CORAL: Binary Classifications (Active/Inactive) for Liver-Related Adverse Effects of Drugs

Andrey      A. Toropov; 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.

Keywords: Binary classification, CORAL software, Liver-Related Adverse Effect, Method Monte Carlo, Optimal descriptor, QSAR, Monte Carlo technique, Hydrogen-suppressed graph, Aspartate aminotransferase, serum enzyme marker of liver toxicity