In this thesis, allosteric activation of PPARα-RXRα heterodimer was studied with MD simulation systems consisting of the LBDs of each receptor. The choice of this approach was determined by the availability of the crystal structures at the time when these simulations were started and, in addition, the availability of
computational capacity. With the current knowledge, what can be said about the approach in general?
The crystal structures of full length PPARγ-RXRα heterodimer showed that there is an interaction between the PPARγ LBD and the RXRα DBD (Chandra et al., 2008).
These structures suggested that focusing solely on the interplay between the LBDs in the heterodimer cannot provide a full explanation for the mechanism of NR activation. In addition, DNA binding has been shown to stabilise the PPARγ-RXRα heterodimer interface and to affect coregulator binding (de Vera, Ian Mitchelle S et al., 2017; Bernardes et al., 2012; Zhang et al., 2011; Hall et al., 2002). Furthermore, MD simulations of PPARγ have shown different kinds of correlated movements as a LBD monomer, as compared to the situation with a full length receptor in a heterodimeric complex (Ricci et al., 2016). Unfortunately, a heterodimer of LBDs was not included in that comparison.
As a mediator of allosteric signals, Ricci et al. emphasized the role of PPARγ
-loop, which is a flexible loop area connecting helices helix 2’ and helix 3 (Ricci et al., 2016). They also suggested that this area might be important as an activation mechanism of partial agonists, which do not make any direct contact with helix 12.
The movement of these regions was found to be correlated with the PPARγ-DBD movements, and the authors speculated that the -loop area may function as a molecular switch, modulating PPARγ function in response to the dynamics of PPARγ-DBD. Obviously, the effects of DBD dynamics cannot be seen in simulations with only the LBD-LBD heterodimer, suggesting that these kinds of simulations may give false or at least an incomplete picture of the effects induced by a ligand.
On the other hand, even a complex with full length receptors and DNA is still a simplification, and all the consequences of that specific choice of inclusion and exclusion of elements are not known. For example, it was evident in the
simulations made by Ricci et al. that the DNA is bending; its motions have a major impact on the dynamics of the whole complex, and these motions are correlated with those of the LBDs. However, it is not known how natural the movements and bending of the DNA are in these simulations, because the DNA is modelled as a relatively short piece instead of a huge macromolecule bound to many proteins such as is the case in real life. While it is evident that in a simulation, some simplification is always needed, the simulation system must be constructed to include all parts that may have an impact on the results, within the limitations of available knowledge of structures and computational capacity.
At the time when the work (I) was started, the computational capacity for MD simulations was in general much less impressive than it is today. UNIX based workstations were still in use and only slowly being replaced with PC computers running Linux. The research plan for the work (I) was motivated by a grant
provided by an association of European supercomputing centers, which allowed me to work in Vrije Universiteit Amsterdam for three months and to use the high-performance computing facilities of a local super computing center. I was able to run nanosecond-scale simulations for a protein complex in a water box and to do that in ten parallel runs for four systems. That demanded a lot of computing power at a time when a simulation with only a part of the protein moving was still a valid option to consider.
In addition to the computational capacity, also methods have developed.
Thanks to the development of new algorithms, it is possible to use longer time steps, which also make the simulation clock go faster and allow observation of longer time scale phenomena (Hopkins et al., 2015). Today, conducting MD simulations with a microsecond time scale seem to be quite common and even some millisecond simulations have been reported. It would be interesting to now repeat the simulations conducted in work (I), but this time using the full-length structure with a piece of DNA and a longer time scale to allow the allosteric signalling to take place.
Although the patenting of the novel AR binders was successful, further
commercial development of the compounds failed. Even though the exact reasons for this failure are unknown, it can be speculated that a better bioavailability after oral administration could have increased the commercial interest. These
compounds could be developed further e.g. by substituting the aliphatic ring structure. However, this kind of project would require a clear sign of interest from a pharmaceutical company capable of moving forward the development process.
8 CONCLUSIONS AND FUTURE PROSPECTS
The following conclusions can be drawn from this thesis:
1) The molecular level mechanism of allosteric activation in the PPARα-RXRα heterodimer was examined with molecular dynamics. The study revealed that allosteric activation of permissive heterodimers may result from PPARα co-activator binding site stabilization upon ligand binding to the heterodimeric partner RXRα. However, further research is still needed to understand the role of DBDs, co-activator proteins and DNA binding in the allosteric mechanism. In addition, the impact of different types of ligands on permissivity needs further research.
2) ERα and ERβ binding compounds were evaluated with molecular docking to explain their observed binding affinities and activities. Single amino acid
differences were found to contribute to the binding orientation of the compounds and selectivity between ERα and ERβ. This information can be used to develop further these or similar compounds, to increase their affinity or selectivity at different ER subtypes.
3) A rational design approach was used to design novel structures for AR binders, by combining the existing features of ER binders, AR binders and new compound structures. In experimental testing, these compounds were found to bind to AR with high affinity and to inhibit AR activation comparably or better than the existing AR antagonists used in clinical practice.
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