@article{repository607,
       publisher = {pharmaciana},
          number = {2},
           title = {In silico toxicity prediction of 1-phenyl-1-(quinazolin-4-yl) ethanol compounds by using Toxtree, pkCSM and preADMET},
          volume = {8},
           pages = {205--216},
         journal = {In silico toxicity prediction of 1-phenyl-1-(quinazolin-4-yl) ethanol compounds by using Toxtree, pkCSM and preADMET},
            issn = {2088 4559},
          author = {Yeni, Yeni and Supandi Supandi, Supandi and Fajar, Merdekawati},
             url = {http://journal.uad.ac.id/index.php/PHARMACIANA/article/view/205},
        abstract = {The 1-phenyl-1-(quinazolin-4-yl) ethanol compounds are alkaloids of quinozoline class found in many Hydrangeaceae families. A survey revealed that most of the identified quinazoline derivatives have anticancer activity. Toxicity prediction of 1-phenyl-1-(quinazolin-4-yl) ethanols compounds were performed to obtain the best three compounds with high activity and the lowest toxicity. Toxicity prediction was conducted using Toxtree, pkCSM and PreADMET. The 2D structure of compounds were formed using ChemDraw. The decision tree approach was used in Toxtree application with endpoints including Cramer rules, Kroes TTC, carcinogenicity (genotoxic and non genotoxic) and in vitro mutagenicity. Graph based signature was used in pkCSM application with endpoints including mutagenicity, maximum daily dose, LD50 and hepatotoxicity. In PreADMET application, a method based on drugs similarity and ADMET properties was used with endpoints including mutagenicity, carcinogenicity to rat and mice. The results of data analysis showed that the best three anticancer compounds that have high activity and the lowest toxicity are compounds 14, 16 and 19.}
}