Student Research Committee, Faculty of Pharmacy, Tabriz University of Medical Sciences, Tabriz, Iran.
Biotechnology Research Center, Tabriz University of Medical Sciences, Tabriz, Iran.
Ann Pharm Fr. 2024 Jun;82(4):663-672. doi: 10.1016/j.pharma.2024.02.003. Epub 2024 Feb 8.
Many drug candidates fail to complete the entire drug development process because of poor physicochemical properties. Solubility is an important physicochemical property which plays a vital role in various stages of drug discovery and development. Several methods have been proposed to enhance the solubility of drugs, and complex formation with cyclodextrins is among them. Beta-cyclodextrin (βCD) is a common excipient for solubilization of drugs. The aim of this study is to develop the mechanistic QSPR models to predict the solubility enhancement of a drug in the presence of βCD. In this study, the solubility enhancement of some drugs in the presence of 10mM βCD at 25°C was experimentally determined or collected from the literature. Two different models to predict the solubilization by βCD were developed by binary logistic regression using structural properties of drugs with more than 80% accuracy. Polar surface area and excess molar refraction are the main parameters for estimating solubilization by βCD. Moreover, other descriptors related to hydrophobicity and the capability of hydrogen bonding formation of molecules could improve the accuracy of the established models.
由于较差的物理化学性质，许多候选药物无法完成整个药物开发过程。溶解度是一个重要的物理化学性质，在药物发现和开发的各个阶段都起着至关重要的作用。已经提出了几种提高药物溶解度的方法，其中包括与环糊精形成复合物。β-环糊精（βCD）是增溶药物的常用赋形剂。本研究旨在建立机制 QSPR 模型，以预测药物在βCD 存在下的溶解度增强。在这项研究中，通过实验测定或从文献中收集了一些药物在 25°C 下存在 10mMβCD 时的溶解度增强。使用药物的结构性质，通过二元逻辑回归建立了两种不同的模型来预测βCD 的增溶作用，准确率超过 80%。极性表面积和过量摩尔折射是估计βCD 增溶作用的主要参数。此外，与分子疏水性和氢键形成能力相关的其他描述符可以提高所建立模型的准确性。
