The Ohio State University, Columbus.
IEEE/ACM Trans Comput Biol Bioinform. 2012 Jan-Feb;9(1):249-61. doi: 10.1109/TCBB.2011.67. Epub 2011 Mar 30.
Availability of an effective tool for protein multiple structural alignment (MSTA) is essential for discovery and analysis of biologically significant structural motifs that can help solve functional annotation and drug design problems. Existing MSTA methods collect residue correspondences mostly through pairwise comparison of consecutive fragments, which can lead to suboptimal alignments, especially when the similarity among the proteins is low. We introduce a novel strategy based on: building a contact-window based motif library from the protein structural data, discovery and extension of common alignment seeds from this library, and optimal superimposition of multiple structures according to these alignment seeds by an enhanced partial order curve comparison method. The ability of our strategy to detect multiple correspondences simultaneously, to catch alignments globally, and to support flexible alignments, endorse a sensitive and robust automated algorithm that can expose similarities among protein structures even under low similarity conditions. Our method yields better alignment results compared to other popular MSTA methods, on several protein structure data sets that span various structural folds and represent different protein similarity levels. A web-based alignment tool, a downloadable executable, and detailed alignment results for the data sets used here are available at http://sacan.biomed. drexel.edu/Smolign and http://bio.cse.ohio-state.edu/Smolign.
有效的蛋白质多重结构比对（MSTA）工具对于发现和分析具有生物学意义的结构基序至关重要，这些基序可以帮助解决功能注释和药物设计问题。现有的 MSTA 方法主要通过连续片段的两两比较来收集残基对应关系，这可能导致次优的比对，特别是当蛋白质之间的相似度较低时。我们引入了一种新的策略，该策略基于：从蛋白质结构数据中构建基于接触窗口的基序库，从该库中发现和扩展常见的对齐种子，以及根据这些对齐种子通过增强的部分顺序曲线比较方法对多个结构进行最佳叠加。我们的策略能够同时检测多个对应关系、全局捕捉对齐关系以及支持灵活的对齐关系，这证明了我们的算法具有敏感性和稳健性，即使在相似度较低的情况下，也能够揭示蛋白质结构之间的相似性。与其他流行的 MSTA 方法相比，我们的方法在跨越各种结构折叠并代表不同蛋白质相似度水平的几个蛋白质结构数据集上产生了更好的对齐结果。一个基于网络的对齐工具、一个可下载的可执行文件以及此处使用的数据集的详细对齐结果可在 http://sacan.biomed. drexel.edu/Smolign 和 http://bio.cse.ohio-state.edu/Smolign 上获得。
