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Considering atomic property vector and atomic correlative function, the 3-dimensional structural vector of atomic property correlation (3D-VAPC), a novel descriptor, is defined to characterize a 3-dimensional molecular structure by introducing self-adaptability regulation mechanism and the idea of orientating to customers. Characterizing the structures of 25 bisphenol A compounds by this vector, the QSAR models of three kinds of estrogen activities (ER affinities, gene induction and cell proliferation) have high multiple correlation coefficient (Rcum2 = 0.933, 0.813, 0.959) and cross verification coefficient (Qcum2 = 0.847, 0.953, 0.798) by support vector machine (SVM), which suits for nonlinear circumstances. The above results show that the models successfully express the correlation between structure and three kinds of estrogen activities. Therefore, 3D-VAPC exactly reflects the molecular structural information and SVM method correctly describes the correlation between information and property of the compounds.
Considering atomic property vector and atomic correlative function, the 3-dimensional structural vector of atomic property correlation (3D-VAPC), a novel descriptor, is defined to characterize a 3-dimensional molecular structure by introducing self-adaptability regulation mechanism and the idea of Characterizing the structures of 25 bisphenol A compounds by this vector, the QSAR models of three kinds of estrogen activities (ER affinities, gene induction and cell proliferation) have high multiple correlation coefficient (Rcum2 = 0.933, 0.813, 0.959) and The above results show that the models successfully express the correlation between the structures and three kinds of estrogen activities. Thus, the 3D-cross verification coefficient (Qcum2 = 0.847, 0.953, 0.798) by support vector machine VAPC exactly reflects the molecular structural information and SVM method correctly describes the correlation between information an d property of the compounds.