Computational Approaches for the Prediction of Environmental Transformation Products: Chlorination of Steroidal Enones.

ABSTRACT: There is growing interest in the fate and effects of transformation products generated from emerging pollutant classes, and new tools that help predict the products most likely to form will aid in risk assessment. Here, using a family of structurally related steroids (enones, dienones, and trienones), we evaluate the use of density functional theory to help predict products from reaction with chlorine, a common chemical disinfectant. For steroidal dienones (e.g., dienogest) and trienones (e.g., 17β-trenbolone), computational data support that reactions proceed through spontaneous C4 chlorination to yield 4-chloro derivatives for trienones and, after further reaction, 9,10-epoxide structures for dienones. For testosterone, a simple steroidal enone, in silico predictions suggest that C4 chlo

SUBMITTER: Knutson CJ 

PROVIDER: S-EPMC8567416 | biostudies-literature | 2021 Nov

REPOSITORIES: biostudies-literature