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嗜盐菌中结构无序的错误预测。

Misprediction of Structural Disorder in Halophiles.

机构信息

Institute of Enzymology, Research Centre for Natural Sciences of the Hungarian Academy of Sciences, 1117 Budapest, Hungary.

VIB Center for Structural Biology (CSB), 1050 Brussels, Belgium.

出版信息

Molecules. 2019 Jan 29;24(3):479. doi: 10.3390/molecules24030479.

Abstract

Whereas the concept of intrinsic disorder derives from biophysical observations of the lack of structure of proteins or protein regions under native conditions, many of our respective concepts rest on proteome-scale bioinformatics predictions. It is established that most predictors work reliably on proteins commonly encountered, but it is often neglected that we know very little about their performance on proteins of microorganisms that thrive in environments of extreme temperature, pH, or salt concentration, which may cause adaptive sequence composition bias. To address this issue, we predicted structural disorder for the complete proteomes of different extremophile groups by popular prediction methods and compared them to those of the reference mesophilic group. While significant deviations from mesophiles could be explained by a lack or gain of disordered regions in hyperthermophiles and radiotolerants, respectively, we found systematic overprediction in the case of halophiles. Additionally, examples were collected from the Protein Data Bank (PDB) to demonstrate misprediction and to help understand the underlying biophysical principles, i.e., halophilic proteins maintain a highly acidic and hydrophilic surface to avoid aggregation in high salt conditions. Although sparseness of data on disordered proteins from extremophiles precludes the development of dedicated general predictors, we do formulate recommendations for how to address their disorder with current bioinformatics tools.

摘要

虽然内源性无序的概念源于在天然条件下缺乏蛋白质或蛋白质区域结构的生物物理观察,但我们的许多概念都基于蛋白质组规模的生物信息学预测。已经确定,大多数预测器在常见的蛋白质上可靠地工作,但人们往往忽略了一个事实,即我们对在极端温度、pH 值或盐浓度等环境中茁壮成长的微生物的蛋白质的性能知之甚少,这些环境可能导致适应性序列组成偏差。为了解决这个问题,我们通过流行的预测方法预测了不同极端微生物组的完整蛋白质组的结构无序性,并将其与参考嗜中温微生物组进行了比较。虽然在高温菌和耐辐射菌中,无规则区域的缺失或获得可以分别解释与嗜中温菌的显著差异,但在嗜盐菌中我们发现了系统的过度预测。此外,还从蛋白质数据库(PDB)中收集了示例来说明错误预测,并帮助理解潜在的生物物理原理,即嗜盐蛋白保持高度酸性和亲水性表面以避免在高盐条件下聚集。尽管来自极端微生物的无序蛋白质的数据稀疏,无法开发专用的通用预测器,但我们确实为如何使用当前的生物信息学工具解决它们的无序性提出了建议。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c0fc/6384707/638f75918e45/molecules-24-00479-g001.jpg

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