The overall goal of this proposal is to define structural rules that govern how the nuclear receptor (NR) superfamily of 48 human transcription factors impact mammalian physiology. There is currently very little known about the structural features that allow small molecule NR ligands to induce specific signaling outcomes, and to date there are only structures of NR sub-regions and domains. We hypothesize that this nuclear receptor (NR) signaling code is defined by interdomain communication with the NR, and its modulation by specific interacting proteins, which are also the effectors of NR signaling, such as transcriptional co-regulator enzymes. It is critical to study complexes both because 1) they are the physiologically relevant structure for a signaling scaffold protein;and 2) co-regulator proteis can stabilize unstructured regions or interdomain interactions and facilitate obtaining structural information. To date, there is only one multi-domain NR complex characterized by x-ray crystallography. A significant barrier to obtaining structures of multi-domain NR constructs has been the conformational flexibility in the different domains, which has been solved for individual domains by addition of interacting molecules, including ligands, DNA, and small peptides. Importantly, only a small subset of interacting molecules are efficient in promoting crystallization, requiring the ability to assay many permutations. A PSI biology consortium is uniquely designed to test many permutations of cloning, expression, and crystallization. Our unique contribution is a high throughput NR drug discovery and structure based design platform, which affords us the expertise to both define optimal interaction molecules and complexes, but also the diversity of approaches for functional validation of resulting structures. We break up the work into two target streams: Target Stream 1 represents the full length NRs, which can be rapidly and directly submitted to the collaborative PSI center. We will work closely with the PSI center to implement a collaborative high throughput platform for salvage and optimization of protein expression. We will use our unique robotic Cell Based Screening Core to implement high throughput biochemistry assays to characterize protein quality, and to define optimal combinations of interacting molecules to promote crystallization, including ligands, DNA, and small NR box peptides. Target Stream 2 focuses on NR complexes. Starting from the list of 350 published NR coregulators, we will characterize those that directly interact with unstructured regions or multiple NR domains, and optimize complex architecture for crystallization for submission to the PSI center. The resulting structures will serve as the basis for functional studies on interdomain communication, allostery, and NR-complex signaling pathways, thus completing the loop in using structure to delineate the nuclear receptor signaling code. Importantly, the proteins and complexes produced by the PSI center will also be used to define structural features of allosteric signaling using our automated high throughput platform for assaying conformational dynamics with hydrogen/deuterium exchange mass spectrometry (HDX).

Public Health Relevance

Nuclear receptors are a family of 48 proteins that control endocrine and metabolic physiology by regulating gene expression, and control of other cellular function such as signal transduction. These activities occur by acting as a scaffold to recruit enzymes and other proteins to DNA, regulating the reading of the DNA code in each cell and thus controlling cellular functions. Our proposed work is to obtain structures of nuclear receptors in complex with known interacting proteins using a consortium with the NIH structural genomics, PSI: Biology network.

National Institute of Health (NIH)
National Institute of General Medical Sciences (NIGMS)
Research Project--Cooperative Agreements (U01)
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Special Emphasis Panel (ZGM1-CBB-0 (BP))
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Preusch, Peter C
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Scripps Florida
United States
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Nwachukwu, Jerome C; Southern, Mark R; Kiefer, James R et al. (2013) Improved crystallographic structures using extensive combinatorial refinement. Structure 21:1923-30