COMPUTER ANALYSIS OF LOW-COMPLEXITY AMINO ACID AND NUCLEOTIDE SEQUENCES

低复杂性氨基酸和核苷酸序列的计算机分析

• 批准号: 5203621
• 负责人: J WOOTTON
• 金额: --
• 依托单位: NATIONAL LIBRARY OF MEDICINE
• 依托单位国家: 美国
• 资助国家: 美国
• 起止时间: 至
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/5203621
• 关键词: automated data processing; chemical information system; computer assisted sequence analysis; computer program /software; computer system design /evaluation; method development; nucleic acid sequence; protein sequence; protein structure function; statistics /biometry

The goal of this project is to define, classify and analyze, using computational analysis, segments of protein and nucleotide sequences showing compositional bias or improbably low compositional complexity. In protein sequences, these include the abundant residue clusters of predominantly one or a few amino acid types, which commonly contain homopolymeric tracts or mosaics of these, aperiodic patterns and sections of low-period repeats. Other common examples include long non-globular domains. The abundance of biased segments in both amino acid and nucleotide sequence databases has been determined, and their properties are being related to evidence of biological functions. A. Methods: Different formal definitions of local compositional complexity were used to make unbiased identification of low-complexity segments, at different levels of stringency. Algorithms were refined to (a) select segments for further study, (b) filter out non-informative segments prior to database searches, and (c) discover and analyze regions in which compositional bias is present in periodically-spaced rather than contiguous residues. New methods for automated classification and neighboring of low- complexity sequences have been developed. B. Abundance and biological properties: Approximately 25% of the residues in protein databases are in compositionally biased segments (including some known long non- globular regions) and approximately 55% of proteins contain one or more such segments. Interspersed low-complexity sequences are particularly abundant in many eukaryotic proteins crucial in morphogenesis and embryonic development, RNA processing, transcriptional regulation, signal transduction and aspects of cellular and extracellular structural integrity. The limited structural information available for low- complexity regions of proteins indicates that they are generally non- globular and polymorphic kr mobile. Significance of project: The project is highlighting the high abundance and biological importance of low-complexity protein segments. Knowledge of their molecular structure and dynamics is beginning to emerge in a few cases, but these are a minority. This is a priority area for future research. The methods recently developed to analyze nucleotide sequences are revealing many new and intricate compositional features. These methods are valuable in eliminating many artefacts in sequence database searches and alignment analysis.

该项目的目标是定义、分类和分析，使用 蛋白质和核苷酸序列片段的计算分析 表现出成分上的偏见或不太可能的低成分复杂性。 在蛋白质序列中，这些包括丰富的残基簇 主要是一种或几种氨基酸，通常含有 这些非周期性图案和切片的均聚束或马赛克 低峰期的重复。其他常见的例子包括长的非球形的 域名。氨基酸和氨基酸中有偏向片段的丰度 核苷酸序列数据库已经确定，它们的性质 与生物功能的证据有关。A.方法： 使用了不同的局部成分复杂性的形式定义 为了对低复杂性分段进行无偏识别，在不同的 严格程度。算法被改进为(A)选择分段用于 进一步研究，(B)在数据库之前过滤掉非信息性部分 搜索，以及(C)发现和分析组成成分的区域 偏置存在于周期性间隔的残基中，而不是连续的残基中。 一种新的低气压自动分类及其邻域方法 已经开发出复杂性序列。B.丰富性和生物学 性质：蛋白质数据库中约25%的残基是 在成分偏向的片段中(包括一些已知的长的非 球状区域)，约55%的蛋白质含有一种或多种 这样的片断。散布的低复杂度序列尤其是 富含许多在形态发生和发育过程中起关键作用的真核蛋白质 胚胎发育、RNA加工、转录调控、信号 细胞和细胞外结构的转导与研究 正直。Low-Low可获得的有限结构信息- 蛋白质的复杂区域表明它们通常是非 球状和多态的KR移动。项目的意义： 该项目正在突出高丰度和生物重要性 低复杂性蛋白质片段。关于它们的分子结构的知识 在一些情况下，动态开始显现，但这些是一个 少数族裔。这是未来研究的优先领域。这些方法 最近发展起来的核苷酸序列分析揭示了许多新的 和错综复杂的成分特征。这些方法在以下方面很有价值 消除序列数据库搜索和比对中的许多伪影 分析。