Interdisciplinary Biological Sciences, Northwestern University, Evanston, IL, 60208, USA.
Department of Molecular Medicine and USF Health Byrd Alzheimer's Research Institute, Morsani College of Medicine, University of South Florida, Tampa, Florida, 33612, USA.
Proteomics. 2019 Mar;19(6):e1800415. doi: 10.1002/pmic.201800415. Epub 2019 Mar 1.
Since the early 2000s, numerous computational tools have been created and used to predict intrinsic disorder in proteins. At present, the output from these algorithms is difficult to interpret in the absence of standards or references for comparison. There are many reasons to establish a set of standard-based guidelines to evaluate computational protein disorder predictions. This viewpoint explores a handful of these reasons, including standardizing nomenclature to improve communication, rigor and reproducibility, and making it easier for newcomers to enter the field. An approach for reporting predicted disorder in single proteins with respect to whole proteomes is discussed. The suggestions are not intended to be formulaic; they should be viewed as a starting point to establish guidelines for interpreting and reporting computational protein disorder predictions.
自 21 世纪初以来，已经创建并使用了许多计算工具来预测蛋白质中的内在无序。目前，由于缺乏标准或参考物进行比较，这些算法的输出结果难以解释。建立一套基于标准的准则来评估计算蛋白质无序预测有很多原因。本观点探讨了其中的一些原因，包括通过标准化命名法来提高沟通、严谨性和可重复性，以及为新进入该领域的人提供便利。还讨论了一种针对整个蛋白质组中单蛋白预测无序的报告方法。这些建议并非一成不变的；它们应被视为建立解释和报告计算蛋白质无序预测的准则的起点。
