Prediction of cellular toxicity of halocarbons from computed chemodescriptors: A hierarchical QSAR approach

Subhash C Basak, Krishnan Balasubramanian, Brian D Gute, Denise Mills, Anna Gorczynska, Szczepan Roszak

Research output: Contribution to journalArticlepeer-review

35 Scopus citations

Abstract

A hierarchical quantitative structure-activity relationship (HiQSAR) approach was used to estimate toxicity and genetic toxicity for a set of 55 halocarbons using computed chemodescriptors. The descriptors consisted of topostructural (TS), topochemical (TC), geometrical, semiempirical (AM1) quantum chemical, and ab initio (STO-3G, 6-31G(d), 6-311G, 6-31(d), and aug-cc-pVTZ) quantum chemical indices. For the two toxicity endpoints investigated, ARR and D37, the TC indices gave the best cross-validated R2 values. The 3-D indices also performed either as well as or slightly superior to the TC indices. For the four categories of quantum chemical indices used for the development of predictive models, the AMI parameters gave the worst performance, and the most advanced ab initio (B3LYP/aug-CC-pVTZ) parameters gave the best results when used alone. This was also the case when the quantum chemical indices were used in the hierarchical QSAR approach for both of the toxicity endpoints, ARR and D37. The models resulting from HiQSAR are of sufficiently good quality to estimate toxicity of halocarbons from structure.

Original languageEnglish (US)
Pages (from-to)1103-1109
Number of pages7
JournalJournal of chemical information and computer sciences
Volume43
Issue number4
DOIs
StatePublished - Jul 1 2003

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