Literature DB >> 17514565

How can structural similarity analysis help in category formation?

J Jaworska1, N Nikolova-Jeliazkova.   

Abstract

Chemical category is a regulatory concept facilitating filling safety data gaps. Practically, all chemical management programs like the OECD HPV Program, EU REACH, or the Canadian DSL Categorization are planning to use or are already using categorization approaches to reduce resources including animal testing. The aim of the study was to discuss the feasibility to apply computational structural similarity methods to augment formation of a category. The article discusses also how this understanding can be translated into computer readable format, an ultimate need for practical, broad scope applications. We conclude that for the skin sensitization endpoint, used as a working example, mechanistic understanding expressed as chemical reactivity can be exploited by computational structural similarity methods to augment category formation process. We propose a novel method, atom environments ranking (AER), to assess similarity to a reference training set representing a common mechanism of action, as a potential method for grouping chemicals into reactivity domains.

Mesh:

Year:  2007        PMID: 17514565     DOI: 10.1080/10629360701306050

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


  8 in total

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2.  AMBIT RESTful web services: an implementation of the OpenTox application programming interface.

Authors:  Nina Jeliazkova; Vedrin Jeliazkov
Journal:  J Cheminform       Date:  2011-05-16       Impact factor: 5.514

3.  The eNanoMapper database for nanomaterial safety information.

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Journal:  Beilstein J Nanotechnol       Date:  2015-07-27       Impact factor: 3.649

4.  Analysis of publically available skin sensitization data from REACH registrations 2008-2014.

Authors:  Thomas Luechtefeld; Alexandra Maertens; Daniel P Russo; Costanza Rovida; Hao Zhu; Thomas Hartung
Journal:  ALTEX       Date:  2016-02-11       Impact factor: 6.043

5.  Global analysis of publicly available safety data for 9,801 substances registered under REACH from 2008-2014.

Authors:  Thomas Luechtefeld; Alexandra Maertens; Daniel P Russo; Costanza Rovida; Hao Zhu; Thomas Hartung
Journal:  ALTEX       Date:  2016-02-11       Impact factor: 6.043

6.  Analysis of public oral toxicity data from REACH registrations 2008-2014.

Authors:  Thomas Luechtefeld; Alexandra Maertens; Daniel P Russo; Costanza Rovida; Hao Zhu; Thomas Hartung
Journal:  ALTEX       Date:  2016-02-11       Impact factor: 6.043

Review 7.  In silico toxicology: comprehensive benchmarking of multi-label classification methods applied to chemical toxicity data.

Authors:  Arwa B Raies; Vladimir B Bajic
Journal:  Wiley Interdiscip Rev Comput Mol Sci       Date:  2017-12-04

8.  In Silico Searching for Alternative Lead Compounds to Treat Type 2 Diabetes through a QSAR and Molecular Dynamics Study.

Authors:  Nicolás Cabrera; Sebastián A Cuesta; José R Mora; Luis Calle; Edgar A Márquez; Roland Kaunas; José Luis Paz
Journal:  Pharmaceutics       Date:  2022-01-19       Impact factor: 6.321

  8 in total

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