Zhao Yang, Hayashida Morihiro, Jindalertudomdee Jira, Nagamochi Hiroshi, Akutsu Tatsuya
Bioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho, Uji, Kyoto 6110011, Japan.
J Bioinform Comput Biol. 2013 Dec;11(6):1343007. doi: 10.1142/S0219720013430075. Epub 2013 Nov 21.
Molecular enumeration plays a basic role in the design of drugs, which has been studied by mathematicians, computer scientists, and chemists for quite a long time. Although many researchers are involved in developing enumeration algorithms specific to drug design systems, molecular enumeration is still a hard problem to date due to its exponentially increasing large search space with larger number of atoms. To alleviate this defect, we propose efficient algorithms, BfsSimEnum and BfsMulEnum to enumerate tree-like molecules without and with multiple bonds, respectively, where chemical compounds are represented as molecular graphs. In order to reduce the large search space, we adjust some important concepts such as left-heavy, center-rooted, and normal form to molecular tree graphs. Different from many existing approaches, BfsSimEnum and BfsMulEnum firstly enumerate tree-like compounds by breadth-first search order. Computational experiments are performed to compare with several existing methods. The results suggest that our proposed methods are exact and more efficient.
分子枚举在药物设计中起着基础性作用,数学家、计算机科学家和化学家已经对其进行了长期研究。尽管许多研究人员致力于开发针对药物设计系统的枚举算法,但由于随着原子数量增加搜索空间呈指数级增长,分子枚举至今仍是一个难题。为了缓解这一缺陷,我们提出了高效算法BfsSimEnum和BfsMulEnum,分别用于枚举无多重键和有多重键的树状分子,其中化合物被表示为分子图。为了减少巨大的搜索空间,我们将一些重要概念如左重、中心根和范式调整应用于分子树图。与许多现有方法不同,BfsSimEnum和BfsMulEnum首先按广度优先搜索顺序枚举树状化合物。进行了计算实验以与几种现有方法进行比较。结果表明我们提出的方法准确且更高效。