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ACD/Log P method description

机译:ACD / Log P方法说明

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摘要

This study describes the development of the ACD/Log P calculation method. Analysis of 14 calculation methods revealed that the most accurate calculations are obtained when correction factors are used. We evaluated the correction factors used by Hansch and Leo in CLOGP in order to simplify their method. Most of the CLOGP structural factors are included in our fragmental increments. Aliphatic and aromatic factors are replaced with additive interfragmental increments. Missing increments are estimated by two empirical equations with simple physical interpretation. The final method uses three simple equations with several types of parameters. The training set included 3601 compounds and the correlation between experimental and calculated Log P values gave R = 0.992, S = 0.21. The method was validated by comparing it with 17 other methods on various data sets of independently selected drugs and other compounds. In all cases, our method produced the best results. The weakness of this methods is that it uses a large number of individual increments for aromatic interactions. Each increment represents a combination of several effects which presently cannot be separated.
机译:这项研究描述了ACD / Log P计算方法的发展。对14种计算方法的分析表明,使用校正因子可获得最准确的计算。为了简化他们的方法,我们评估了Hansch和Leo在CLOGP中使用的校正因子。大多数CLOGP结构因素都包含在我们的片段增量中。脂肪和芳香因子被片段间相加增量所取代。缺失增量由两个具有简单物理解释的经验方程式估算。最终方法使用带有几种类型参数的三个简单方程式。训练集包括3601种化合物,实验值与计算值Log P的相关性得出R = 0.992,S = 0.21。通过与独立选择的药物和其他化合物的各种数据集上的其他17种方法进行比较,对该方法进行了验证。在所有情况下,我们的方法都能产生最佳结果。该方法的弱点在于,它使用大量的单个增量进行芳族相互作用。每个增量代表目前无法分离的几种效果的组合。

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