FAMILY SPECIFIC ANALYSIS OF BETA BULGES & BETA TWIST IN BETA SANDWICH PROTEINS

蛋白质的折叠结构在不同的 层次：一级结构、二级结构、三级结构 四级结构。 Beta-Sheets由几股线组成， 必须列为三级结构元素。 天然存在 β-片层不是平坦的，而是显示出更强或更弱的 左旋旋转（沿沿着穿过股线的轴观察， 片）。 此外，氢键图案的不规则性， 所谓的“β-凸起”并不罕见。 今天有足够的 具有几个确定的3D结构的蛋白质家族， 分析描述扭转的几何参数， 同源蛋白质家族内的β凸起（即， 通过共同的祖先进化相关）。 的数据库 已知的“β-夹层”结构已经从可获得的 3D结构（Brookhaven数据库）。 我们目前正在分析， 编制各种几何参数（如股间和 股线内角度）来描述β-片层扭曲特性， 在夹层数据库结构中出现β-凸起。 我们将 首先使用数据来检查失真与 一个规则的片材（即具有恒定的平均扭曲参数）， 同源蛋白质对及其进化距离。 通过 几何数据与相应倍数的相关性 序列比对，这项研究的结果应该让我 开发新的化学方法来改善蛋白质结构预测， 氨基酸序列数据。 例如，许多常见的 在预测β链二级 由于对β-扭曲的认识不足， 片状结构中的β-凸起。 计算机图形实验室 资源提供了计算和可视化 在项目概述中测量的几何参数 以上，并进一步的手段来分析这些相关性 参数与原始序列数据。

The folded structure of a protein is described at different levels: primary structure, secondary structure, tertiary structure and quaternary structure. Beta-Sheets are made of several strands and must be listed as tertiary structural elements. Naturally found beta-sheets are not flat, but rather display stronger or weaker left-handed rotation (viewed along an axis lying across the strands in the sheet). Further, irregularities in the hydrogen-bonding pattern, so-called "beta-bulges", are not uncommon. There are today enough protein families with several determined 3D-structures to enable an analysis of geometrical parameters describing the twist and beta-bulges within families of homologous proteins (i.e. evolutionarily related through a common ancestor). A database of known "beta-sandwich" structures has been derived from the available 3D- structures (Brookhaven Data Base). We are currently analyzing and compiling various geometrical parameters (e.g. inter-strand and intra-strand angles) to describe the beta-sheet twist properties and occurring beta-bulges in the sandwich database structures. We will use the data first to examine the relation between the distortion from a regular sheet (i.e. with constant, average twist parameters) of pairs of homologous proteins and their evolutionary distance. By correlation of the geometrical data with the corresponding mu ltiple sequence alignments, the results of this study should allow me to develop new heuristics to improve protein structure prediction from amino acid sequence data. For example, many of the commonly encountered difficulties with predicting beta-strand secondary structure arise from insufficient knowledge about the beta-twist and beta-bulges in the sheet structures. The Computer Graphics Laboratory resources provide the means for computing and visualizing the geometrical parameters that are surveyed in the project outlined above, and further the means to analyze the correlation of these parameters with primary sequence data.