Citation: XIANG Yangyang, YU Huimin, DENG Haishan, CHEN Jingya, ZHANG Aihua, CHI Yumei, HAN Shuying. Prediction of n-octanol-water partition coefficients of hepatotoxicity/nephrotoxicity components in traditional herbs using quantitative structure-retention relationship models by high performance liquid chromatography[J]. Chinese Journal of Chromatography, ;2017, 35(4): 432-438. doi: 10.3724/SP.J.1123.2016.10044 shu

Prediction of n-octanol-water partition coefficients of hepatotoxicity/nephrotoxicity components in traditional herbs using quantitative structure-retention relationship models by high performance liquid chromatography

Nanjing University of Chinese Medicine, Nanjing 210046, China

Received Date: 22 October 2016

Fund Project: National Natural Science Foundation of China (No. 81303311)

A quantitative structure-retention relationship (QSRR) was proposed to determine n-octanol-water partition coefficients (K_ow) of aristolochic acid A, aristolochic acid B, aristololactam and resveratrol in this paper. Sixteen acidic and neutral benzene analogues with reliable experimental K_ow data were chosen as model compounds for establishing linear relationship between the apparent n-octanol-water partition coefficient (K_ow″) and retention factor of 100% aqueous phase (k_w), which corresponds to retention factors of solutes using neat aqueous fraction as mobile phase. Methanol-water mixture was used as mobile phase at various mobile phase pH, and retention time (t_R) was rectified by a dual-point retention time correction (DP-RTC). The established models were evaluated by internal and external validations, respectively. QSRR models had good correlation coefficients at different mobile phase pH with correlation coefficients (R²) ranged from 0.980 to 0.987. Both internal (the cross-validated correlation coefficients (R_cv²) of 0.982-0.988) and external (0.6% ≤ relative errors (RE)≤10.9% for all the six verification compounds) validations showed satisfactory results. K_ow values of four hepatotoxic/nephrotoxic ingredients in traditional herbs were predicted by QSRR, and compared with the ones obtained by shake-flask method (SFM) and calculated by software as well. The method provided a convenient and rapid way to obtain reliable K_ow data. In addition, the proposed protocol realized simultaneous prediction for K_ow values of structure-similar components in traditional herbs merely through retention times, thereupon solved the dilemma of K_ow measurement by SFM resulting from inaccessibility of separating single component from complex herbs. These K_ow data can be applied in toxicity prediction of components in traditional herbs through quantitative structure-activity relationships (QSARs) in a follow-up study.
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