相似聚类预测咖啡因的QSAR

Central European Journal of Chemistry Pub Date : 2014-03-01 DOI:10.2478/s11532-013-0389-y

Teodora E. Harsa, Alexandra M. Harsa, Beata Szefler

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引用次数: 3

摘要

在PubChem数据库下载的一组40种咖啡因上，研究了一种基于相关加权和对齐的新型QSAR方法，该方法模拟了所研究的相关空间。在外部测试集和新的预测模型中，利用相似性聚类验证了描述该咖啡因衍生物的logp和LD50值的最佳模型。

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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QSAR of caffeines by similarity cluster prediction

AbstractA novel QSAR approach based on correlation weighting and alignment over a hypermolecule that mimics the investigated correlational space was performed on a set of 40 caffeines downloaded from the PubChem database. The best models describing log P and LD50 values of this set of caffeine derivatives were validated against the external test set and in a new predictive model by using clusters of similarity.

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来源期刊

Central European Journal of Chemistry 化学-化学综合

自引率

0.00%

发文量

审稿时长

3 months