AlphaFold2结构低plddt区域的分类预测模式:近预测、伪结构和铁丝网。

Christopher J Williams,Vincent B Chen,David C Richardson,Jane S Richardson
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引用次数: 0

摘要

AlphaFold2蛋白结构预测广泛应用于结构生物学。这些预测,特别是对真核蛋白质的预测,经常包含大量低于pLDDT = 70水平的预测区域,这是高置信度的经验截断值。这项工作通过对AlphaFold蛋白质结构数据库提供的人类蛋白质组预测的调查,确定了低plddt区域的主要行为模式。近乎预测的模式类似于折叠的蛋白质,可以是一个近乎准确的预测。带刺铁丝非常不像蛋白质,可以通过宽环形线圈识别,没有包装接触和许多签名验证异常值,并且它代表了一个构象没有预测价值的区域。伪结构表现为一种中间行为,具有孤立的和形成不良的二级结构样元素的误导外观。这些预测模式与MobiDB的无序注释进行了比较,显示出铁丝网/假结构与许多无序测量之间的普遍相关性,假结构与信号肽之间的相关性,以及接近预测和条件折叠区域之间的相关性。为了使用户能够在预测中识别这些区域,我们开发了一个新的Phenix工具,包含了这项工作的结果,包括预测注释、可视化标记和基于这些预测模式的残留物选择。该工具将帮助用户开发解释困难的AlphaFold预测的专业知识,并确定接近预测的区域,当预测不包含足够的高plddt区域时,可以帮助进行分子替换。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Categorizing prediction modes within low-pLDDT regions of AlphaFold2 structures: near-predictive, pseudostructure and barbed wire.
AlphaFold2 protein structure predictions are widely available for structural biology uses. These predictions, especially for eukaryotic proteins, frequently contain extensive regions predicted below the pLDDT = 70 level, the rule-of-thumb cutoff for high confidence. This work identifies major modes of behavior within low-pLDDT regions through a survey of human proteome predictions provided by the AlphaFold Protein Structure Database. The near-predictive mode resembles folded protein and can be a nearly accurate prediction. Barbed wire is extremely unprotein-like, being recognized by wide looping coils, an absence of packing contacts and numerous signature validation outliers, and it represents a region where the conformation has no predictive value. Pseudostructure presents an intermediate behavior with a misleading appearance of isolated and badly formed secondary-structure-like elements. These prediction modes are compared with annotations of disorder from MobiDB, showing general correlation between barbed wire/pseudostructure and many measures of disorder, an association between pseudostructure and signal peptides, and an association between near-predictive and regions of conditional folding. To enable users to identify these regions within a prediction, a new Phenix tool is developed encompassing the results of this work, including prediction annotation, visual markup and residue selection based on these prediction modes. This tool will help users develop expertise in interpreting difficult AlphaFold predictions and identify the near-predictive regions that can aid in molecular replacement when a prediction does not contain enough high-pLDDT regions.
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