Quantitative Characterization of Molecular Similarity Spaces: Tools for Computational Toxicology (1996-1997)
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Quantitative Characterization of Molecular Similarity Spaces: Tools for Computational Toxicology (1996-1997)
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1997
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University of Minnesota Duluth
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Technical Report
Abstract
Four classes of theoretical structural parameters, viz., topostructural, topochemical,geometrical and quantum chemical descriptors, have been used in the development of
quantitative structure-activity relationship (QSAR) models for a set of sixty-nine
benzene derivatives. None of the individual classes of parameters was very effective in
predicting toxicity. A hierarchical approach was followed in using a combination of the
four classes of indices in QSAR model development. The results show that the
hierarchical QSAR approach using the algorithmically derived molecular descriptors can estimate the LC50 values of the benzene derivatives reasonably well.
Description
Progress Report of the AFOSR AASERT Project; Covering research period 8/1/96 to 7/31/97; Agency No: DOD/F49620-96-1-0330;
U of M No:9606754
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Natural Resources Research Institute
University of Minnesota, Duluth
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Basak, Subhash C; Gute, Brian D. (1997). Quantitative Characterization of Molecular Similarity Spaces: Tools for Computational Toxicology (1996-1997). Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/187201.
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