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.

这个项目的目标是定义，分类和分析，使用 计算分析，蛋白质片段和核苷酸序列 表现出成分偏差或成分复杂性低得不可能。 在蛋白质序列中，这些包括大量的 主要是一种或几种氨基酸类型，其通常含有 这些的均聚物束或镶嵌物、非周期性图案和截面 低周期重复。 其他常见的例子包括长非球形 域. 在氨基酸和氨基酸序列中， 核苷酸序列数据库已经确定，其性质 与生物功能的证据有关。 A.研究方法： 对局部成分复杂性采用了不同的形式化定义 为了在不同的时间点对低复杂度的片段进行无偏识别， 严格程度。 算法进行了改进，以（a）选择片段， 进一步研究，（B）在数据库之前过滤掉非信息段 搜索，以及（c）发现和分析其中组成 偏倚存在于相邻间隔的残基中而不是相邻的残基中。 一种新的低密度土壤自动分类和邻区处理方法 复杂性序列已经被开发出来。 B。abstract和生物 性质：蛋白质数据库中大约25%的残基是 在成分偏向的片段（包括一些已知的长的非- 大约55%的蛋白质含有一个或多个 这样的片段。 散布的低复杂度序列特别适合于 在许多真核生物的蛋白质中含量丰富， 胚胎发育，RNA加工，转录调控，信号 细胞和细胞外结构的转导和方面 完整 有限的结构信息可用于低- 蛋白质的复杂性区域表明它们通常是非- 球形和多形态kr移动的。 项目意义： 该项目强调了高丰度和生物重要性， 低复杂性蛋白质片段。 了解它们的分子结构 动力学开始在少数情况下出现，但这些都是 少数 这是未来研究的优先领域。 的方法 最近开发的用于分析核苷酸序列的技术揭示了许多新的 和复杂的组成特征。 这些方法在以下方面很有价值： 消除了序列数据库搜索和比对中的许多假象 分析.