Approved Abstracts

Nuclear receptor superfamily structural diversity in Pacific Oyster: in silico analysis of estradiol binding candidates



Author(s): Madaloz TZ; Brascher TC; Santos K; Zacchi FL; Bainy ACD; Razzera G;
Presenter: Tâmela Zamboni Madaloz

Emerging pollutants, such as drugs and hormones, have been frequently reported in aquatic environments and pose risks when interacting with biomolecules. Xenobiotic compounds, such as 17-β-estradiol, modulate gene transcription of the nuclear receptor (NR) transcription factor superfamily. The binding mechanisms and modulation for NRs are poorly understood in aquatic invertebrates, such as the Pacific oyster, Crassostrea gigas, a species widely used in studies with biomarkers of aquatic contamination. The only non-vertebrate Estrogen Receptor (ER) that has been described so far, from C.gigas, was shown to be unable to bind estradiol due to the smaller binding cavity. Since other NRs may be modulated by estradiol, the present work aims to structurally characterize the NR superfamily of C. gigas, mapping potential estradiol binding targets. An in silico approach, using molecular 3D modeling, docking, and dynamics simulations were performed to investigate the interaction mechanisms of Pacific oyster NRs with 17-β-estradiol. From the 43 sequences identified as C. gigas NRs, the overall architecture of the LBD, containing all the structural elements neighboring the binding pocket, was encountered for 30 models. Quantitative criteria such as the Ramachandran plot were used to evaluate the quality and confidence of the models, showing that 90-98.2% of the residues were in favored regions, indicating the high quality of the modeled structures. The molecular docking assay testing the interaction of the 30 models with 17-β-estradiol indicated binding positions with the target molecule for 23 models. The analysis of docking positions was performed considering binding affinity (ΔG); ligand position compared to the control structure from human ER (PDB ID 1gwr), and identifying weak interactions between ligand and residues. The ΔG values ranged between -11.5 to -5.1 kcal/mol, and more than 70% presented values lower than -9.0, demonstrating similarity with the control structure, which re-docking showed a ΔG of -11.2 kcal/mol. According to the docking analysis, estradiol binding candidates among NRs of the Pacific oyster include CgNR1Ja, homologous to the DHR96 receptor of the invertebrate Daphnia pulex, which is described as containing a promiscuous binding site capable of binding with xenobiotic molecules such as estradiol. CgNR2E1 also demonstrated a favorable interaction with estradiol. This receptor has homologs in humans and Drosophila melanogaster, in both species acting as a transcriptional repressor in the nervous system. In humans, this receptor may present a large binding pocket with the potential to bind compounds with steroidal scaffolds. Protein-ligand complexes for the 23 models with possible interactions identified by docking analysis are currently being computer-simulated through molecular dynamics. These simulations provided information regarding the stability of the interaction through time, enabling a more reliable analysis to suggest binding candidates. In summary, the in silico structural characterization approach was able to provide structural information concerning Pacific oyster NR superfamily. Favorable binding poses and interactions were mapped, highlighting candidates for ligand-binding. Further simulations and analysis will assist in elucidating Pacific oyster NR targets for binding to the estradiol xenobiotic.

Keywords: Bioinformatics; Xenobiotic; Endocrine disruption

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