METHODS FOR COMPARISON OF PROTEIN THREE DIMENSIONAL STRUCTURE

我们已经开发了用于蛋白质三维比较的算法 结构。“大量”算法，用于“向量比对搜索工具”， 通过比较类型来快速确定子结构的相似性， 连通性和相对取向的二级结构元素。 工作集中在三个领域：1)界定门槛 相似性统计，2)灵敏度和特异度的验证，以及 3)制定逐个“最佳”残渣的统计标准 对齐。按偶发事件划分的巨大等级下层结构相似性 很有可能。这是作为以下概率的乘积计算的 独立的元素对叠加残差将被观察到 机会，通过参考基于以下公式的经验分布来确定 随机抽取结构数据库中的元素对。一个门槛 统计量作为最大子结构似然的乘积给出 以及可能的子结构选项的数量，由 包含离散元素个数的组合公式 在每种蛋白质中。如果值较小，则可将此值直接解释为 检验统计数据或p值是否具有显著的相似性。浩瀚一直是 通过对已知结构的全面分析进行了测试。敏感度 关于爆炸的“命中”是99.5%。测试用例中的专用性 这部文学作品看起来很完美，与现有的非 统计方法显示命中率较低，遗漏为低分 边际相似之处。残基-残基对齐现在被构建 通过Gibb的抽样方案，事实证明比Metropolis更有效 取样。评价了替代残基比对的意义 通过参考下列公式中叠加残差的经验分布 随机排列，以确定最令人惊讶的。一位分析家 经验随机元素自身比较的密度函数 残差被证明优于特定于子结构的零模型 重现文学专家的比对，另外速度更快。这个 这项工作的意义将是将地平线扩展到 可以通过使用结构来检测进化关系 用比较代替单独的序列比较。结果是 被生物学家作为“Entrez”中的“结构邻居”提供 浏览器。

We have developed algorithms for comparison of protein three dimensional structures. The "VAST" algorithm, for "vector alignment search tool," identifies substructures similarities rapidly by comparing the types, connectivity, and relative orientations secondary structure elements. Work has focused in three areas: 1) definition of the threshold similarity statistic, 2) validation of sensitivity and specificity, and 3) development of statistical criteria for "optimal" residue-by-residue alignment. VAST ranks substructure similarities by chance-occurrence likelihood. This is calculated as the product of the probabilities that independent element-pair superposition residuals would be observed by chance, as determined by reference to an empirical distribution based on random draws of element pairs in the structural database. A threshold statistic is given as the product of the greatest substructure likelihood and the number of possible substructure choices, as determined by a combinatorial formula involving the number of discrete elements present in each protein. If small, this value is interpretable directly as a test statistic or p-value for significant similarity. VAST has been tested by an all-against-all analysis of known structures. Sensitivity with respect to BLAST "hits" is 99.5%. Specificity in test cases from the literature appears perfect, and comparison to existing non- statistical methods indicates fewer hits, with omissions being low-score marginal similarities. Residue-residue alignments are now constructed by a Gibb's sampling scheme, which proved more efficient than Metropolis sampling. Significance of alternative residue alignments is evaluated by reference to an empirical distribution of superposition residuals in random alignments, to identify the most surprising one. An analytical density function fitted to empirical random-element self comparison residuals proved superior to a substructure-specific null model in reproducing literature expert alignments, and is in addition faster. The significance of this work will be in extending the horizon to which evolutionary relationship may be detected, by employing structure comparison in place of sequence comparison alone. The results have been made available to biologists as "structural neighbors" in the "Entrez" browser.