Computer Analysis Of Low-complexity Amino Acid And Nucleotide Sequences

这个项目的目标是定义和分析显示出组成偏见的蛋白质和核苷酸序列片段，并了解它们的结构、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或内在非结构区域，重复序列，以及更广泛分布的氨基酸含量偏向。后者可以反映基因组水平的定向突变压力和特定于蛋白质或结构域功能的约束。低复杂性区域包括很大比例的基因组编码的氨基酸，并可能包含少数氨基酸的同质多聚区或嵌合体，或者经常微妙的重复模式，包括那些典型的许多非球状结构域和蛋白质的动态或内在非结构片段。已经开发了数学定义和算法来定义和识别成分偏向区域，并发现和分析与其结构、相互作用和进化相关的这些区域的属性。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某些伪影方面也是有价值的。由富含AT或GC的基因组编码的蛋白质显示出强烈的背景偏差，其中包括几种重要的传染病生物体的基因组，这给序列比对算法带来了问题。低复杂性和简单重复氨基酸序列的局部区域存在于许多蛋白质中，涉及细胞分化和胚胎发育、RNA加工、转录调控、信号转导以及细胞和细胞外结构完整性等方面。实验数据表明，低复杂性的蛋白质片段通常是非球形的、本质上无结构的或构象可移动的：然而，对这些结构域的分子结构和动力学的了解仍然非常有限。它们一般较难通过结晶学和核磁共振进行研究，在目前的结构数据库中仍占不到1%的残基。此外，目前基于分子力学和动力学的结构预测方法在应用于低复杂性氨基酸序列时给出了不一致的结果。因此，我们正在进行从头算量子化学方法的实验，以研究这些蛋白质区域可获得的构象状态系综。再加上可用的高分辨率结构和生物物理数据的数量有限，这种方法开始为进一步的实验提出更多的焦点问题。我们目前正在调查作为疟疾疫苗成分进行试验的重复结构域。

The goal of this project is to define and analyze 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 and dynamic or intrinsically unstructured segments of proteins. Mathematical definitions and algorithms have been developed to define and identify regions of compositional bias, and to discover and analyze properties of these regions relevant to their structures, interactions, and evolution. 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. 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, raising problems for sequence alignment algorithms. Local regions of low complexity and tandemly repeated amino acid sequences 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 still account for less than 1% of the residues in current structural databases. Moreover, current structure prediction methods based on molecular mechanics and dynamics have given inconsistent results when applied to low-complexity amino acid sequences. Accordingly, we are experimenting with ab initio quantum chemical methods to investigate the ensembles of conformational states accessible to these regions of proteins. Together with the limited amount of available high-resolution structural and biophysical data, this approach is starting to raise more focussed questions for further experiments. We are currently investigating repeated domains that are under trial as components of malaria vaccines.