Measuring the functional sequence complexity of proteins.

Kirk K Durston, David K Y Chiu, David L Abel, Jack T Trevors
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引用次数: 24

Abstract

Background: Abel and Trevors have delineated three aspects of sequence complexity, Random Sequence Complexity (RSC), Ordered Sequence Complexity (OSC) and Functional Sequence Complexity (FSC) observed in biosequences such as proteins. In this paper, we provide a method to measure functional sequence complexity.

Methods and results: We have extended Shannon uncertainty by incorporating the data variable with a functionality variable. The resulting measured unit, which we call Functional bit (Fit), is calculated from the sequence data jointly with the defined functionality variable. To demonstrate the relevance to functional bioinformatics, a method to measure functional sequence complexity was developed and applied to 35 protein families. Considerations were made in determining how the measure can be used to correlate functionality when relating to the whole molecule and sub-molecule. In the experiment, we show that when the proposed measure is applied to the aligned protein sequences of ubiquitin, 6 of the 7 highest value sites correlate with the binding domain.

Conclusion: For future extensions, measures of functional bioinformatics may provide a means to evaluate potential evolving pathways from effects such as mutations, as well as analyzing the internal structural and functional relationships within the 3-D structure of proteins.

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测量蛋白质的功能序列复杂性。
Abel和Trevors描述了在蛋白质等生物序列中观察到的序列复杂性的三个方面,即随机序列复杂性(RSC)、有序序列复杂性(OSC)和功能序列复杂性(FSC)。本文提供了一种测量函数序列复杂度的方法。方法和结果:我们通过将数据变量与功能变量合并来扩展香农不确定性。由此产生的测量单位,我们称之为功能位(Fit),由序列数据与定义的功能变量一起计算。为了证明与功能生物信息学的相关性,开发了一种测量功能序列复杂性的方法,并将其应用于35个蛋白质家族。在确定如何使用该测量来关联与整个分子和亚分子相关的功能时进行了考虑。在实验中,我们表明,当提出的测量应用于泛素排列的蛋白质序列时,7个最高值位点中有6个与结合域相关。结论:对于未来的扩展,功能生物信息学的测量可能提供一种方法来评估潜在的进化途径,如突变,以及分析蛋白质三维结构中的内部结构和功能关系。
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来源期刊
Theoretical Biology and Medical Modelling
Theoretical Biology and Medical Modelling MATHEMATICAL & COMPUTATIONAL BIOLOGY-
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审稿时长
6-12 weeks
期刊介绍: Theoretical Biology and Medical Modelling is an open access peer-reviewed journal adopting a broad definition of "biology" and focusing on theoretical ideas and models associated with developments in biology and medicine. Mathematicians, biologists and clinicians of various specialisms, philosophers and historians of science are all contributing to the emergence of novel concepts in an age of systems biology, bioinformatics and computer modelling. This is the field in which Theoretical Biology and Medical Modelling operates. We welcome submissions that are technically sound and offering either improved understanding in biology and medicine or progress in theory or method.
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