Literature DB >> 23062237

CORAL: binary classifications (active/inactive) for Liver-Related Adverse Effects of Drugs.

Andrey A Toropov1, Alla P Toropova, Bakhtiyor F Rasulev, Emilio Benfenati, Giuseppina Gini, Danuta Leszczynska, Jerzy Leszczynski.   

Abstract

Classification data related to the Liver-Related Adverse Effects of Drugs have been studied with the CORAL software (http://www.insilico.eu/coral). Two datasets which contain compounds with two serum enzyme markers of liver toxicity: alanine aminotransferase (ALT, n=187) and aspartate aminotransferase (AST, n=209) are analyzed. Statistical quality of the prediction for ALT activity is n=35, Sensitivity = 0.5556, Specificity = 0.8077, and Accuracy = 0.7429. In the case of AST activity the prediction is characterized by n=42, Sensitivity = 0.6875, Specificity = 0.7692, and Accuracy = 0.7381. A number of structural alerts which can be related to the studied activities are revealed. It is the first attempt to build up the classification QSAR model by means of the Monte Carlo technique based on representation of the molecular structure by SMILES using the CORAL software.

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Year:  2012        PMID: 23062237     DOI: 10.2174/157488612804096542

Source DB:  PubMed          Journal:  Curr Drug Saf        ISSN: 1574-8863


  3 in total

1.  Large-scale structure-activity relationship study of hepatitis C virus NS5B polymerase inhibition using SMILES-based descriptors.

Authors:  Apilak Worachartcheewan; Virapong Prachayasittikul; Alla P Toropova; Andrey A Toropov; Chanin Nantasenamat
Journal:  Mol Divers       Date:  2015-11       Impact factor: 2.943

2.  CORAL: Building up QSAR models for the chromosome aberration test.

Authors:  Andrey A Toropov; Alla P Toropova; Giuseppa Raitano; Emilio Benfenati
Journal:  Saudi J Biol Sci       Date:  2018-05-09       Impact factor: 4.219

3.  Computational Models Using Multiple Machine Learning Algorithms for Predicting Drug Hepatotoxicity with the DILIrank Dataset.

Authors:  Robert Ancuceanu; Marilena Viorica Hovanet; Adriana Iuliana Anghel; Florentina Furtunescu; Monica Neagu; Carolina Constantin; Mihaela Dinu
Journal:  Int J Mol Sci       Date:  2020-03-19       Impact factor: 5.923

  3 in total

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