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New developments in PEST shape/property hybrid descriptors

Publication Type : Journal Article

Thematic Areas : Center for Computational Engineering and Networking (CEN)

Source : Journal Computer-Aided Mol. Design, 17, 231–240, 2003

Url : https://www.researchgate.net/publication/9888019_New_developments_in_PEST_shapeproperty_hybrid_descriptors

Campus : Coimbatore

School : School of Engineering

Center : Center for Computational Engineering and Networking, Computational Engineering and Networking

Department : Center for Computational Engineering and Networking (CEN)

Year : 2003

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.

Cite this Research Publication : Curt M. Breneman, C. Matthew Sundling, N. Sukumar, Lingling Shen, William P. Katt and Mark J. Embrechts, “New developments in PEST shape/property hybrid descriptors” J. Computer-Aided Mol. Design, 17, 231–240, (2003) DOI: 10.1023/A:1025334310107 IF: 2.990

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