COMPUTER ANALYSIS OF AMINO ACID AND NUCLEOTIDE SEQUENCES

氨基酸和核苷酸序列的计算机分析

• 批准号: 6554461
• 负责人: JOHN C. 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/6554461
• 关键词: artificial intelligence; computer assisted sequence analysis; computer system design /evaluation; nucleic acid repetitive sequence; nucleic acid sequence; protein sequence; statistics /biometry

The goal of this project is to define and analyze, using computational methods, segments of protein and nucleotide sequences showing compositional bias (low-complexity regions or domains) and to understand their structural, functional and evolutionary significance, and their pathology. In protein sequences, these regions comprise a large proportion of the genome encoded amino acids (approximately 25% in most eukaryotes,and most of the translated protein sequences contain at least one such region). They may contain homopolymeric tracts or mosaics of a few amino acids, or repeated patterns, frequently subtle, including those typical of many non-globular domains. New mathematical definitions and algorithms are continuing to be developed to make unbiased identification of low-complexity segments, and to discover and analyze properties of these regions relevant to their structures, interactions and biological functions. 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. Structural data indicate that low complexity segments of proteins are generally non-globular or conformationally mobile. However, knowledge of the molecular structures and dynamics of these domains is still very limited because they are generally relatively intractable to investigation by crystallography and NMR, and they account for less than 1% of the residues in current structural databases. Hence, mathematically rigorous sequence analysis provides a primary methodology for gaining insights into their biology, and for raising questions to be investigated expermentally. These methods are also valuable, for both nucleotide and amino acid sequences, in detecting and eliminating some artifacts in sequence database searches and alignment analysis.

该项目的目标是使用计算方法来定义和分析蛋白质和核苷酸序列中表现出组成偏差的片段（低复杂性区域或结构域），并了解它们的结构，功能和进化意义，以及它们的生物学特性。 病理在蛋白质序列中，这些区域包含大部分基因组编码的氨基酸（在大多数真核生物中约为25%，并且大多数翻译的蛋白质序列包含至少一个这样的区域）。它们可能含有几个氨基酸的均聚物片段或镶嵌物，或重复的模式，通常是微妙的，包括许多非球形结构域的典型模式。新的数学定义和算法正在继续开发，以无偏地识别低复杂度的片段，并发现和 分析这些区域的结构、相互作用和生物学特性 功能协调发展的 散布的低复杂性序列在许多真核蛋白中特别丰富，这些蛋白在形态发生和胚胎发育、RNA加工、转录调节、信号转导以及细胞和细胞外结构完整性方面至关重要。 结构数据表明，蛋白质的低复杂性区段通常是非球形的或构象移动的。然而，这些域的分子结构和动力学的知识仍然非常有限，因为它们通常相对难以通过晶体学和NMR进行调查，并且它们在当前结构数据库中占不到1%的残基。因此，数学上严格的序列分析提供了一个主要的方法，以获得深入了解他们的生物学，并提出问题进行实验研究。对于核苷酸和氨基酸序列，这些方法在检测和消除序列数据库搜索中的一些伪像方面也是有价值的， 对准分析。