Related Experiment Video
Updated: Sep 29, 2025

A General Method for Detecting Nitrosamide Formation in the In Vitro Metabolism of Nitrosamines by Cytochrome P450s
Published on: September 25, 2017
Machine learning predictive classification models for the carcinogenic activity of activated metabolites derived from
Andrés Halabi1, Elizabeth Rincón1, Eduardo Chamorro2
1Facultad de Ciencias, Instituto de Ciencias Químicas, Universidad Austral de Chile, Independencia 631, Valdivia 5090000, Chile.
Abstract:
A 3D-QSAR study based on DFT descriptors and machine learning calculations is presented in this work. Our goal has been to build predictive models for classifying the carcinogenic activity of a set of aromatic amines (AA) and nitroaromatic (NA) compounds. As the main result, we stress that calculations must consider both the activated metabolites (derived from AA and NA species) and the water solvent to obtain reliable predictive classification models. We have obtained eight decision tree models that presented an accuracy of over 90% by using either Gázquez-Vela chemical potential (μ+) or the chemical hardness (η) of the activated metabolites in aqueous solvent.
More Related Videos
Related Concept Videos
Physical Properties of Amines
Mutagenicity and Carcinogenicity
2° Amines to N-Nitrosamines: Reaction with NaNO2
Nomenclature of Aryl and Heterocyclic Amines
Basicity of Heterocyclic Aromatic Amines
Amines: Introduction

