文献类型：期刊文献

英文题名：A novel, customizable and optimizable parameter method using spherical harmonics for molecular shape similarity comparisons

作者：Cai, Chaoqian[1];Gong, Jiayu[1];Liu, Xiaofeng[2];Jiang, Hualiang[2];Gao, Daqi[1];Li, Honglin[2]

机构：[1]E China Univ Sci & Technol, Sch Informat Sci & Engn, Shanghai 200237, Peoples R China;[2]E China Univ Sci & Technol, Sch Pharm, Shanghai Key Lab Chem Biol, State Key Lab Bioreactor Engn, Shanghai 200237, Peoples R China

年份：2012

卷号：18

期号：4

起止页码：1597

外文期刊名：JOURNAL OF MOLECULAR MODELING

收录：;WOS:【SCI-EXPANDED(收录号:WOS:000303540700033)】；

基金：This work was supported by the Special Fund for Major State Basic Research Project (grant 2009CB918501), the National Natural Science Foundation of China (grants 20803022), the Shanghai Committee of Science and Technology (grants 09dZ1975700 and 10431902600), the 863 Hi-Tech Program of China (grant 2007AA02Z304), and the Major National Scientific and Technological Project of China (grant 2009ZX09501-001). H. L. is also sponsored by Shanghai Rising-Star Program (grant 10QA1401800) and the Fundamental Research Funds for the Central Universities. The program and test sets of SHeMS are available from H. L. upon request.

语种：英文

外文关键词：Molecular shape; Similarity comparison; Spherical harmonic; Genetic optimization; Virtual screening

摘要：A novel molecular shape similarity comparison method, namely SHeMS, derived from spherical harmonic (SH) expansion, is presented in this study. Through weight optimization using genetic algorithms for a customized reference set, the optimal combination of weights for the translationally and rotationally invariant (TRI) SH shape descriptor, which can specifically and effectively distinguish overall and detailed shape features according to the molecular surface, is obtained for each molecule. This method features two key aspects: firstly, the SH expansion coefficients from different bands are weighted to calculate similarity, leading to a distinct contribution of overall and detailed features to the final score, and thus can be better tailored for each specific system under consideration. Secondly, the reference set for optimization can be totally configured by the user, which produces great flexibility, allowing system-specific and customized comparisons. The directory of useful decoys (DUD) database was adopted to validate and test our method, and principal component analysis (PCA) reveals that SH descriptors for shape comparison preserve sufficient information to separate actives from decoys. The results of virtual screening indicate that the proposed method based on optimal SH descriptor weight combinations represents a great improvement in performance over original SH (OSH) and ultra-fast shape recognition (USR) methods, and is comparable to many other popular methods. Through combining efficient shape similarity comparison with SH expansion method, and other aspects such as chemical and pharmacophore features, SHeMS can play a significant role in this field and can be applied practically to virtual screening by means of similarity comparison with 3D shapes of known active compounds or the binding pockets of target proteins.