Defining and computing optimum RMSD for gapped and weighted multiple-structure alignment.
Defining and computing optimum RMSD for gapped and weighted multiple-structure alignment.
复制标题
定义和计算带间隙和加权多结构比对的最佳 RMSD。
DOI：
10.1109/tcbb.2008.92
复制
发表时间：
2008
期刊：
影响因子：
--
通讯作者：
Snoeyink,Jack
中科院分区：
文献类型：
--
作者：
Wang,Xueyi;Snoeyink,Jack
成对结构比对通常使用均方根偏差（RMSD）来衡量结构相似性，并且已经建立了优化RMSD的方法。我们扩展RMSD加权RMSD多个结构。通过使用乘法权重，我们表明，加权RMSD的所有对是相同的加权RMSD的平均结构。因此，使用RMSD或加权RMSD意味着平均值是一个共识结构。虽然我们表明，在一般情况下，找到最佳的平移和旋转加权RMSD最小化的两个任务不能分开的多个结构一样，他们可以对，一个固有的困难和以前的工作忽略的事实，我们开发了一个近线性迭代算法收敛加权RMSD到局部最小值。对来自HOMSTRAD的23个蛋白质家族中的每一个进行了10，000次空位比对实验（其中每个结构都以随机平移和旋转开始），并迅速收敛到相同的最小值。最后，我们提出了一种启发式的方法来迭代地消除离群值的影响，并找到良好的对齐的位置，确定结构保守区的建模B-因子和偏离的平均位置的权重和迭代分配更高的权重，以更好地对齐原子。
Pairwise structure alignment commonly uses root mean square deviation (RMSD) to measure the structural similarity, and methods for optimizing RMSD are well established. We extend RMSD to weighted RMSD for multiple structures. By using multiplicative weights, we show that weighted RMSD for all pairs is the same as weighted RMSD to an average of the structures. Thus, using RMSD or weighted RMSD implies that the average is a consensus structure. Although we show that in general, the two tasks of finding the optimal translations and rotations for minimizing weighted RMSD cannot be separated for multiple structures like they can for pairs, an inherent difficulty and a fact ignored by previous work, we develop a near-linear iterative algorithm to converge weighted RMSD to a local minimum. 10,000 experiments of gapped alignment done on each of 23 protein families from HOMSTRAD (where each structure starts with a random translation and rotation) converge rapidly to the same minimum. Finally we propose a heuristic method to iteratively remove the effect of outliers and find well-aligned positions that determine the structural conserved region by modeling B-factors and deviations from the average positions as weights and iteratively assigning higher weights to better aligned atoms.