Abstract
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.
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Breneman, C.M., Sundling, C.M., Sukumar, N. et al. New developments in PEST shape/property hybrid descriptors. J Comput Aided Mol Des 17, 231–240 (2003). https://doi.org/10.1023/A:1025334310107
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DOI: https://doi.org/10.1023/A:1025334310107