Department of Molecular Medicine and USF Health Byrd Alzheimer's Research Institute, Morsani College of Medicine, University of South Florida, Tampa, Florida.
Department of Computer Science, Virginia Commonwealth University, Richmond, Virginia.
Curr Protoc. 2023 Jun;3(6):e802. doi: 10.1002/cpz1.802.
There are over 100 computational predictors of intrinsic disorder. These methods predict amino acid-level propensities for disorder directly from protein sequences. The propensities can be used to annotate putative disordered residues and regions. This unit provides a practical and holistic introduction to the sequence-based intrinsic disorder prediction. We define intrinsic disorder, explain the format of computational prediction of disorder, and identify and describe several accurate predictors. We also introduce recently released databases of intrinsic disorder predictions and use an illustrative example to provide insights into how predictions should be interpreted and combined. Lastly, we summarize key experimental methods that can be used to validate computational predictions. © 2023 Wiley Periodicals LLC.
有超过 100 种计算预测蛋白质内无序性的方法。这些方法可以直接从蛋白质序列预测氨基酸水平的无序倾向。这些倾向可用于注释潜在的无序残基和区域。本单元提供了一个实用的、整体的基于序列的内在无序性预测介绍。我们定义了内在无序性，解释了无序性的计算预测格式，并确定和描述了几个准确的预测器。我们还介绍了最近发布的内在无序性预测数据库，并使用一个说明性的例子深入了解如何解释和组合预测。最后，我们总结了可用于验证计算预测的关键实验方法。© 2023 Wiley Periodicals LLC。
