Connecting the functional effects of drugs to how they change PPAR? The most effective drugs for treating and preventing Type II diabetes are those that bind to a protein named PPAR?. PPAR? is a transcription factor critical for the production and maintenance of adipocytes and bone cells and it affects immune function. Some PPAR? dependent effects can be beneficial to people with diabetes and some are not. The challenge is to develop PPAR? binding drugs that retain the unique and robust anti-diabetic effects but reduce the side effects of heart failure, weight gain and bone loss. Current research indicates that it may be possible to achieve separation of unwanted and wanted effects by targeting PPAR? with the right drug. This concept is supported by the fact that animal studies show some new PPAR? drugs activate distinct gene sets from currently prescribed drugs. However, how different drugs uniquely change PPAR? in order to produce these drug specific effects are unknown. Development of improved anti-diabetic PPAR? drugs is more likely when it is known how drugs change PPAR? and how these changes produce functional changes such as changes in gene expression. Understanding how ligands produce function in PPAR? and closely related proteins is the long term goal of the principle investigator (PI). This knowledge will aid in development of better drugs for the whole family of PPAR? like proteins (nuclear receptors) which are the target of ~13% of FDA approved drugs. Recently we have discovered that a large region of PPAR? exists in at least two conformations in solution alone or when bound to less efficacious drugs, however one PPAR conformation is detected when bound to a ligand that induces high transcription (Hughes et al. 2012). Importantly, these data are time consuming and expensive to obtain and only indicate that internal movement exists with little other detail. To better understand the link between PPAR?s internal motion and its function in cells we have developed low- cost, rapid NMR methods that can be used on large complexes and a NMR line shape analysis program which reveal in detail the range of conformations present (i.e. the conformational ensemble) at one site within the flexible region of PPAR?. These methods reveal conformational complexity that would be very difficult to observe using other NMR methods (manuscript in preparation) and allow characterization of a sufficient number of PPAR? drugs to draw statistically meaningful conclusions about any correlation between drug induced changes to PPAR? and changes in gene expression in cells. During the independent phase (aim 2) of the project the amount of NMR probe locations will be expanded (from the single current location) to get a more complete picture of PPAR?'s conformational ensemble in different areas. Additionally we will study PPAR? in the two main forms that it is found in the body 1) full length PPAR? (FL-PPAR?) and 2) the full-length heterodimer complex, which consists of PPAR?, RXR? and DNA. This work will reveal in unprecedented detail how ligands affect the range of related structures that comprise the conformational ensemble of PPAR?. However, they will not detect ligand-induced changes in PPAR?'s small fast movements (i.e. conformational entropy) that may be critical to how ligands produce effects in humans. To study these movements the PI will be trained in using molecular dynamics simulations. These simulations will be checked against experiment where possible using NMR. These data will be used to estimate the average regional change in the small fast internal movement of PPAR? (conformational entropy) that occurs when a drug binds PPAR. All of these measurements of drug-induced changes in PPAR? will be tested for correlation with functional outcomes such as dimerization with FL-RXR?, recruitment of coregulator peptides and gene expression in adipocytes. In order to fully utilize these recent advances and to build the best possible model of how PPAR dynamics and conformation leads to function the PI needs protected time for training in molecular dynamics simulation. The advisory team, which includes Dr. Cheatham, will provide expert guidance in this area. During the mentored portion of the grant (aim 1) the PI will continue to receive guidance in NMR and protein molecular dynamics simulations from collaborators (Drs. Art Palmer and Mark Rance), in addition to the PI's primary mentor Dr. Kojetin. The PI will also receive training in the methods and analysis of PPAR? drug effects on target gene expression in cells from Dr. Griffin (co-mentor). The Scripps Research Institute in Florida (TSRI) has seven groups (Nettles, Griffin, Kojetin, Kameneka, Solt, Rousch and Smith) that study nuclear receptors. Four of these groups are currently using different approaches and methods for answering important questions about PPAR?. This makes collaboration natural and provides an excellent environment in which to receive the training necessary to sustain independent research in this area. The PI has degrees in physics and biology which has allowed him to quickly acquire expertise in many areas of nuclear magnetic resonance (NMR) of proteins and several other biophysical and biology techniques during his 3 years of training at TSRI and provides a breadth of training that will be essential for connecting the biophysics and thermodynamics of PPAR movement and structure to functional outcomes.
Current insulin sensitizing drugs bind PPARg (a protein), helping treat diabetes but also causing weight gain and heart failure in some patients. In this work we will better define the ligand-induced changes in PPAR? structure and internal movements. Improved understanding of these drugs change PPAR? will allow development of effective anti-diabetic drugs which only induce a subset of wanted effects.
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|Kojetin, Douglas J; Matta-Camacho, Edna; Hughes, Travis S et al. (2015) Structural mechanism for signal transduction in RXR nuclear receptor heterodimers. Nat Commun 6:8013|
|Hughes, Travis S; Wilson, Henry D; de Vera, Ian Mitchelle S et al. (2015) Deconvolution of Complex 1D NMR Spectra Using Objective Model Selection. PLoS One 10:e0134474|
|Marciano, David P; Kuruvilla, Dana S; Boregowda, Siddaraju V et al. (2015) Pharmacological repression of PPARÎ³ promotes osteogenesis. Nat Commun 6:7443|