Ghafourian Taravat, Barzegar-Jalali Mohammad, Dastmalchi Siavoush, Khavari-Khorasani Tina, Hakimiha Nasim, Nokhodchi Ali
Drug Design and Chemometrics Laboratory, Drug Applied Research Centre and School of Pharmacy, Tabriz University of Medical Sciences, Tabriz, Iran.
Int J Pharm. 2006 Aug 17;319(1-2):82-97. doi: 10.1016/j.ijpharm.2006.03.043. Epub 2006 Apr 7.
An estimate of volume of distribution (V(d)) is of paramount importance both in drug choice as well as maintenance and loading dose calculations in therapeutics. It can also be used in the prediction of drug biological half life. This study employs quantitative structure-pharmacokinetic relationship (QSPR) techniques for the prediction of volume of distribution. Values of V(d) for 129 drugs were collated from the literature. Structural descriptors consisted of partitioning, quantum mechanical, molecular mechanical, and connectivity parameters calculated by specialized software and pK(a) values obtained from ACD labs/log D database. Genetic algorithm and stepwise regression analyses were used for variable selection and model development. Models were validated using a leave-many-out procedure. QSPR analyses resulted in a number of significant models for acidic and basic drugs separately, and for all the drugs. Validation studies showed that mean fold error of predictions for the selected models were between 1.79 and 2.17. Although separate QSPR models for acids and bases resulted in lower prediction errors than models for all the drugs, the external validation study showed a limited applicability for the equation obtained for acids. Therefore, the universal model that requires only calculated structural descriptors was recommended. The QSPR model is able to predict the volume of distribution of drugs belonging to different chemical classes with a prediction error similar to that of the other more complicated prediction methods including the commonly practiced interspecies scaling. The structural descriptors in the model can be interpreted based on the known mechanisms of distribution and the molecular structures of the drugs.
分布容积（V(d)）的估算在药物选择以及治疗中的维持剂量和负荷剂量计算方面都至关重要。它还可用于预测药物的生物半衰期。本研究采用定量构效关系（QSPR）技术来预测分布容积。从文献中整理出了129种药物的V(d)值。结构描述符包括通过专门软件计算的分配、量子力学、分子力学和连接性参数，以及从ACD labs/log D数据库获得的pK(a)值。使用遗传算法和逐步回归分析进行变量选择和模型开发。采用留多法对模型进行验证。QSPR分析分别得出了针对酸性药物和碱性药物以及所有药物的多个显著模型。验证研究表明，所选模型预测的平均倍数误差在1.79至2.17之间。虽然针对酸和碱的单独QSPR模型的预测误差低于针对所有药物的模型，但外部验证研究表明，所得到的酸的方程适用性有限。因此，推荐使用仅需要计算结构描述符的通用模型。QSPR模型能够预测不同化学类别的药物的分布容积，其预测误差与其他更复杂的预测方法（包括常用的种间缩放）类似。该模型中的结构描述符可根据已知的分布机制和药物的分子结构进行解释。
