Significance Inflammation is a critical contributor to the pathogenesis of metabolic disorders associated with obesity. A group of molecules crucial in regulating the immune system are costimulatory molecules, including CD40. Our current study shows that CD40 acts as a double-edged sword in the metabolic syndrome through the initiation of differential signaling cascades. The CD40-TNF receptor-associated factor (TRAF) 2/3/5 signaling pathway protects against metabolic dysfunction and inflammation associated with obesity; conversely, the CD40-TRAF6 pathway contributes to the detrimental consequences of obesity. In the present study, we therefore designed, validated, and used a small-molecule inhibitor that blocks CD40-TRAF6 interactions. The improvement of insulin resistance by this specific CD40-TRAF6 inhibitor could represent a therapeutic breakthrough in the field of immunometabolism.

BackgroundDisrupting the costimulatory CD40-CD40L dyad reduces atherosclerosis, but can result in immune suppression. The authors recently identified small molecule inhibitors that block the interaction between CD40 and tumor necrosis factor receptor-associated factor (TRAF) 6 (TRAF-STOPs), while leaving CD40-TRAF2/3/5 interactions intact, thereby preserving CD40-mediated immunity.ObjectivesThis study evaluates the potential of TRAF-STOP treatment in atherosclerosis.MethodsThe effects of TRAF-STOPs on atherosclerosis were investigated in apolipoprotein E deficient (Apoe−/−) mice. Recombinant high-density lipoprotein (rHDL) nanoparticles were used to target TRAF-STOPs to macrophages.ResultsTRAF-STOP treatment of young Apoe−/− mice reduced atherosclerosis by reducing CD40 and integrin expression in classical monocytes, thereby hampering monocyte recruitment. When Apoe−/− mice with established atherosclerosis were treated with TRAF-STOPs, plaque progression was halted, and plaques contained an increase in collagen, developed small necrotic cores, and contained only a few immune cells. TRAF-STOP treatment did not impair “classical” immune pathways of CD40, including T-cell proliferation and costimulation, Ig isotype switching, or germinal center formation, but reduced CD40 and β2-integrin expression in inflammatory monocytes. In vitro testing and transcriptional profiling showed that TRAF-STOPs are effective in reducing macrophage migration and activation, which could be attributed to reduced phosphorylation of signaling intermediates of the canonical NF-κB pathway. To target TRAF-STOPs specifically to macrophages, TRAF-STOP 6877002 was incorporated into rHDL nanoparticles. Six weeks of rHDL-6877002 treatment attenuated the initiation of atherosclerosis in Apoe−/− mice.ConclusionsTRAF-STOPs can overcome the current limitations of long-term CD40 inhibition in atherosclerosis and have the potential to become a future therapeutic for atherosclerosis.

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The CD154-CD40 receptor complex plays a pivotal role in several inflammatory pathways. Attempts to inhibit the formation of this complex have resulted in systemic side effects. Downstream inhibition of the CD40 signaling pathway therefore seems a better way to ameliorate inflammatory disease. To relay a signal, the CD40 receptor recruits adapter proteins called tumor necrosis factor receptor-associated factors (TRAFs). CD40-TRAF6 interactions are known to play an essential role in several inflammatory diseases. We used in silico, in vitro, and in vivo experiments to identify and characterize compounds that block CD40-TRAF6 interactions. We present in detail our drug docking and optimization pipeline and show how we used it to find lead compounds that reduce inflammation in models of peritonitis and sepsis. These compounds appear to be good leads for drug development, given the observed absence of side effects and their demonstrated efficacy for peritonitis and sepsis in mouse models.

The activation mechanism of class B G-protein-coupled receptors (GPCRs) remains largely unknown. To characterize conformational changes induced by peptide hormones, we investigated interactions of the class B corticotropin-releasing factor receptor type 1 (CRF1R) with two peptide agonists and three peptide antagonists obtained by N-truncation of the agonists. Surface mapping with genetically encoded photo-crosslinkers and pair-wise crosslinking revealed distinct footprints of agonists and antagonists on the transmembrane domain (TMD) of CRF1R and identified numerous ligand-receptor contact sites, directly from the intact receptor in live human cells. The data enabled generating atomistic models of CRF- and CRF(12-41)-bound CRF1R, further explored by molecular dynamics simulations. We show that bound agonist and antagonist adopt different folds and stabilize distinct TMD conformations, which involves bending of helices VI and VII around flexible glycine hinges. Conservation of these glycine hinges among all class B GPCRs suggests their general role in activation of these receptors.DOI: http://dx.doi.org/10.7554/eLife.27711.001

The pharmacophore concept is of central importance in computer-aided drug design (CADD) mainly because of its successful application in medicinal chemistry and, in particular, high-throughput virtual screening (HTVS). The simplicity of the pharmacophore definition enables the complexity of molecular interactions between ligand and receptor to be reduced to a handful set of features. With many pharmacophore screening softwares available, it is of the utmost interest to explore the behavior of these tools when applied to different biological systems. In this work, we present a comparative analysis of eight pharmacophore screening algorithms (Catalyst, Unity, LigandScout, Phase, Pharao, MOE, Pharmer, and POT) for their use in typical HTVS campaigns against four different biological targets by using default settings. The results herein presented show how the performance of each pharmacophore screening tool might be specifically related to factors such as the characteristics of the binding pocket, the use of specific pharmacophore features, and the use of these techniques in specific steps/contexts of the drug discovery pipeline. Algorithms with rmsd-based scoring functions are able to predict more compound poses correctly as overlay-based scoring functions. However, the ratio of correctly predicted compound poses versus incorrectly predicted poses is better for overlay-based scoring functions that also ensure better performances in compound library enrichments. While the ensemble of these observations can be used to choose the most appropriate class of algorithm for specific virtual screening projects, we remarked that pharmacophore algorithms are often equally good, and in this respect, we also analyzed how pharmacophore algorithms can be combined together in order to increase the success of hit compound identification. This study provides a valuable benchmark set for further developments in the field of pharmacophore search algorithms, e.g., by using pose predictions and compound library enrichment criteria.

In order to boost the identification of low-molecular-weight drugs on protein–protein interactions (PPI), it is essential to properly collect and annotate experimental data about successful examples. This provides the scientific community with the necessary information to derive trends about privileged physicochemical properties and chemotypes that maximize the likelihood of promoting a given chemical probe to the most advanced stages of development. To this end we have developed iPPI-DB (freely accessible at http://www.ippidb.cdithem.fr), a database that contains the structure, some physicochemical characteristics, the pharmacological data and the profile of the PPI targets of several hundreds modulators of protein–protein interactions. iPPI-DB is accessible through a web application and can be queried according to two general approaches: using physicochemical/pharmacological criteria; or by chemical similarity to a user-defined structure input. In both cases the results are displayed as a sortable and exportable datasheet with links to external databases such as Uniprot, PubMed. Furthermore each compound in the table has a link to an individual ID card that contains its physicochemical and pharmacological profile derived from iPPI-DB data. This includes information about its binding data, ligand and lipophilic efficiencies, location in the PPI chemical space, and importantly similarity with known drugs, and links to external databases like PubChem, and ChEMBL.

Recently, a novel negative allosteric modulator (NAM) of the D-like dopamine receptors 1 was identified through virtual ligand screening. This ligand comprises a thieno[2,3- d]pyrimidine scaffold that does not feature in known dopaminergic ligands. Herein, we provide pharmacological validation of an allosteric mode of action for 1, revealing that it is a NAM of dopamine efficacy and identify the structural determinants of this allostery. We find that key structural moieties are important for functional affinity and negative cooperativity, while functionalization of the thienopyrimidine at the 5- and 6-positions results in analogues with divergent cooperativity profiles. Successive compound iterations have yielded analogues exhibiting a 10-fold improvement in functional affinity, as well as enhanced negative cooperativity with dopamine affinity and efficacy. Furthermore, our study reveals a fragment-like core that maintains low μM affinity and robust negative cooperativity with markedly improved ligand efficiency.