New developments in PEST shape/property hybrid descriptors
New developments in PEST shape/property hybrid descriptors
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DOI：
10.1023/a:1025334310107
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发表时间：
2003-02-01
影响因子：
3.5
通讯作者：
Embrechts, MJ
中科院分区：
文献类型：
--
作者：
Breneman, CM;Sundling, CM;Embrechts, MJ
最近的研究表明，形状/属性混合描述符与2D拓扑描述符的结合提高了QSAR和QSPR模型的预测能力。可以使用从头算或半经验电子密度表面和/或电子性质以及基于原子片段的TAE/Recon性质编码表面重建来计算性质编码表面翻译器(PEST)描述符。Recon和PEST算法还包括基于片段的快速小波系数描述符(WCD)计算。这些描述符能够对化学信息进行紧凑编码。我们还简要讨论了在虚拟高通量模式下使用Recon/PEST方法，以及使用TAE性质进行分子表面自相关分析。
Recent investigations have shown that the inclusion of hybrid shape/property descriptors together with 2D topological descriptors increases the predictive capability of QSAR and QSPR models. Property-Encoded Surface Translator (PEST) descriptors may be computed using ab initio or semi-empirical electron density surfaces and/or electronic properties, as well as atomic fragment-based TAE/RECON property-encoded surface reconstructions. The RECON and PEST algorithms also include rapid fragment-based wavelet coefficient descriptor (WCD) computation. These descriptors enable a compact encoding of chemical information. We also briefly discuss the use of the RECON/PEST methodology in a virtual high-throughput mode, as well as the use of TAE properties for molecular surface autocorrelation analysis.