Structure-activity relationship study on the binding of PBDEs with thyroxine transport proteins.

Molecular docking and three-dimensional quantitative structure-activity relationships (3D-QSAR) were used to develop models to predict binding affinity of polybrominated diphenyl ether (PBDE) compounds to the human transthyretin (TTR). Based on the molecular conformations derived from the molecular docking, predictive comparative molecular similarity indices analysis (CoMSIA) models were developed. The results of CoMSIA models were as follows: leave-one-out (LOO) cross-validated squared coefficient q² (LOO) = 0.827 (full model, for all 28 compounds); q² (LOO) = 0.752 (split model, for 22 compounds in the training set); leave-many-out (LMO) cross-validated squared coefficient q² (LMO, two groups) = 0.723 ± 0.100 (full model, for all 28 compounds); q² (LMO, five groups) = 0.795 ± 0.030 (full model, for all 28 compounds); and the predictive squared correlation coefficient r²(pred) = 0.928 (for six compounds in the test set). The developed CoMSIA models can be used to infer the activities of compounds with similar structural characteristics. In addition, the interaction mechanism between hydroxylated polybrominated diphenyl ethers (HO-PBDEs) and the TTR was explored. Hydrogen bonding with amino acid residues Asp74, Ala29, and Asn27 may be an important determinant for HO-PBDEs binding to TTR. Among them, forming hydrogen bonds with amino acid residues Asp74 might exert a more important function.

Topological research on diamagnetic susceptibilities of organic compounds.

A novel molecular connectivity index, (m)chi('), based on the adjacency matrix of molecular graphs and novel atomic valence connectivities, delta(i)(') for predicting the molar diamagnetic susceptibilities of organic compounds is proposed. The delta(i)(') is defined as: delta(i)(') = delta(i)(nu) x Ei=12:625, where delta(i)(nu) and E(i) are the atomic valence connectivity and the valence orbital energy of atom i, respectively. A good QSPR model for molar diamagnetic susceptibilities can be constructed from (0)chi('), (1)chi('), (2)chi(') and (4)chi(p)(') using multivariate linear regression (MLR). The correlation coefficient r, standard error, and average absolute deviation of the MLR model are 0.9918, 5.56 cgs, and 4.26 cgs, respectively, for the 721 organic compounds tested (training set). Cross-validation using the leave-one-out method demonstrates that the MLR model is highly reliable statistically. Using the MLR model, the average absolute deviations of the predicted values of molar diamagnetic susceptibility of another 360 organic compounds (test set) is 4.34 cgs. 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 thus provides an acceptable model for the prediction of molar diamagnetic susceptibilities of organic compounds.