结构的蛋白质（或蛋白质中的区域）在广泛的生物学功能中很重要，并与许多疾病有关。由于内在疾病的实验测定成本高昂且效率低，并且未注释的蛋白质序列呈指数增长，因此开发互补的计算预测方法已成为数十年来研究的一个活跃领域。在这里，我们采用了深层压缩和激发残差起始和长短期记忆（LSTM）网络的集合，利用进化信息和预测的一维结构特性来预测蛋白质固有的紊乱。这种称为SPOT-Disorder2的方法不仅在我们以前仅基于LSTM网络的技术上提供了实质性且一致的改进，而且在三个独立的测试中，与其他最新技术相比，无序氨基酸与有序氨基酸残基的比率不同，并且具有丰富或有限的进化信息。更重要的是，与直接设计用于MoRF预测的方法相比，在SPOT-Disorder2中预测的半无序区域在识别分子识别特征（MoRF）方面更准确。SPOT-Disorder2可作为Web服务器和独立程序在https://sparks-lab.org/server/spot-disorder2/上获得。与直接设计用于MoRF预测的方法相比，在SPOT-Disorder2中预测的半混乱区域在识别分子识别特征（MoRF）方面更准确。SPOT-Disorder2可作为Web服务器和独立程序在https://sparks-lab.org/server/spot-disorder2/上获得。与直接设计用于MoRF预测的方法相比，在SPOT-Disorder2中预测的半混乱区域在识别分子识别特征（MoRF）方面更准确。SPOT-Disorder2可作为Web服务器和独立程序在https://sparks-lab.org/server/spot-disorder2/上获得。