Human Nuclear Receptor (NR) family play significant roles in critical cellular functions such as development, metabolism, and physiology. Disruptions in their DNA binding specificities, due to either mutation in the NR or in the associated DNA regulatory sites, have been implicated in has been implicated in several diseases including glaucoma, cataract, retinal diseases, asthma, inflammation, autoimmune and developmental disorders, hormonal imbalances, obesity, cancers and diabetes. Human NRs are some of the most effective drug targets and the focus of multi-billion dollar pharmaceuticals. A comprehensive understanding of NR gene targeting in vivo, especially when bound to different physiological ligands as well as widely prescribed drugs that have different impact in different individuals and different cell types, will result in a highly informed approach to drug development and deployment. State-of-the-art methods are inadequate to fully characterize the DNA cognate sites of NRs because they often bind as cooperative homotypic or heterotypic oligomers with other TFs. Additionally, the site preferences of NRs are modulated in non-obvious ways by certain natural ligands and related synthetic drugs. The state-of-the-art methods also often ignore the medium-to-low sequence specificity differences of closely related TFs, which in turn are crucial to understanding the vital differences in the biological functions among the NRs. This project?s first aim is to develop innovative computational approaches to elucidate the complex binding characteristics of NRs and to identify the vital differences in binding profiles of closely related NRs. The analysis will utilize recently collected experimental cognate site identification (CSI) data from high throughput sequencing of DNA-interactomes of all full-length functional human NRs in the context of whole cell extracts. We also propose to rigorously evaluate the impact of a wide-range of physiological small molecule ligands as well as prescribed therapeutics/drugs on NR-DNA interactomes. The computationally determined sequence preferences will be experimentally tested using biochemical, biophysical and cell biological assays. Thus we will integrate computation and experimental validation to decipher how NRs target the genome and manifest their biological roles. Moreover, the efforts will enable precision-medicine by defining the impact of current therapeutics in guiding NRs in the context of individual genomes.
A malfunction in regulatory circuit of many transcription factors have been implicated as the primary cause of a wide array of diseases including developmental disorders, inflammation, allergies and asthma, cancers, diabetes, cardiovascular problems, and neurological disorders. As a result, identifying the binding preferences of transcription factors is crucial for targeting therapeutic interventions for diseases. The major goal of this project is to computationally detail and experimentally validate the complex DNA binding patterns of Nuclear Receptor (NR) class of transcription factors, with an especial focus on unmasking the impact of co-factors, natural ligands, as well as synthetic therapeutic molecules and widely prescribed drugs.
| Bhimsaria, Devesh; Rodríguez-Martínez, José A; Pan, Junkun et al. (2018) Specificity landscapes unmask submaximal binding site preferences of transcription factors. Proc Natl Acad Sci U S A 115:E10586-E10595 |
