电子构象QSAR法鉴定I类代谢性谷氨酸受体激动剂的药效团及生物活性预测

E. Rosines, I. Bersuker, J. E. Boggs
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引用次数: 7

摘要

利用已开发和进一步改进的电子构象(EC)方法,揭示了一类代谢型谷氨酸受体(mGluRl)激动剂的药效团,并对其活性进行了预测。该方法的一个显著特征是,除了将药效团的活性揭示为一组以特殊几何形状排列的特定原子电子特征外,它还允许定量预测药效团的活性,作为药效团灵活性和抗药效团屏蔽群参数的函数。对29个化合物(13个活性化合物和16个非活性化合物)的训练集进行构象分析、电子结构计算和矩阵处理,并对mGluRl激动剂的药效团进行评价。它包含一个四点骨架,由三个氧原子和一个氮原子组成,在一定的原子间距离上具有有限的原子相互作用指数,所有这些参数都是在一定的公差范围内确定的。药效团参数的灵活性,以及抗药效团屏蔽和其他辅助基团的影响被参数化,并由7个常数加权,它们的值从具有很好的统计量的最小二乘回归中得到:r2 =0.97, F=589(~ 100%置信水平),标准误差约为测量值范围的5%。结果也用留一交叉验证方法进行了检验,得到预测统计量r2 = 0.91。还评估了E统计数据,说明了所涉及的每个活动参数的作用。
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Pharmacophore identification and bioactivity prediction for group I metabotropic glutamate receptor agonists by the electron-conformational QSAR method
The pharmacophore for group I metabotropic glutamate receptor (mGluRl) agonists is revealed and their activity predicted by means of the previously developed and further improved electron-conformational (EC) method. A distinguishing feature of this method is that in addition to revealing the pharmacophore of activity as a set of specific atomic electronic features arranged in a special geometry, it allows for prediction of the activity quantitatively as a function of the parameters of pharmacophore flexibility and anti-pharmacophore shielding groups. Conformational analysis, electronic structure calculations, and matrix processing are performed for the training set of 29 compounds, 13 active and 16 inactive, and the pharmacophore of mGluRl agonists is evaluated. It contains a four-point skeleton of three oxygen atoms and one nitrogen atom at certain interatomic distances with restricted atomic interaction indices whereby all these parameters are determined within certain tolerances. The pharmacophore parameter flexibilities, as well as the influence of the anti-pharmacophore shielding and other auxiliary groups are parameterized and weighted by seven constants, their values being obtained from a least-square regression with very good statistics: R 2 =0.97, F=589 (∼100% level of confidence), and a standard error of about 5% of the range of measured values. The results are also tested with the leave-one-out cross-validation method that yields prediction statistics R 2 = 0.91. The E statistics were also evaluated illustrating the role of each of the activity parameters involved.
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