A theoretical entropy score as a single value to express inhibitor selectivity

<p>Abstract</p> <p>Background</p> <p>Designing maximally selective ligands that act on individual targets is the dominant paradigm in drug discovery. Poor selectivity can underlie toxicity and side effects in the clinic, and for this reason compound selectivity is increasingly monitored from very early on in the drug discovery process. To make sense of large amounts of profiling data, and to determine when a compound is sufficiently selective, there is a need for a proper quantitative measure of selectivity.</p> <p>Results</p> <p>Here we propose a new theoretical entropy score that can be calculated from a set of IC₅₀data. In contrast to previous measures such as the 'selectivity score', Gini score, or partition index, the entropy score is non-arbitary, fully exploits IC₅₀data, and is not dependent on a reference enzyme. In addition, the entropy score gives the most robust values with data from different sources, because it is less sensitive to errors. We apply the new score to kinase and nuclear receptor profiling data, and to high-throughput screening data. In addition, through analyzing profiles of clinical compounds, we show quantitatively that a more selective kinase inhibitor is not necessarily more drug-like.</p> <p>Conclusions</p> <p>For quantifying selectivity from panel profiling, a theoretical entropy score is the best method. It is valuable for studying the molecular mechanisms of selectivity, and to steer compound progression in drug discovery programs.</p

Genomics of Signaling Crosstalk of Estrogen Receptor α in Breast Cancer Cells

BACKGROUND: The estrogen receptor alpha (ERalpha) is a ligand-regulated transcription factor. However, a wide variety of other extracellular signals can activate ERalpha in the absence of estrogen. The impact of these alternate modes of activation on gene expression profiles has not been characterized. METHODOLOGY/PRINCIPAL FINDINGS: We show that estrogen, growth factors and cAMP elicit surprisingly distinct ERalpha-dependent transcriptional responses in human MCF7 breast cancer cells. In response to growth factors and cAMP, ERalpha primarily activates and represses genes, respectively. The combined treatments with the anti-estrogen tamoxifen and cAMP or growth factors regulate yet other sets of genes. In many cases, tamoxifen is perverted to an agonist, potentially mimicking what is happening in certain tamoxifen-resistant breast tumors and emphasizing the importance of the cellular signaling environment. Using a computational analysis, we predicted that a Hox protein might be involved in mediating such combinatorial effects, and then confirmed it experimentally. Although both tamoxifen and cAMP block the proliferation of MCF7 cells, their combined application stimulates it, and this can be blocked with a dominant-negative Hox mutant. CONCLUSIONS/SIGNIFICANCE: The activating signal dictates both target gene selection and regulation by ERalpha, and this has consequences on global gene expression patterns that may be relevant to understanding the progression of ERalpha-dependent carcinomas

Medium Chain Fatty Acids Are Selective Peroxisome Proliferator Activated Receptor (PPAR) γ Activators and Pan-PPAR Partial Agonists

Thiazolidinediones (TZDs) act through peroxisome proliferator activated receptor (PPAR) γ to increase insulin sensitivity in type 2 diabetes (T2DM), but deleterious effects of these ligands mean that selective modulators with improved clinical profiles are needed. We obtained a crystal structure of PPARγ ligand binding domain (LBD) and found that the ligand binding pocket (LBP) is occupied by bacterial medium chain fatty acids (MCFAs). We verified that MCFAs (C8–C10) bind the PPARγ LBD in vitro and showed that they are low-potency partial agonists that display assay-specific actions relative to TZDs; they act as very weak partial agonists in transfections with PPARγ LBD, stronger partial agonists with full length PPARγ and exhibit full blockade of PPARγ phosphorylation by cyclin-dependent kinase 5 (cdk5), linked to reversal of adipose tissue insulin resistance. MCFAs that bind PPARγ also antagonize TZD-dependent adipogenesis in vitro. X-ray structure B-factor analysis and molecular dynamics (MD) simulations suggest that MCFAs weakly stabilize C-terminal activation helix (H) 12 relative to TZDs and this effect is highly dependent on chain length. By contrast, MCFAs preferentially stabilize the H2-H3/β-sheet region and the helix (H) 11-H12 loop relative to TZDs and we propose that MCFA assay-specific actions are linked to their unique binding mode and suggest that it may be possible to identify selective PPARγ modulators with useful clinical profiles among natural products

NFkappaB selectivity of estrogen receptor ligands revealed by comparative crystallographic analyses

Our understanding of how steroid hormones regulate physiological functions has been significantly advanced by structural biology approaches. However, progress has been hampered by misfolding of the ligand binding domains in heterologous expression systems and by conformational flexibility that interferes with crystallization. Here, we show that protein folding problems that are common to steroid hormone receptors are circumvented by mutations that stabilize well-characterized conformations of the receptor. We use this approach to present the structure of an apo steroid receptor that reveals a ligand-accessible channel allowing soaking of preformed crystals. Furthermore, crystallization of different pharmacological classes of compounds allowed us to define the structural basis of NFkappaB-selective signaling through the estrogen receptor, thus revealing a unique conformation of the receptor that allows selective suppression of inflammatory gene expression. The ability to crystallize many receptor-ligand complexes with distinct pharmacophores allows one to define structural features of signaling specificity that would not be apparent in a single structure.Kendall W Nettles, John B Bruning, German Gil, Jason Nowak, Sanjay K Sharma, Johnnie B Hahm, Kristen Kulp, Richard B Hochberg, Haibing Zhou, John A Katzenellenbogen, Benita S Katzenellenbogen, Younchang Kim, Andrzej Joachimiak & Geoffrey L Green

Coupling of receptor conformation and ligand orientation determine graded activity

Small molecules stabilize specific protein conformations from a larger ensemble, enabling molecular switches that control diverse cellular functions. We show here that the converse also holds true: the conformational state of the estrogen receptor can direct distinct orientations of the bound ligand. 'Gain-of-allostery' mutations that mimic the effects of ligand in driving protein conformation allowed crystallization of the partial agonist ligand WAY-169916 with both the canonical active and inactive conformations of the estrogen receptor. The intermediate transcriptional activity induced by WAY-169916 is associated with the ligand binding differently to the active and inactive conformations of the receptor. Analyses of a series of chemical derivatives demonstrated that altering the ensemble of ligand binding orientations changes signaling output. The coupling of different ligand binding orientations to distinct active and inactive protein conformations defines a new mechanism for titrating allosteric signaling activity.John B. Bruning, Alexander A. Parent, German Gil, Min Zhao, Jason Nowak, Margaret C. Pace, Carolyn L. Smith, Pavel V. Afonine, Paul D. Adams, John A. Katzenellenbogen and Kendall W. Nettle