Receptor structure-based discovery of non-metabolite agonists for the succinate receptor GPR91

Besides functioning as an intracellular metabolite, succinate acts as a stress-induced extracellular signal through activation of GPR91 (SUCNR1) for which we lack suitable pharmacological tools.Here we first determined that the cis conformation of the succinate backbone is preferred and that certain backbone modifications are allowed for GPR91 activation. Through receptor modeling over the X-ray structure of the closely related P2Y1 receptor, we discovered that the binding pocket is partly occupied by a segment of an extracellular loop and that succinate therefore binds in a very different mode than generally believed. Importantly, an empty side-pocket is identified next to the succinate binding site. All this information formed the basis for a substructure-based search query, which, combined with molecular docking, was used in virtual screening of the ZINC database to pick two serial mini-libraries of a total of only 245 compounds from which sub-micromolar, selective GPR91 agonists of unique structures were identified. The best compounds were backbone-modified succinate analogs in which an amide-linked hydrophobic moiety docked into the side-pocket next to succinate as shown by both loss- and gain-of-function mutagenesis. These compounds displayed GPR91-dependent activity in altering cytokine expression in human M2 macrophages similar to succinate, and importantly were devoid of any effect on the major intracellular target, succinate dehydrogenase.These novel, synthetic non-metabolite GPR91 agonists will be valuable both as pharmacological tools to delineate the GPR91-mediated functions of succinate and as leads for the development of GPR91-targeted drugs to potentially treat low grade metabolic inflammation and diabetic complications such as retinopathy and nephropathy

Biased Signaling of CCL21 and CCL19 Does Not Rely on N-Terminal Differences, but Markedly on the Chemokine Core Domains and Extracellular Loop 2 of CCR7

Chemokine receptors play important roles in the immune system and are linked to several human diseases. Targeting chemokine receptors have so far shown very little success owing to, to some extent, the promiscuity of the immune system and the high degree of biased signaling within it. CCR7 and its two endogenous ligands display biased signaling and here we investigate the differences between the two ligands, CCL21 and CCL19, with respect to their biased activation of CCR7. We use bystander bioluminescence resonance energy transfer (BRET) based signaling assays and Transwell migration assays to determine (A) how swapping of domains between the two ligands affect their signaling patterns and (B) how receptor mutagenesis impacts signaling. Using chimeric ligands we find that the chemokine core domains are central for determining signaling outcome as the lack of β-arrestin-2 recruitment displayed by CCL21 is linked to its core domain and not N-terminus. Through a mutagenesis screen, we identify the extracellular domains of CCR7 to be important for both ligands and show that the two chemokines interact differentially with extracellular loop 2 (ECL-2). By using in silico modeling, we propose a link between ECL-2 interaction and CCR7 signal transduction. Our mutagenesis study also suggests a lysine in the top of TM3, K1303.26, to be important for G protein signaling, but not β-arrestin-2 recruitment. Taken together, the bias in CCR7 between CCL19 and CCL21 relies on the chemokine core domains, where interactions with ECL-2 seem particularly important. Moreover, TM3 selectively regulates G protein signaling as found for other chemokine receptors.publishe

Visual and computational analysis of structure-activity relationships in high-throughput screening data

Novel analytic methods are required to assimilate the large volumes of structural and bioassay data generated by combinatorial chemistry and high-throughput screening programmes in the pharmaceutical and agrochemical industries. This paper reviews recent work in visualisation and data mining that can be used to develop structure-activity relationships from such chemical/biological datasets

Molecular dynamics-guided discovery of an ago-allosteric modulator for GPR40/FFAR1

The long-chain fatty acid receptor FFAR1/GPR40 binds agonists in both an interhelical site between the extracellular segments of transmembrane helix (TM)-III and TM-IV and a lipid-exposed groove between the intracellular segments of these helices. Molecular dynamics simulations of FFAR1 with agonist removed demonstrated a major rearrangement of the polar and charged anchor point residues for the carboxylic acid moiety of the agonist in the interhelical site, which was associated with closure of a neighboring, solvent-exposed pocket between the extracellular poles of TM-I, TM-II, and TM-VII. A synthetic compound designed to bind in this pocket, and thereby prevent its closure, was identified through structure-based virtual screening and shown to function both as an agonist and as an allosteric modulator of receptor activation. This discovery of an allosteric agonist for a previously unexploited, dynamic pocket in FFAR1 demonstrates both the power of including molecular dynamics in the drug discovery process and that this specific, clinically proven, but difficult, antidiabetes target can be addressed by chemotypes different from existing ligands

Biased Gs versus Gq proteins and ?-arrestin signaling in the NK1 receptor determined by interactions in the water hydrogen bond network

X-ray structures, molecular dynamics simulations, and mutational analysis have previously indicated that an extended water hydrogen bond network between trans-membranes I-III, VI, and VII constitutes an allosteric interface essential for stabilizing different active and inactive helical constellations during the seven-trans-membrane receptor activation. The neurokinin-1 receptor signals efficiently through Gq, Gs, and ?-arrestin when stimulated by substance P, but it lacks any sign of constitutive activity. In the water hydrogen bond network the neurokinin-1 has a unique Glu residue instead of the highly conserved AspII:10 (2.50). Here, we find that this GluII:10 occupies the space of a putative allosteric modulating Na+ ion and makes direct inter-helical interactions in particular with SerIII:15 (3.39) and AsnVII:16 (7.49) of the NPXXY motif. Mutational changes in the interface between GluII:10 and AsnVII:16 created receptors that selectively signaled through the following: 1) Gqonly; 2) ?-arrestin only; and 3) Gqand ?-arrestinbutnot through Gs. Interestingly, increased constitutive Gs but not Gq signaling was observed by Ala substitution of four out of the six core polar residues of the network, in particular SerIII:15. Three residues were essential for all three signaling pathways, i.e. the water-gating micro-switch residues TrpVI:13 (6.48) of the CWXP motif and TyrVII:20 (7.53) of the NPXXY motif plus the totally conserved AsnI:18 (1.50) stabilizing the kink in trans-membrane VII. It is concluded that the interface between position II:10 (2.50), III:15 (3.39), and VII:16 (7.49) in the center of the water hydrogen bond network constitutes a focal point for fine-tuning seven transmembrane receptor conformations activating different signal transduction pathways

The second intracellular loop of the calcitonin gene-related peptide receptor provides molecular determinants for signal transduction and cell surface expression

The calcitonin gene-related peptide (CGRP) receptor is a heterodimer of a family B G-protein-coupled receptor, calcitonin receptor-like receptor (CLR), and the accessory protein receptor activity modifying protein 1. It couples to Gs, but it is not known which intracellular loops mediate this. We have identified the boundaries of this loop based on the relative position and length of the juxtamembrane transmembrane regions 3 and 4. The loop has been analyzed by systematic mutagenesis of all residues to alanine, measuring cAMP accumulation, CGRP affinity, and receptor expression. Unlike rhodopsin, ICL2 of the CGRP receptor plays a part in the conformational switch after agonist interaction. His-216 and Lys-227 were essential for a functional CGRP-induced cAMP response. The effect of (H216A)CLR is due to a disruption to the cell surface transport or surface stability of the mutant receptor. In contrast, (K227A)CLR had wild-type expression and agonist affinity, suggesting a direct disruption to the downstream signal transduction mechanism of the CGRP receptor. Modeling suggests that the loop undergoes a significant shift in position during receptor activation, exposing a potential G-protein binding pocket. Lys-227 changes position to point into the pocket, potentially allowing it to interact with bound G-proteins. His-216 occupies a position similar to that of Tyr-136 in bovine rhodopsin, part of the DRY motif of the latter receptor. This is the first comprehensive analysis of an entire intracellular loop within the calcitonin family of G-protein-coupled receptor. These data help to define the structural and functional characteristics of the CGRP-receptor and of family B G-protein-coupled receptors in general. © 2006 by The American Society for Biochemistry and Molecular Biology, Inc

A novel method for mining highly imbalanced high-throughput screening data in PubChem

Motivation: The comprehensive information of small molecules and their biological activities in PubChem brings great opportunities for academic researchers. However, mining high-throughput screening (HTS) assay data remains a great challenge given the very large data volume and the highly imbalanced nature with only small number of active compounds compared to inactive compounds. Therefore, there is currently a need for better strategies to work with HTS assay data. Moreover, as luciferase-based HTS technology is frequently exploited in the assays deposited in PubChem, constructing a computational model to distinguish and filter out potential interference compounds for these assays is another motivation

Physiochemical property space distribution among human metabolites, drugs and toxins

<p>Abstract</p> <p>Background</p> <p>The current approach to screen for drug-like molecules is to sieve for molecules with biochemical properties suitable for desirable pharmacokinetics and reduced toxicity, using predominantly biophysical properties of chemical compounds, based on empirical rules such as Lipinski's "rule of five" (Ro5). For over a decade, Ro5 has been applied to combinatorial compounds, drugs and ligands, in the search for suitable lead compounds. Unfortunately, till date, a clear distinction between drugs and non-drugs has not been achieved. The current trend is to seek out drugs which show metabolite-likeness. In identifying similar physicochemical characteristics, compounds have usually been clustered based on some characteristic, to reduce the search space presented by large molecular datasets. This paper examines the similarity of current drug molecules with human metabolites and toxins, using a range of computed molecular descriptors as well as the effect of comparison to clustered data compared to searches against complete datasets.</p> <p>Results</p> <p>We have carried out statistical and substructure functional group analyses of three datasets, namely human metabolites, drugs and toxin molecules. The distributions of various molecular descriptors were investigated. Our analyses show that, although the three groups are distinct, present-day drugs are closer to toxin molecules than to metabolites. Furthermore, these distributions are quite similar for both clustered data as well as complete or unclustered datasets.</p> <p>Conclusion</p> <p>The property space occupied by metabolites is dissimilar to that of drugs or toxin molecules, with current drugs showing greater similarity to toxins than to metabolites. Additionally, empirical rules like Ro5 can be refined to identify drugs or drug-like molecules that are clearly distinct from toxic compounds and more metabolite-like. The inclusion of human metabolites in this study provides a deeper insight into metabolite/drug/toxin-like properties and will also prove to be valuable in the prediction or optimization of small molecules as ligands for therapeutic applications.</p

Advances and Challenges in Protein-Ligand Docking

Molecular docking is a widely-used computational tool for the study of molecular recognition, which aims to predict the binding mode and binding affinity of a complex formed by two or more constituent molecules with known structures. An important type of molecular docking is protein-ligand docking because of its therapeutic applications in modern structure-based drug design. Here, we review the recent advances of protein flexibility, ligand sampling, and scoring functions—the three important aspects in protein-ligand docking. Challenges and possible future directions are discussed in the Conclusion