PPARγ is the functioning receptor for the thiazolidinedione (TZD) class of anti-diabetes drugs including rosiglitazone and pioglitazone1. These drugs are full classical agonists for this nuclear receptor, but recent data has shown that many PPARγ-based drugs have a separate biochemical activity, blocking the obesity-linked phosphorylation of PPARγ by Cdk52. Here we describe novel synthetic compounds that have a unique mode of binding to PPARγ, completely lack classical transcriptional agonism and block the Cdk5-mediated phosphorylation in cultured adipocytes and in insulin-resistant mice. Moreover, one such compound, SR1664, has potent anti-diabetic activity while not causing the fluid retention and weight gain that are serious side effects of many of the PPARγ drugs. Unlike TZDs, SR1664 also does not interfere with bone formation in culture. These data illustrate that new classes of anti-diabetes drugs can be developed by specifically targeting the Cdk5-mediated phosphorylation of PPARγ.

T helper cells that produce Interleukin-17 (IL-17) (TH17 cells) are a recently identified CD4+ T-cell subset with characterized pathological roles in autoimmune diseases1–3. The nuclear receptors retinoic acid receptor-related orphan receptors α and γt (RORα and RORγt) have indispensible roles in the development of this cell type4–7. Here we present a first-in-class, high-affinity synthetic ligand, SR1001, specific to both RORα and RORγt that inhibits TH17 cell differentiation and function. SR1001 binds specifically to the ligand binding domains (LBDs) of RORα and RORγt inducing a conformational change within the LBD that encompasses repositioning of helix 12 leading to diminished affinity for coactivators and increased affinity for corepressors resulting in suppression of the receptors transcriptional activity. SR1001 inhibited the development of murine TH17 cells as demonstrated by inhibition of IL-17A gene expression and protein production. Additionally, SR1001 inhibited the expression of cytokines when added to differentiated murine or human TH17 cells. Finally, SR1001 effectively suppressed the clinical severity of autoimmune disease in mice. Thus, our data demonstrates the feasibility of targeting the orphan receptors RORα and RORγt to specifically inhibit TH17 cell differentiation and function and indicates that this novel class of compound has potential utility in the treatment of autoimmune diseases.

A large proportion of biomedical research and the development of therapeutics is focused on a small fraction of the human genome. In a strategic effort to map the knowledge gaps around proteins encoded by the human genome and to promote the exploration of currently understudied, but potentially druggable, proteins, the US National Institutes of Health launched the Illuminating the Druggable Genome (IDG) initiative in 2014. In this article, we discuss how the systematic collection and processing of a wide array of genomic, proteomic, chemical and disease-related resource data by the IDG Knowledge Management Center have enabled the development of evidence-based criteria for tracking the target development level (TDL) of human proteins, which indicates a substantial knowledge deficit for approximately one out of three proteins in the human proteome. We then present spotlights on the TDL categories as well as key drug target classes, including G protein-coupled receptors, protein kinases and ion channels, which illustrate the nature of the unexplored opportunities for biomedical research and therapeutic development.

The Library of Integrated Network-Based Cellular Signatures (LINCS) is an NIH Common Fund program that catalogs how human cells globally respond to chemical, genetic, and disease perturbations. Resources generated by LINCS include experimental and computational methods, visualization tools, molecular and imaging data, and signatures. By assembling an integrated picture of the range of responses of human cells exposed to many perturbations, the LINCS program aims to better understand human disease and to advance the development of new therapies. Perturbations under study include drugs, genetic perturbations, tissue micro-environments, antibodies, and disease-causing mutations. Responses to perturbations are measured by transcript profiling, mass spectrometry, cell imaging, and biochemical methods, among other assays. The LINCS program focuses on cellular physiology shared among tissues and cell types relevant to an array of diseases, including cancer, heart disease, and neurodegenerative disorders. This Perspective describes LINCS technologies, datasets, tools, and approaches to data accessibility and reusability.