Literature DB >> 18617309

Toxmatch--a chemical classification and activity prediction tool based on similarity measures.

Ana Gallegos-Saliner1, Albert Poater, Nina Jeliazkova, Grace Patlewicz, Andrew P Worth.   

Abstract

Chemical similarity forms the underlying basis for the development of (Quantitative) Structure-Activity Relationships ((Q)SARs), expert systems and chemical groupings. Recently a new software tool to facilitate chemical similarity calculations named Toxmatch was developed. Toxmatch encodes a number of similarity indices to help in the systematic development of chemical groupings, including endpoint specific groupings and read-across, and the comparison of model training and test sets. Two rule-based classification schemes were additionally implemented, namely: the Verhaar scheme for assigning mode of action for aquatic toxicants and the BfR rulebase for skin irritation and corrosion. In this study, a variety of different descriptor-based similarity indices were used to evaluate and compare the BfR training set with respect to its test set. The descriptors utilised in this comparison were the same as those used to derive the original BfR rules i.e. the descriptors selected were relevant for skin irritation/corrosion. The Euclidean distance index was found to be the most predictive of the indices in assessing the performance of the rules.

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Year:  2008        PMID: 18617309     DOI: 10.1016/j.yrtph.2008.05.012

Source DB:  PubMed          Journal:  Regul Toxicol Pharmacol        ISSN: 0273-2300            Impact factor:   3.271


  6 in total

1.  Navigating through the minefield of read-across tools: A review of in silico tools for grouping.

Authors:  Patlewicz Grace; Helman George; Pradeep Prachi; Shah Imran
Journal:  Comput Toxicol       Date:  2017-08

2.  Exploring current read-across applications and needs among selected U.S. Federal Agencies.

Authors:  Grace Patlewicz; Lucina E Lizarraga; Diego Rua; David G Allen; Amber B Daniel; Suzanne C Fitzpatrick; Natàlia Garcia-Reyero; John Gordon; Pertti Hakkinen; Angela S Howard; Agnes Karmaus; Joanna Matheson; Moiz Mumtaz; Andrea-Nicole Richarz; Patricia Ruiz; Louis Scarano; Takashi Yamada; Nicole Kleinstreuer
Journal:  Regul Toxicol Pharmacol       Date:  2019-05-10       Impact factor: 3.271

3.  MetMaxStruct: A Tversky-Similarity-Based Strategy for Analysing the (Sub)Structural Similarities of Drugs and Endogenous Metabolites.

Authors:  Steve O'Hagan; Douglas B Kell
Journal:  Front Pharmacol       Date:  2016-08-22       Impact factor: 5.810

4.  In silico identification of protein targets for chemical neurotoxins using ToxCast in vitro data and read-across within the QSAR toolbox.

Authors:  Y G Chushak; H W Shows; J M Gearhart; H A Pangburn
Journal:  Toxicol Res (Camb)       Date:  2018-03-12       Impact factor: 3.524

5.  In-Silico Drug Toxicity and Interaction Prediction for Plant Complexes Based on Virtual Screening and Text Mining.

Authors:  Feng Zhang; Kumar Ganesan; Yan Li; Jianping Chen
Journal:  Int J Mol Sci       Date:  2022-09-02       Impact factor: 6.208

6.  Pesticides Curbing Soil Fertility: Effect of Complexation of Free Metal Ions.

Authors:  Sukhmanpreet Kaur; Vijay Kumar; Mohit Chawla; Luigi Cavallo; Albert Poater; Niraj Upadhyay
Journal:  Front Chem       Date:  2017-07-04       Impact factor: 5.221

  6 in total

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