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BASILIScan: a tool for high-throughput analysis of intrinsic disorder patterns in homologous proteins

机译:Basiliscan:同源蛋白质中固有疾病模式的高通量分析的工具

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摘要

Intrinsic structural disorder is a common property of many proteins, especially in eukaryotic and virus proteomes. The tendency of some proteins or protein regions to exist in a disordered state usually precludes their structural characterisation and renders them especially difficult for experimental handling after recombinant expression. A new intuitive, publicly-available computational resource, called BASILIScan, is presented here. It provides a BLAST-based search for close homologues of the protein of interest, integrated with a simultaneous prediction of intrinsic disorder together with a robust data viewer and interpreter. This allows for a quick, high-throughput screening, scoring and selection of closely-related yet highly structured homologues of the protein of interest. Comparative parallel analysis of the conservation of extended regions of disorder in multiple sequences is also offered. The use of BASILIScan and its capacity for yielding biologically applicable predictions is demonstrated. Using a high-throughput BASILIScan screen it is also shown that a large proportion of the human proteome displays homologous sequences of superior intrinsic structural order in many related species. Through the swift identification of intrinsically stable homologues and poorly conserved disordered regions by the BASILIScan software, the chances of successful recombinant protein expression and compatibility with downstream applications such as crystallisation can be greatly increased.
机译:内在结构障碍是许多蛋白质的常见性,特别是在真核和病毒蛋白质中的常见性。一些蛋白质或蛋白质区域以无序状态存在的趋势通常妨碍了它们的结构表征,并使它们特别难以在重组表达后进行实验处理。这里给出了一个名为Basiliscan的新直观,可公开的计算资源。它提供了一种基于炸药的搜索,用于感兴趣的蛋白质的近似同源物,与强大的数据查看器和解释器一起同时预测内在病症。这允许快速,高通量的筛选,评分和选择感兴趣的蛋白质的密切且高度结构的同源物。还提供了对多个序列中延长区域的延长区域守恒的比较平行分析。证明了底栖省的使用及其产生生物应用预测的能力。使用高通量底池筛网还表明,大部分人蛋白质组在许多相关物种中显示出优异的内在结构顺序的同源序列。通过巨大的稳定性识别本质上稳定的同源物和底座软件不良的混乱区域,可以大大增加成功重组蛋白表达和与下游应用的相容性的可能性。可以大大增加。

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  • 来源
    《BMC Genomics》 |2018年第1期|共9页
  • 作者

    Michal Barski;

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