使用最大公共边子图算法进行化学图相似性搜索的启发式方法。

Heuristics for similarity searching of chemical graphs using a maximum common edge subgraph algorithm.

作者信息

Raymond John W, Gardiner Eleanor J, Willett Peter

机构信息

Pfizer Global Research and Development, Ann Arbor Laboratories, Michigan 48105, USA.

出版信息

J Chem Inf Comput Sci. 2002 Mar-Apr;42(2):305-16. doi: 10.1021/ci010381f.

DOI:10.1021/ci010381f

PMID:11911700

Abstract

Recently a method (RASCAL) for determining graph similarity using a maximum common edge subgraph algorithm has been proposed which has proven to be very efficient when used to calculate the relative similarity of chemical structures represented as graphs. This paper describes heuristics which simplify a RASCAL similarity calculation by taking advantage of certain properties specific to chemical graph representations of molecular structure. These heuristics are shown experimentally to increase the efficiency of the algorithm, especially at more distant values of chemical graph similarity.

摘要

最近，一种使用最大公共边子图算法来确定图形相似度的方法（RASCAL）被提出来了，该方法在用于计算以图形表示的化学结构的相对相似度时已被证明非常有效。本文描述了一些启发式方法，这些方法利用分子结构的化学图形表示所特有的某些属性来简化RASCAL相似度计算。实验表明，这些启发式方法提高了算法的效率，特别是在化学图形相似度较远的值时。