Center for Drug Delivery System, Shanghai Institute of Materia Medica, State Key Laboratory of Drug Research, Chinese Academy of Sciences, Shanghai, China.
Eur J Pharm Sci. 2011 Jan 18;42(1-2):55-64. doi: 10.1016/j.ejps.2010.10.006. Epub 2010 Oct 25.
Cyclodextrin inclusion complexation technique is the key method to enhance the solubility and absorption of poorly soluble drugs in the early development stage, and thus it is essential to predict the binding constant between drug molecules and cyclodextrin. Structure-based in silico model was constructed for a data set of 86 poorly soluble drugs and used to profile the binding constant of drug-β-cyclodextrin inclusion complex. The stepwise regression was employed to select the optimum subset of the independent variables. The in silico model was built by the multiple linear regression method and validated by the residual analysis, the normal Probability-Probability plot and Williams plot. For the entire data set, the R(2) and Q(2) of the model were 0.78 and 0.67, respectively. The results indicated that the fitted model is robust, stable and satisfies all the prerequisites of the regression models. The chemical space position and important contributors were compared between selected drug molecules and organic compounds available in the literature. It was suggested that the binding behavior of drug molecules with β-CD should differ from that of the common organic compounds. Focusing on structurally diverse drugs, the in silico model can be used as an efficient tool to rapidly screen the drug-β-cyclodextrin inclusion complex stability and to rationally design the new drug delivery system of poorly soluble drugs.
环糊精包合技术是提高早期开发阶段难溶性药物溶解度和吸收度的关键方法，因此预测药物分子与环糊精之间的结合常数至关重要。本文构建了一个包含 86 个难溶性药物的基于结构的计算模型，用于描述药物-β-环糊精包合物的结合常数。采用逐步回归法选择最佳的自变量子集。通过多元线性回归方法建立了计算模型，并通过残差分析、正态概率-概率图和 Williams 图进行了验证。对于整个数据集，模型的 R(2)和 Q(2)分别为 0.78 和 0.67。结果表明，拟合模型稳健、稳定，满足回归模型的所有前提条件。比较了所选药物分子与文献中常见有机化合物的化学空间位置和重要贡献者。结果表明，药物分子与β-CD 的结合行为应不同于常见的有机化合物。该计算模型专注于结构多样化的药物，可以作为一种快速筛选难溶性药物-β-环糊精包合物稳定性的有效工具，并合理设计新的难溶性药物给药系统。
