Toxic Constituents Index: A Toxicity-Calibrated Quantitative Evaluation Approach for the Precise Toxicity Prediction of the Hypertoxic Phytomedicine-Aconite

Front Pharmacol. 2016 Jun 17:7:164. doi: 10.3389/fphar.2016.00164. eCollection 2016.

Abstract

Complex chemical composition is an important reason for restricting herbal quality evaluation. Despite the multi-components determination method significantly promoted the progress of herbal quality evaluation, however, which mainly concerned the total amount of multiple components and ignored the activity variation between each one, and did not accurately reflect the biological activity of botanical medicines. In this manuscript, we proposed a toxicity calibrated contents determination method for hyper toxic aconite, called toxic constituents index (TCI). Initially, we determined the minimum lethal dose value of mesaconitine (MA), aconitine (AC), and hypaconitine (HA), and established the equation TCI = 100 × (0.3387 ×X MA + 0.4778 ×X AC + 0.1835 ×X HA). Then, 10 batches of aconite were selected and their evaluation results of toxic potency (TP), diester diterpenoid alkaloids (DDAs), and TCI were compared. Linear regression analysis result suggested that the relevance between TCI and TP was the highest and the correlation coefficient R was 0.954. Prediction error values study also indicated that the evaluation results of TCI was highly consistent with that of TP. Moreover, TCI and DDAs were both applied to evaluate 14 batches of aconite samples oriented different origins; from the different evaluation results, we found when the proportion of HA was reached 25% in DDAs, the pharmacopeia method could generate false positive results. All these results testified the accuracy and universality of TCI method. We believe that this study method is rather accurate, simple, and easy operation and it will be of great utility in studies of other foods and herbs.

Keywords: aconite; multi-components determination; toxic constituents index; toxic potency; toxicity calibration coefficient; toxicity prediction.