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评价 211 个类药性化合物的 pKa 估算方法。

Evaluation of pKa estimation methods on 211 druglike compounds.

机构信息

Infection Discovery, AstraZeneca R&D Boston, 35 Gatehouse Drive, Waltham, Massachusetts 02451, USA.

出版信息

J Chem Inf Model. 2010 Apr 26;50(4):565-71. doi: 10.1021/ci100019p.

Abstract

The pK(a) values of 211 discovery (druglike) compounds were determined experimentally using capillary electrophoresis coupled with ultraviolet spectroscopy and a novel fitting algorithm. These values were compared to those predicted by five different commercially available pK(a) estimation packages: ACDLabs/pK(a), Marvin (ChemAxon), MoKa (Molecular Discovery), Epik (Schrodinger), and Pipeline Pilot (Accelrys). Even though the topological method MoKa was noticeably faster than ACD, the accuracy of those two methods and Marvin was statistically indistinguishable, with a root-mean-squared error of about 1 pK(a) unit compared to experiment. Pipeline Pilot and EpiK both produced pK(a) estimates in significantly worse agreement with the experiment. Interestingly, on a number of compounds, the predictions due to ACD v12 were in poorer agreement with the experiment than ACD v10. Microscopic and "apparent" pK(a) predictions were also compared using ACD v10. Microscopic pK(a)s gave significantly worse agreement with the experiment than the "apparent" values. In all cases, the errors appeared to be randomly distributed across chemical series.

摘要

使用毛细管电泳结合紫外光谱和一种新的拟合算法,实验测定了 211 种发现(类药)化合物的 pK(a) 值。将这些值与五种不同的商业可用 pK(a) 估算软件包的预测值进行了比较:ACD Labs/pK(a)、Marvin(ChemAxon)、MoKa(Molecular Discovery)、Epik(Schrodinger)和 Pipeline Pilot(Accelrys)。尽管拓扑方法 MoKa 明显快于 ACD,但这两种方法和 Marvin 的准确性在统计学上是不可区分的,与实验相比,均方根误差约为 1 pK(a)单位。Pipeline Pilot 和 EpiK 生成的 pK(a) 估算值与实验的一致性明显较差。有趣的是,在许多化合物上,ACD v12 的预测值与实验的一致性不如 ACD v10。还使用 ACD v10 比较了微观和“表观”pK(a)预测值。微观 pK(a) 值与实验的一致性明显较差。在所有情况下,误差似乎在化学系列中随机分布。

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