Literature DB >> 9501507

Predicting acute toxicity (LC50) of benzene derivatives using theoretical molecular descriptors: a hierarchical QSAR approach.

B D Gute1, S C Basak.   

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.

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Year:  1997        PMID: 9501507     DOI: 10.1080/10629369708039127

Source DB:  PubMed          Journal:  SAR QSAR Environ Res        ISSN: 1026-776X            Impact factor:   3.000


  3 in total

1.  Comparative QSPR studies with molecular connectivity, molecular negentropy and TAU indices. Part I: molecular thermochemical properties of diverse functional acyclic compounds.

Authors:  Kunal Roy; Achintya Saha
Journal:  J Mol Model       Date:  2003-06-20       Impact factor: 1.810

2.  Development, interpretation and temporal evaluation of a global QSAR of hERG electrophysiology screening data.

Authors:  Claire L Gavaghan; Catrin Hasselgren Arnby; Niklas Blomberg; Gert Strandlund; Scott Boyer
Journal:  J Comput Aided Mol Des       Date:  2007-03-24       Impact factor: 3.686

Review 3.  Machine Learning Based Toxicity Prediction: From Chemical Structural Description to Transcriptome Analysis.

Authors:  Yunyi Wu; Guanyu Wang
Journal:  Int J Mol Sci       Date:  2018-08-10       Impact factor: 5.923

  3 in total

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