Zhou Congyi, Nie Changming, Li Shan, Li Zhonghai
School of Chemistry and Chemical Engineering, Nanhua University, Hengyang, People's Republic of China 421001.
J Comput Chem. 2007 Nov 30;28(15):2413-23. doi: 10.1002/jcc.20540.
A novel semi-empirical topological descriptor Nt was proposed by revising the traditional distance matrix based on the equilibrium electronegativity and the relative bond length. Nt can not only efficiently distinguish structures of organic compounds containing multiple bonds and/or heteroatoms, but also possess good applications of QSPR/QSAR (quantitative structure-property/activity relationships) to a large diverse set of compounds, which are alkanes, alkenes, alkynes, aldehydes, ketones, thiols, and alkoxy silicon chlorides with all the correlation coefficients of the models over 0.99. The LOO CV (leave-one-out cross-validation) method was used to testify the stability and predictive ability of the models. The validation results verify the good stability and predictive ability of the models employing the cross-validation parameters: RCV, SEPCV and SCV, which demonstrate the wide potential of the Nt descriptor for applications to QSPR/QSAR.
通过基于平衡电负性和相对键长修正传统距离矩阵,提出了一种新型半经验拓扑描述符Nt。Nt不仅能够有效区分含有多重键和/或杂原子的有机化合物结构,而且在大量不同类型化合物(包括烷烃、烯烃、炔烃、醛、酮、硫醇和烷氧基硅氯)的定量结构-性质/活性关系(QSPR/QSAR)中具有良好应用,所有模型的相关系数均超过0.99。采用留一法交叉验证(LOO CV)方法来验证模型的稳定性和预测能力。验证结果证实了采用交叉验证参数RCV、SEPCV和SCV的模型具有良好的稳定性和预测能力,这表明Nt描述符在QSPR/QSAR应用中具有广泛潜力。