Collect. Czech. Chem. Commun.
1999, 64, 1551-1571
https://doi.org/10.1135/cccc19991551
QSPR and QSAR Models Derived Using Large Molecular Descriptor Spaces. A Review of CODESSA Applications
Mati Karelsona,*, Uko Marana, Yilin Wangb and Alan R. Katritzkyb,*
a Department of Chemistry, University of Tartu, 2 Jakobi Str., Tartu 51014, Estonia
b Center for Heterocyclic Compounds, Department of Chemistry, University of Florida, P.O. Box 117200, Gainesville, FL 32611-7200, U.S.A
Abstract
An overview on the development of QSPR/QSAR equations using various descriptor-mining techniques and multilinear regression analysis in the framework of the CODESSA (Comprehensive Descriptors for Structural and Statistical Analysis) program is given. The description of the methodologies applied in CODESSA is followed by the presentation of the QSAR and QSPR models derived for eighteen molecular activities and properties. The properties cover single molecular species, interactions between different molecular species, properties of surfactants, complex properties and properties of polymers. A review with 54 references.
Keywords: Molecular descriptors; QSPR; QSAR; Property or activity prediction.
