Literature DB >> 20693021

Skin sensitization structure-activity relationships for phenyl benzoates.

M D Barratt1, D A Basketter, D W Roberts.   

Abstract

The key to determining whether a chemical has the ability to behave as a contact allergen must reside ultimately in the structure and properties of that chemical rather than in the immune system. Quantitative structure-activity relationships (QSARs) have been demonstrated for a small number of series of chemicals in the past, using the relative alkylation index model based on this principle. In the present work, a carefully chosen range of phenyl benzoate esters has been synthesized such that they would have a single mechanism of action but otherwise would span important areas of parameter space-reactivity, skin penetration characteristics and biological response. Computer-based methods of analysis were used to generate a QSAR. The model showed that molecular volume and particularly the calculated logarithm of the partition coefficient (ClogP) were key parameters. Surprisingly, while chemical reactivity is a requirement for skin sensitization, it was not found to be an important variable in the QSAR. In conclusion, the study confirms that within a series of related chemicals it is possible to derive a useful QSAR.

Entities:  

Year:  1994        PMID: 20693021     DOI: 10.1016/0887-2333(94)90077-9

Source DB:  PubMed          Journal:  Toxicol In Vitro        ISSN: 0887-2333            Impact factor:   3.500


  3 in total

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2.  Identification of Potential Inhibitors from Pyriproxyfen with Insecticidal Activity by Virtual Screening.

Authors:  Ryan da Silva Ramos; Josivan da Silva Costa; Rai Campos Silva; Glauber Vilhena da Costa; Alex Bruno Lobato Rodrigues; Érica de Menezes Rabelo; Raimundo Nonato Picanço Souto; Carlton Anthony Taft; Carlos Henrique Tomich de Paula da Silva; Joaquín Maria Campos Rosa; Cleydson Breno Rodrigues Dos Santos; Williams Jorge da Cruz Macêdo
Journal:  Pharmaceuticals (Basel)       Date:  2019-01-25

Review 3.  Applications of Deep-Learning in Exploiting Large-Scale and Heterogeneous Compound Data in Industrial Pharmaceutical Research.

Authors:  Laurianne David; Josep Arús-Pous; Johan Karlsson; Ola Engkvist; Esben Jannik Bjerrum; Thierry Kogej; Jan M Kriegl; Bernd Beck; Hongming Chen
Journal:  Front Pharmacol       Date:  2019-11-05       Impact factor: 5.810

  3 in total

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