Literature DB >> 2405259

The structural basis of the mutagenicity of chemicals in Salmonella typhimurium: the Gene-Tox data base.

G Klopman1, M R Frierson, H S Rosenkranz.   

Abstract

The CASE structure-activity methodology has been applied to a Gene-Tox derived Salmonella mutagenicity data base consisting of 808 chemicals. Based upon qualitative structural features, CASE identified 29 activating and 3 inactivating structural determinants which correctly predicted the probability of carcinogenicity of 93.7% of the known mutagens and non-mutagens in the data base (sensitivity = 0.998, and specificity = 0.704). Additionally, based upon a qualitative structure-activity analysis, CASE's performance was even better, leading to a sensitivity of 0.981 and a specificity of 1.000. Using the structural determinants identified in this data base, CASE gave excellent predictions of the mutagenicity of chemicals not included in the data base. The identified biophores and biophobes can also be used to investigate the structural basis of the mutagenicity of various chemical classes.

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Year:  1990        PMID: 2405259     DOI: 10.1016/0027-5107(90)90013-t

Source DB:  PubMed          Journal:  Mutat Res        ISSN: 0027-5107            Impact factor:   2.433


  8 in total

1.  Mutagenicity of cytostatic drugs in a bacterial system. I. Ames test.

Authors:  J Marhan
Journal:  Folia Microbiol (Praha)       Date:  1995       Impact factor: 2.099

2.  Persistent proliferation of normal hepatocytes and promotion of preneoplastic development by N-nitrosodibenzylamine in rats.

Authors:  H Blaszyk; A Hartmann; M Danz
Journal:  J Cancer Res Clin Oncol       Date:  1993       Impact factor: 4.553

3.  Structure-activity relations: maximizing the usefulness of mutagenicity and carcinogenicity databases.

Authors:  G Klopman; H Rosenkranz
Journal:  Environ Health Perspect       Date:  1991-12       Impact factor: 9.031

4.  Relationship between molecular connectivity and carcinogenic activity: a confirmation with a new software program based on graph theory.

Authors:  D Malacarne; R Pesenti; M Paolucci; S Parodi
Journal:  Environ Health Perspect       Date:  1993-09       Impact factor: 9.031

5.  In vivo and in vitro mutagenicity of perillaldehyde and cinnamaldehyde.

Authors:  Masamitsu Honma; Masami Yamada; Manabu Yasui; Katsuyoshi Horibata; Kei-Ichi Sugiyama; Kenichi Masumura
Journal:  Genes Environ       Date:  2021-07-16

6.  Bioalerts: a python library for the derivation of structural alerts from bioactivity and toxicity data sets.

Authors:  Isidro Cortes-Ciriano
Journal:  J Cheminform       Date:  2016-03-04       Impact factor: 5.514

7.  Improvement of quantitative structure-activity relationship (QSAR) tools for predicting Ames mutagenicity: outcomes of the Ames/QSAR International Challenge Project.

Authors:  Masamitsu Honma; Airi Kitazawa; Alex Cayley; Richard V Williams; Chris Barber; Thierry Hanser; Roustem Saiakhov; Suman Chakravarti; Glenn J Myatt; Kevin P Cross; Emilio Benfenati; Giuseppa Raitano; Ovanes Mekenyan; Petko Petkov; Cecilia Bossa; Romualdo Benigni; Chiara Laura Battistelli; Alessandro Giuliani; Olga Tcheremenskaia; Christine DeMeo; Ulf Norinder; Hiromi Koga; Ciloy Jose; Nina Jeliazkova; Nikolay Kochev; Vesselina Paskaleva; Chihae Yang; Pankaj R Daga; Robert D Clark; James Rathman
Journal:  Mutagenesis       Date:  2019-03-06       Impact factor: 3.000

8.  Development of a new quantitative structure-activity relationship model for predicting Ames mutagenicity of food flavor chemicals using StarDrop™ auto-Modeller™.

Authors:  Toshio Kasamatsu; Airi Kitazawa; Sumie Tajima; Masahiro Kaneko; Kei-Ichi Sugiyama; Masami Yamada; Manabu Yasui; Kenichi Masumura; Katsuyoshi Horibata; Masamitsu Honma
Journal:  Genes Environ       Date:  2021-04-30
  8 in total

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