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首页> 外文期刊>Journal of molecular graphics & modelling >Modeling structure-activity relationships of prodiginines with antimalarial activity using GA/MLR and OPS/PLS
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Modeling structure-activity relationships of prodiginines with antimalarial activity using GA/MLR and OPS/PLS

机译:使用GA / MLR和OPS / PLS对具有抗疟疾活性的原虫的构效关系进行建模

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摘要

In the present study, we performed a multivariate quantitative structure-activity relationship (QSAR) analysis of 52 prodiginines with antimalarial activity. Variable selection was based on the genetic algorithm (GA) and ordered predictor selection (OPS) approaches, and the models were built using the multiple linear regression (MLR) and partial least squares (PLS) regression methods. The leave-N-out crossvalidation and y-randomization tests showed that the models were robust and free from chance correlation. The mechanistic interpretation of the results was supported by earlier findings. In addition, the comparison of our models with those previously described indicated that the OPS/PLS-based model had a higher quality of external prediction. Thus, this study provides a comprehensive approach to the evaluation of the antimalarial activity of prodiginines, which may be used as a support tool in designing new therapeutic agents for malaria. (C) 2014 Elsevier Inc. All rights reserved.
机译:在本研究中,我们对52个具有抗疟疾活性的蛋白质进行了多变量定量构效关系(QSAR)分析。变量选择基于遗传算法(GA)和有序预测变量选择(OPS)方法,并且使用多元线性回归(MLR)和偏最小二乘(PLS)回归方法构建模型。遗忘-N-交叉验证和y随机化测试表明,该模型很健壮,没有机会相关性。结果的机械解释得到了早期发现的支持。此外,我们的模型与前面描述的模型的比较表明,基于OPS / PLS的模型具有更高的外部预测质量。因此,本研究提供了一种综合的方法来评估pro虫的抗疟活性,可将其用作设计疟疾新治疗剂的辅助工具。 (C)2014 Elsevier Inc.保留所有权利。

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