Chemical Informatics

Candidate Molecule Selection Based on In Silico Predicted ADMET Properties of 12 Indenoindole Derivatives

For considering future in vivo assays, it is necessary to investigate pharmacokinetic and toxicity profile of new chemical entities to select the best candidate(s) for further evaluations. Physicochemical parameters and ADMET (Absorption, Distribution, Metabolism, Elimination and Toxicity) properties of 12 indenoindole derivatives – identified as potent inhibitors of the ABCG2 protein - were predicted in silico with the Molinspiration and the ACD/Percepta softwares. The evaluation of mutagenicity and carcinogenicity was achieved by using the QSAR Toolbox software. Based on the exercise, i) two phenolic derivatives should not be metabolically activated by CYP enzymes according to the QSAR Toolbox software leading to a lower mutagenic risk, ii) compounds 2b, 2c could be excluded from further studies because of clastogenic risks and again compound 2c for a relatively low oral bioavailability, iii) one compound for its blood toxicity and five because for their pulmonary toxicity. Finally, six out of the 12 derivatives (1a, 1b, 2a, 2d, 2e and 2g), were predicted, in terms of ADMET properties, to be good candidates for further in vivo investigations.

Author(s):

Nathalie Guragossian, Gustavo Jabor Gozzi, Bruno Fouillet, Marie-Paule Gustin, Raphaël Terreux, Zouhair Bouaziz, Christelle Marminon, Joachim Jose, Attilio Di Pietro, Markku Pasanen and Marc Le Borgne

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