Improved QSPR Study of Diamagnetic Susceptibilities for Organic Compounds Using Two Novel Molecular Connectivity Indexes

TLDR: In this paper, a multilinear regression (MLR) model was proposed for predicting the molar diamagnetic susceptibilities of organic compounds, where the optimal values of parameters x, a, and y included in definition of variable molecular connectivity indexmχ' and its converse index mχ'' were found by an optimization method.

Abstract: For predicting the molar diamagnetic susceptibilities of organic compounds, a variable molecular connectivity indexmχ' and its converse index mχ'' based on adjacency matrix of molecular graphs and the variable atomic valence connectivity index δi' were proposed. The optimal values of parameters x, a, and y included in definition of δi', mχ' and mχ'' can be found by an optimization method. When x2.9, a1.10, and y0.36, a good five-parameter model for the molar diamagnetic susceptibilities can be constructed from 0χ', 1χ', 2χ', 1χ'' and 2χ'' by using the best subset regression analysis method. The correlation coefficient r, standard error s, and average absolute deviation of the multilinear regression (MLR) model are 0.9930, 4.96 cgs, and 3.74 cgs, respectively, for the 721 organic compounds (training set). The cross-validation by using the leave-one-out method demonstrates that the MLR model is highly reliable from the point of view of statistics. The average absolute deviation of predicted values of the molar diamagnetic susceptibility of another 360 organic compounds (test set) is 4.37 cgs for the MLR model. The results show that the current method is more effective than literature methods for estimating the molar diamagnetic susceptibility of an organic compound. The MLR method can provide an acceptable model for the prediction of the molar diamagnetic susceptibilities of organic compounds.