Berberine (BBR), isolated from a Chinese herb, is identified as a new cholesterol‐lowering small molecule, and hundreds of berberine derivatives have been obtained for optimization of their hypolipidemic activities in recent years. However, so far there is no available quantitative structure–activity relationship (QSAR) model used for the development of novel BBR analogues with hypolipidemic activities, mainly due to lack of lipid‐lowering molecular mechanisms and target identification of BBR. In this paper, the tactics using ligand efficiency indice instead of pIC₅₀ as the activity could be adopted for the development of BBR QSAR models. A series of 59 BBR derivatives with hypolipidemic activities have been studied and split randomly into three sets of training and test sets. Statistical quality of most building models shows obviously robust. Best calculated model that employs LLE indice as the activity (Model 6) has the following statistical parameters: for training set R² = .984, Q² = 0.981, RMSE = 0.1160, and for test set R² = .989, RMSE = 0.0067. This model would be used for the development of novel BBR analogues with lipid‐lowering activities as a hit discovery tool.

中文翻译：

---

具有降血脂活性的小ber碱衍生物的预测QSAR建模研究

从中草药中分离出的小ber碱（BBR）被确定为一种新的降低胆固醇的小分子，近年来已获得数百种小ber碱衍生物以优化其降血脂活性。但是，到目前为止，尚无可用于开发具有降血脂活性的新型BBR类似物的定量结构-活性关系（QSAR）模型，这主要是由于缺乏降脂分子机制和BBR的靶标鉴定。在本文中，使用配体效率指标代替pIC _50的策略因为该活动可用于开发BBR QSAR模型。研究了一系列具有降血脂活性的59种BBR衍生物，并将其随机分为三组训练和测试集。大多数建筑模型的统计质量显示出明显的稳健性。使用LLE指标作为活动的最佳计算模型（模型6）具有以下统计参数：对于训练集R ²  = .984，Q ²  = 0.981，RMSE = 0.1160，对于测试集R ²  = .989，RMSE = 0.0067。该模型将用于开发具有降脂活性的新型BBR类似物作为命中发现工具。