Endocrine disruption study of active sunscreens´s compounds by docking and molecular dynamics simulations

Abstract

Abstract Context: The use of sunscreens is important in reducing the harmful effects caused by UV radiation. When applied in personal care, the sunscreens ingredients can assume inappropriate destinations, such as cutaneous permeation and bioaccumulation, which may have adverse impacts on human health and the environment. Information on the endocrine disrupting risks of sunscreen active ingredients is not satisfactory, requiring studies that elucidate ligand-receptor recognition. This work investigated the probabilities of interaction of nuclear receptors with commercially available UV filters and natural molecules, used in sunscreens products, seeking to understand their health risk. A further exploration was performed together with the activating ligand testosterone and the endocrine disruptor Bisphenol-A, analyzing the interaction mechanisms by molecular docking. The target was the androgen receptor (AR), which in excessive activation can trigger prostatic hyperplasia and cancer. The results show interaction with the activation site of AR, similar to the AR-Testosterone complex and Bisphenol-A. To understand the magnitude of the interactions, molecular dynamics simulations and binding energy calculations were performed on selected complexes showing changes in the AR activation pocket. This study provided relevant information for the development of safer and less toxic sunscreens Methods: After computationally screening of ligands using the tool available on the web http://endocrinedisruptome.ki.si/, the androgen receptor was selected as a protein target. 3D structures of the ligands were prepared in Avogadro ® and optimized with semi-empirical method PM7 by MOPAC®. Next, docking was performed with AutoDockTools1.5.7®, and the best poses of the selected complexes were submitted to molecular dynamics simulations using the GROMACS software, with the OPLS/AA force field. The simulation trajectory frames were analyzed and used to calculate the MM-PBSA. Results were analyzed using xmgrace and Discovery Studio Visualizer® software.