Computer Analysis of Low-complexity Amino Acid and Nucle

低复杂性氨基酸和核酸的计算机分析

• 批准号: 6988450
• 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/6988450
• 关键词: artificial intelligence; chemical models; computer assisted sequence analysis; computer system design /evaluation; conformation; nucleic acid repetitive sequence; nucleic acid sequence; protein sequence; statistics /biometry; structural biology

The goal of this project is to define and analyze, using computational methods, segments of protein and nucleotide sequences showing compositional bias and to understand their structural, functional and evolutionary significance, and their pathology. These sequences include local low complexity regions or domains, including conformationally mobile or intrinsically unstructured regions of proteins, tandemly-repeated sequences, and also more generally distributed amino acid content bias. The latter can reflect directional mutation pressures at the genomic level and constraints specific to protein or domain function. Low complexity regions comprise a large proportion of the genome-encoded amino acids, and 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 identify regions of compositional bias, and to discover and analyze properties of these regions relevant to their structures, interactions, biological functions, and evolution. Strong background bias is shown by proteins encoded by very AT-rich or GC-rich genomes, which include those of several important infectious disease organisms: these raise problems for sequence alignment algorithms which are being addressed. Local regions of low complexity and tandemly repeated amino acid sequecnes occur in many proteins involved in cellular differentiation and embryonic development, RNA processing, transcriptional regulation, signal transduction and aspects of cellular and extracellular structural integrity. Experimental data indicate that low complexity segments of proteins are generally non-globular, intrinsically unstructured, or conformationally mobile: however, knowledge of the molecular structures and dynamics of these domains is still very limited. 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.

该项目的目标是定义和分析，使用计算方法，蛋白质和核苷酸序列片段显示组成的偏见，并了解其结构，功能和进化意义，以及它们的病理学。这些序列包括局部低复杂性区域或结构域，包括蛋白质的构象移动的或固有非结构化区域、串联重复序列，以及更普遍分布的氨基酸含量偏差。后者可以反映基因组水平的定向突变压力和蛋白质或结构域功能的特定约束。低复杂性区域包含大比例的基因组编码的氨基酸，并且可以包含几个氨基酸的均聚物片段或镶嵌物，或重复的模式，通常是细微的，包括许多非球状结构域的典型模式。新的数学定义和算法正在继续发展，以确定区域的成分偏差，并发现和分析这些区域的相关属性，其结构，相互作用，生物功能和进化。强烈的背景偏见是由非常AT丰富或GC丰富的基因组，其中包括那些几个重要的传染病生物编码的蛋白质：这些序列比对算法正在解决的问题。低复杂性和串联重复氨基酸序列的局部区域存在于参与细胞分化和胚胎发育、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的许多蛋白质中。实验数据表明，蛋白质的低复杂性片段通常是非球形的，本质上是非结构化的，或构象移动的：然而，这些结构域的分子结构和动力学的知识仍然非常有限。它们通常相对难以通过晶体学和NMR进行研究，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和比对分析中的一些伪影方面也是有价值的。