In this paper, a novel strategy in the application of the parallel factor analysis (PARAFAC) to a four-way voltammetric dataset was improved to evidence the interaction of etoposide (ETO) and calf thymus deoxyribonucleic acid (DNA) to determine the ETO-DNA binding constant. PARAFAC is one of the most commonly used techniques applicable to the decomposition of higher-order data arrays to focus on features of interest and provides a different resolution of the chemical problem of interest. Under optimized conditions, peak current data of a seven-sample set containing DNA in the range of 2.0-90.0 µM in the presence of ETO at a constant concentration (10 µM) at five different pHs were recorded as a function of potential and frequency and then arranged as a four-dimensional array. The characteristic curves of ETO and ETO-DNA complex were monitored from the potential, frequency, pH, and DNA concentration profiles obtained by PARAFAC decomposition of the fourth-order array. The binding constant, which is one of the principal parameters for the estimation of drug-DNA interaction and mechanism, was computed from the DNA concentration profile. The consequence of drug-DNA binding constant (K = 1.26 × 106) indicated that there was a significant interaction between ETO and DNA with the intercalation mechanism.

中文翻译：

---

伏安法四向数据集的四向平行因子分析，用于监测依托泊苷与DNA的相互作用及其结合常数。

本文改进了将平行因素分析（PARAFAC）应用于四向伏安数据集的新策略，以证明依托泊苷（ETO）和小牛胸腺脱氧核糖核酸（DNA）相互作用来确定ETO-DNA结合常数。PARAFAC是适用于分解高阶数据数组以关注目标特征的最常用技术之一，并为目标化学问题提供了不同的解决方案。在优化条件下，记录了七个样品组的峰值电流数据，该样品在五个不同pH值的恒定浓度（10 µM）的ETO存在下在2.0-90.0 µM范围内的DNA随电位和频率的变化而变化，然后排列为四维数组。从通过四阶阵列的PARAFAC分解获得的电势，频率，pH和DNA浓度曲线监测ETO和ETO-DNA复合物的特征曲线。从DNA浓度曲线计算出结合常数，该常数是用于估计药物-DNA相互作用和机理的主要参数之一。药物-DNA结合常数（K = 1.26×106）的结果表明，ETO和DNA之间存在显着的相互作用，并具有嵌入机制。