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首页> 外文期刊>Der Pharma Chemica: journal for medicinal chemistry, pharmaceutical chemistry and computational chemistry >Three dimensional quantitative structure analysis substituted 1,3-diaryl propenone derivatives as antimalarial activity
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Three dimensional quantitative structure analysis substituted 1,3-diaryl propenone derivatives as antimalarial activity

机译：三维定量结构分析取代1,3-二芳基丙烯酮衍生物具有抗疟活性

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Molecular modeling analysis performed by k nearest neighbor molecular field analysis (kNN MFA) to recognize the necessary structural requirements of 1,3-diaryl propenone derivatives in 3D chemical space for adjusting modulation of the antimalarial activity. In study 14 compounds were selected randomly, using sphere exclusion (SE) algorithm and random selection method struture divided into training and test set. kNN-MFA methodology with stepwise (SW), simulated annealing (SA) and genetic algorithm (GA) was used for building the QSAR models. Predictive models were generated with SW-kNN MFA. The most significant model 1 is having internal predictivity 64.24% (q2 = 64.24) and external predictivity 61.57 % (pred_r2 = 0.61.57). Model showed that steric (S_584), and electrostatic (E-295) interactions play important role in determining DPP IV inhibitory activity.
机译：通过k最近邻分子场分析（kNN MFA）进行的分子建模分析，以认识3D化学空间中1,3-二芳基丙烯酮衍生物的必要结构要求，以调节抗疟活性的调节。在研究中，使用球排除（SE）算法和随机选择方法将14种化合物随机选择为训练和测试集。使用具有逐步（SW），模拟退火（SA）和遗传算法（GA）的kNN-MFA方法来构建QSAR模型。用SW-kNN MFA生成预测模型。最重要的模型1具有内部预测性64.24％（q2 = 64.24）和外部预测性61.57％（pred_r2 = 0.61.57）。模型显示空间（S_584）和静电（E-295）相互作用在确定DPP IV抑制活性中起重要作用。

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