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一种用于多组分药物设计的新方法及其在优化参麦配方中活性成分组合的应用。

A novel methodology for multicomponent drug design and its application in optimizing the combination of active components from Chinese medicinal formula Shenmai.

机构信息

Pharmaceutical Informatics Institute, Zhejiang University, Hangzhou 310058, China.

出版信息

Chem Biol Drug Des. 2010 Mar;75(3):318-24. doi: 10.1111/j.1747-0285.2009.00934.x.

Abstract

Traditional Chinese Medicine has become an important resource for searching the effective drug combinations in multicomponent drug designs. In this article, we investigate the methodology on how to efficiently optimize the combination of several active components from traditional Chinese formula. A new method based upon lattice experimental design and multivariate regression was applied to model the quantitative composition-activity relationship (QCAR) in this study. As a result, multi-objective optimization was achieved by Derringer function using extensive search algorithm. This newly proposed QCAR-based strategy for multicomponent drug design was then successfully applied on search optimal combination of three components from Chinese medicinal formula Shenmai. The result validated the effectiveness of the presented method for multicomponent drug design.

摘要

中医药已成为从多组分药物设计中寻找有效药物组合的重要资源。本文研究了如何有效地优化从传统中药配方中提取的几种活性成分的组合的方法。在这项研究中,我们应用基于格子实验设计和多元回归的新方法来构建定量构效关系(QCAR)模型。结果,通过 Derringer 函数使用广泛搜索算法实现了多目标优化。然后,我们成功地将基于 QCAR 的多组分药物设计策略应用于从中药配方参麦中搜索最佳的三种成分组合。结果验证了该方法在多组分药物设计中的有效性。

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