ESPE Abstracts (2016) 86 RFC1.1

Tracing the Glucocorticoid Receptor Evolutionary Pedigree: Insights from a Comprehensive Phylogenetic Analysis of the Full NR Super-Family

Dimitrios Vlachakisa, Nicolas C. Nicolaidesb,c, Louis Papageorgioua, Agaristi Lamprokostopoulouc & Evangelia Charmandarib,c


aBioinformatics and Medical Informatics Team, Biomedical Research Foundation of the Academy of Athens, Athens, Greece; bDivision of Endocrinology, Metabolism and Diabetes, First Department of Pediatrics, University of Athens Medical School, ‘Aghia Sophia’ Children’s Hospital, Athens, Greece; cDivision of Endocrinology and Metabolism, Biomedical Research Foundation of the Academy of Athens, Athens, Greece


Background: The nuclear receptor (NR) family comprises three main subfamilies: the steroid hormones receptors, the thyroid/retinoid hormone receptors and the orphan receptors. Proteins within the NR family share common domain architecture. These closely related receptors and their cognate ligand compounds play a key role in homeostasis, reproduction, growth and development. Despite their biological significance, their evolution and diversification remains to be elucidated.

Objective and hypotheses: To establish an in-depth phylogenetic tree of the NR family across all species in the tree of life in order to identify molecular and evolutionary traits specific to the glucocorticoid receptor (GR).

Methods and Results: Combinations of key terms were employed in order to identify relative NR and GR protein sequences on both primary and tertiary/ quaternary structural levels. Sequence data were collected from the NCBI Database. Two distinct datasets were prepared for the purposes of this study. The first dataset comprised of all NRs, which involved 84566 entries across all known receptor sub-classes. In the second dataset, 217 GR entries were collected and clustered in groups using both evolutionary and physicochemical criteria. The clustered groups were then blasted against the PDB in a query for X-ray solved structures as templates for a holistic 3D homology modeling experiment of the GR family. Both datasets were aligned using progressive methods. The phylogenetic analysis was conducted using the UPGMA distance method and the 3D modeling was performed using MOE.

Conclusion: Based on our comprehensive phylogenetic analysis of nuclear receptors, a reliable phylogeny “map” was constructed for GRs. It allowed to pinpoint evolutionary and structurally invariant patches on both the 1D and 3D level of the GR family, which led to the identification of structural ‘hotspots’ directly related to function that are of great interest as novel pharmacological targets.

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