Temelso Berhane, Mabey Joel M, Kubota Toshiro, Appiah-Padi Nana, Shields George C
Dean's Office, College of Arts and Sciences, and Department of Chemistry, Bucknell University , Lewisburg, Pennsylvania 17837, United States.
Department of Mathematical Sciences, Susquehanna University , Selinsgrove, Pennsylvania 17870, United States.
J Chem Inf Model. 2017 May 22;57(5):1045-1054. doi: 10.1021/acs.jcim.6b00546. Epub 2017 May 3.
When assessing the similarity between two isomers whose atoms are ordered identically, one typically translates and rotates their Cartesian coordinates for best alignment and computes the pairwise root-mean-square distance (RMSD). However, if the atoms are ordered differently or the molecular axes are switched, it is necessary to find the best ordering of the atoms and check for optimal axes before calculating a meaningful pairwise RMSD. The factorial scaling of finding the best ordering by looking at all permutations is too expensive for any system with more than ten atoms. We report use of the Kuhn-Munkres matching algorithm to reduce the cost of finding the best ordering from factorial to polynomial scaling. That allows the application of this scheme to any arbitrary system efficiently. Its performance is demonstrated for a range of molecular clusters as well as rigid systems. The largely standalone tool is freely available for download and distribution under the GNU General Public License v3.0 (GNU_GPL_v3) agreement. An online implementation is also provided via a web server ( http://www.arbalign.org ) for convenient use.
在评估两个原子顺序相同的异构体之间的相似性时,通常会平移和旋转它们的笛卡尔坐标以实现最佳对齐,并计算成对均方根距离(RMSD)。然而,如果原子顺序不同或分子轴被切换,则有必要在计算有意义的成对RMSD之前找到原子的最佳排序并检查最佳轴。通过查看所有排列来找到最佳排序的阶乘缩放对于任何原子数超过十个的系统来说成本都太高了。我们报告了使用库恩 - 蒙克雷斯匹配算法将找到最佳排序的成本从阶乘缩放降低到多项式缩放。这使得该方案能够有效地应用于任何任意系统。它在一系列分子簇以及刚性系统上的性能得到了证明。这个基本独立的工具可根据GNU通用公共许可证v3.0(GNU_GPL_v3)协议免费下载和分发。还通过网络服务器(http://www.arbalign.org)提供了在线实现,以便于使用。