Interpretation of CoMFA Results – A Probe Set Study Using Hydrophobic Fields

I. Pajeva, M. Wiese
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引用次数: 7

Abstract

The main purpose of the study was to examine the correctness of interpretation of CoMFA results using an artificially designed data set with predefined contributions of the compound substituents to activity. The activity values were assigned according to additive (sum of substituent π-constants) and nonlinear (sum of absolute values of substituent π-constants) dependencies on hydrophobicity. Predictions by 3D (HINT hydrophobic fields) and logP (HINT and CLOGP values) presentations of hydrophobicity were compared and similarity between standard CoMFA and hydrophobic fields was evaluated. The main results are: (i) the cross- validated R2 (Q2) values with the first PLS components of the field models may be indicative for identification of the underlying property(ies) in the data set providing each field alone yields a satisfactory predictive model with several components; (ii) the logP values alone are not predictive when the target property is nonlinearly dependent on the explanatory property; (iii) similarity between fields of different nature (steric, electrostatic, hydrophobic) can be evaluated by cross- and non-cross-validation correlations between the X-scores of the first components – low Q2 and R2 suggest that the most informative variances of the compared fields are different; (iv) the CoMFA graphical display is very much dependent on the distribution of the positive and negative field terms – if their contributions to the whole field signal are not symmetrically distributed the default CoMFA contour view setting can lead to wrong displays and, consequently, wrong interpretation of the results.
CoMFA结果的解释-使用疏水场的探针组研究
本研究的主要目的是检验使用人工设计的数据集对CoMFA结果的解释的正确性,这些数据集预先定义了化合物取代基对活性的贡献。活性值是根据疏水性的可加性(取代基π常数和)和非线性(取代基π常数绝对值和)关系确定的。比较了3D (HINT疏水性场)和logP (HINT和CLOGP值)对疏水性的预测,并评价了标准CoMFA和疏水性场之间的相似性。主要结果是:(i)交叉验证的R2 (Q2)值与字段模型的第一个PLS分量可以指示识别数据集中的潜在属性(ies),提供每个字段单独产生具有多个分量的令人满意的预测模型;(ii)当目标属性非线性依赖于解释属性时,单独的logP值不能预测;(iii)不同性质的场(立体、静电、疏水)之间的相似性可以通过第一个分量的x值之间的交叉验证和非交叉验证相关性来评估——低Q2和R2表明比较场的最重要的信息方差是不同的;(iv) CoMFA图形显示非常依赖于正负场项的分布,如果它们对整个场信号的贡献不对称分布,默认的CoMFA轮廓视图设置可能导致错误的显示,从而导致对结果的错误解释。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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