Investigation of the S427F oncogenic mutation effects on the RXRα structure and dynamics

Postgraduate Thesis uoadl:2879923 293 Read counter

Unit:
Κατεύθυνση Πληροφορική στην Ιατρική
Πληροφορική
Deposit date:
2019-07-30
Year:
2019
Author:
Stergiou Georgia
Supervisors info:
Δρ. Ζωή Κούρνια, Ερευνήτρια Γ’, Ίδρυμα Ιατροβιολογικών Ερευνών Ακαδημίας Αθηνών (ΙΙΒΕΑΑ)
Original Title:
Investigation of the S427F oncogenic mutation effects on the RXRα structure and dynamics
Languages:
English
Translated title:
Investigation of the S427F oncogenic mutation effects on the RXRα structure and dynamics
Summary:
Retinoid X Receptor alpha (RXRα) is a nuclear hormone receptor of the vitamin A metabolite, 9-cis Retinoic Acid (RA). When bound to 9-cis RA, RXRα can activate the transcription of specific genes by serving either as an obligate heterodimer partner for many nuclear receptors (NRs) or as a homodimer partner. These dimers play a significant role in many physiological conditions such as regulation of metabolic rate, cell growth and differentiation. However, some of them are involved in pathological conditions such as premature birth, skin deceases and cancer development.
Studies have shown that 5-8% of bladder cancer patients bear the S427F single point mutation on RXRα, where a serine is replaced by phenylalanine at amino acid position 427. Biological experiments demonstrated that this mutation increases the expression of genes regulated by the Peroxisome Proliferator-Activated Receptor (PPAR). PPAR, in turn, switches on genes that aid cancer cells growth. Although valuable, biochemical studies aimed at determining the exact molecular mechanism of how the S427F mutation exerts its oncogenic action on RXRα in relation to its partners lack sufficient resolution for investigating the detailed underlying molecular interactions that bring about the observed result. Computational experiments such as Molecular Dynamics simulations (MD) together with atomic-level detailed experiments such as X-ray crystallography supplement biological experiments as they provide atomic resolution of the conformational changes that biomolecules undergo during a biological process. With the use of MD simulations, details of conformational changes are sampled to clarify mechanistic characteristics of biological processes that may otherwise be elusive.
In the present study, following up on a series of experiments that showed that the mutant RXRα inhibits the transcription of genes regulated by the RXRα homodimer, we investigated the effects of the S427F mutation on the structure and dynamics of the RXRα homodimer in the presence and absence of the ligands 9-cis RA. MD simulations were performed in order to elucidate the structural and dynamical consequences of this oncogenic mutation on the RXRα protein and its interactions within both Wild Type (WT) and mutant RXRα homodimers. Moreover, control simulations were performed to compare with previously reported data from the WT and mutant RXRα-PPARγ heterodimer. Results were also compared with previously performed RAR-RXRα heterodimer simulations. Furthermore, Dynamical Network Analysis was used to illustrate differences in the inter-residue pathways of the three dimers, in order to examine if there is a disruption in the communication.
Our results show that the mutation S427F does not affect the dimerization ability of the RXRα homodimer neither in the presence nor the absence of the endogenous ligand 9-cis RA. However, further analysis of the apo mutant demonstrates an increase of the solvent accessible surface area of the binding site in both monomers of the dimer in the absence of the ligands compared to the WT protein. This fact could prohibit the ligand 9-cis RA from binding resulting to a loss of transcriptional activity for RXRα. Finally, we validated our results analyzing the findings of the simulated RXRα-PPARγ heterodimer and compared to previous RAR-RXRα simulations, and finding that the two calculations are in agreement.
Main subject category:
Science
Keywords:
RXRα, PPARγ, bladder cancer, molecular dynamics, dynamical network analysis
Index:
Yes
Number of index pages:
11
Contains images:
Yes
Number of references:
103
Number of pages:
97
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