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首页> 外文期刊>Molecular informatics >Are Mechanistic and Statistical QSAR Approaches Really Different? MLR Studies on 158 Cycloalkyl-Pyranones
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Are Mechanistic and Statistical QSAR Approaches Really Different? MLR Studies on 158 Cycloalkyl-Pyranones

机译：机械和统计QSAR方法真的不同吗？ 158个环烷基吡喃酮的MLR研究

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摘要

Two parallel approaches for quantitative structure-activity relationships (QSAR) are predominant in literature, one guided by mechanistic methods (including read-across) and another by the use of statistical methods. To bridge the gap between these two approaches and to verify their main differences, a comparative study of mechanistically relevant and statistically relevant QSAR models, developed on a case study of 158 cycloalkyl-pyranones, biologically active on inhibition (K~i) of HIV protease, was performed. Firstly, Multiple Linear Regression (MLR) based models were developed starting from a limited amount of molecular descriptors which were widely proven to have mechanistic interpretation. Then robust and predictive MLR models were developed on the same set using two different statistical approaches unbiased of input descriptors. Development of models based on Statistical I method was guided by stepwise addition of descriptors while Genetic Algorithm based selection of descriptors was used for the Statistical II. Internal validation, the standard error of the estimate, and Fisher's significance test were performed for both the statistical models. In addition, external validation was performed for Statistical II model, and Applicability Domain was verified as normally practiced in this approach. The relationships between the activity and the important descriptors selected in all the models were analyzed and compared.
机译：文献中主要采用两种并行的定量构效关系（QSAR）方法，一种是通过机械方法（包括交叉阅读）进行指导，另一种是通过统计方法进行指导。为了弥合这两种方法之间的差距并验证它们的主要差异，在158个环烷基-吡喃酮的案例研究中，对机械相关和统计相关的QSAR模型进行了比较研究，该化合物对HIV蛋白酶的抑制（K〜i）具有生物活性，已执行。首先，从有限数量的分子描述符开始开发基于多元线性回归（MLR）的模型，该分子描述符已被广泛证明具有机理性解释。然后，使用两种不带输入描述符偏差的统计方法，在同一组上开发了健壮和可预测的MLR模型。通过逐步添加描述符来指导基于统计I方法的模型的开发，而基于遗传算法的描述符选择用于统计II。对两个统计模型都进行了内部验证，估计的标准误和费舍尔显着性检验。此外，对统计II模型进行了外部验证，并按照此方法的正常操作对“适用性域”进行了验证。分析和比较了活动与在所有模型中选择的重要描述符之间的关系。

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