Mapping the Binding Sites of UDP and Prostaglandin E2 Glyceryl Ester in the Nucleotide Receptor P2Y6.

Cyclooxygenase-2 catalyzes the biosynthesis of prostaglandins from arachidonic acid and the biosynthesis of prostaglandin glycerol esters (PG-Gs) from 2-arachidonoylglycerol. PG-Gs are mediators of several biological actions such as macrophage activation, hyperalgesia, synaptic plasticity, and intraocular pressure. Recently, the human UDP receptor P2Y6 was identified as a target for the prostaglandin E2 glycerol ester (PGE2 -G). Here, we show that UDP and PGE2 -G are evolutionary conserved endogenous agonists at vertebrate P2Y6 orthologs. Using sequence comparison of P2Y6 orthologs, homology modeling, and ligand docking studies, we proposed several receptor positions participating in agonist binding. Site-directed mutagenesis and functional analysis of these P2Y6 mutants revealed that both UDP and PGE2 -G share in parts one ligand-binding site. Thus, the convergent signaling of these two chemically very different agonists has already been manifested in the evolutionary design of the ligand-binding pocket.

PSCAN: Spatial scan tests guided by protein structures improve complex disease gene discovery and signal variant detection.

Germline disease-causing variants are generally more spatially clustered in protein 3-dimensional structures than benign variants. Motivated by this tendency, we develop a fast and powerful protein-structure-based scan (PSCAN) approach for evaluating gene-level associations with complex disease and detecting signal variants. We validate PSCAN's performance on synthetic data and two real data sets for lipid traits and Alzheimer's disease. Our results demonstrate that PSCAN performs competitively with existing gene-level tests while increasing power and identifying more specific signal variant sets. Furthermore, PSCAN enables generation of hypotheses about the molecular basis for the associations in the context of protein structures and functional domains.

The Impact of Natural Selection on the Evolution and Function of Placentally Expressed Galectins.

Immunity genes have repeatedly experienced natural selection during mammalian evolution. Galectins are carbohydrate-binding proteins that regulate diverse immune responses, including maternal-fetal immune tolerance in placental pregnancy. Seven human galectins, four conserved across vertebrates and three specific to primates, are involved in placental development. To comprehensively study the molecular evolution of these galectins, both across mammals and within humans, we conducted a series of between- and within-species evolutionary analyses. By examining patterns of sequence evolution between species, we found that primate-specific galectins showed uniformly high substitution rates, whereas two of the four other galectins experienced accelerated evolution in primates. By examining human population genomic variation, we found that galectin genes and variants, including variants previously linked to immune diseases, showed signatures of recent positive selection in specific human populations. By examining one nonsynonymous variant in Galectin-8 previously associated with autoimmune diseases, we further discovered that it is tightly linked to three other nonsynonymous variants; surprisingly, the global frequency of this four-variant haplotype is ∼50%. To begin understanding the impact of this major haplotype on Galectin-8 protein structure, we modeled its 3D protein structure and found that it differed substantially from the reference protein structure. These results suggest that placentally expressed galectins experienced both ancient and more recent selection in a lineage- and population-specific manner. Furthermore, our discovery that the major Galectin-8 haplotype is structurally distinct from and more commonly found than the reference haplotype illustrates the significance of understanding the evolutionary processes that sculpted variants associated with human genetic disease.

PIK3CA C2 Domain Deletions Hyperactivate Phosphoinositide 3-kinase (PI3K), Generate Oncogene Dependence, and Are Exquisitely Sensitive to PI3Kα Inhibitors.

Purpose: We describe herein a novel P447_L455 deletion in the C2 domain of PIK3CA in a patient with an ER+ breast cancer with an excellent response to the PI3Kα inhibitor alpelisib. Although PIK3CA deletions are relatively rare, a significant portion of deletions cluster within amino acids 446-460 of the C2 domain, suggesting these residues are critical for p110α function.Experimental Design: A computational structural model of PIK3CAdelP447-L455 in complex with the p85 regulatory subunit and MCF10A cells expressing PIK3CAdelP447-L455 and PIK3CAH450_P458del were used to understand the phenotype of C2 domain deletions.Results: Computational modeling revealed specific favorable inter-residue contacts that would be lost as a result of the deletion, predicting a significant decrease in binding energy. Coimmunoprecipitation experiments showed reduced binding of the C2 deletion mutants with p85 compared with wild-type p110α. The MCF10A cells expressing PIK3CA C2 deletions exhibited growth factor-independent growth, an invasive phenotype, and higher phosphorylation of AKT, ERK, and S6 compared with parental MCF10A cells. All these changes were ablated by alpelisib treatment.Conclusions: C2 domain deletions in PIK3CA generate PI3K dependence and should be considered biomarkers of sensitivity to PI3K inhibitors. Clin Cancer Res; 24(6); 1426-35. ©2017 AACR.

Identification and Characterization of the First Selective Y4 Receptor Positive Allosteric Modulator.

The human Y4 receptor (Y4R) and its cognate ligand, pancreatic polypeptide (PP), are involved in the regulation of energy expenditure, satiety, and food intake. This system represents a potential target for the treatment of metabolic diseases and has been extensively investigated and validated in vivo. Here, we present the compound tBPC (tert-butylphenoxycyclohexanol), a novel and selective Y4R positive allosteric modulator that potentiates Y4R activation in G-protein signaling and arrestin3 recruitment experiments. The compound has no effect on the binding of the orthosteric ligands, implying its allosteric mode of action at the Y4R and evidence for a purely efficacy-driven positive allosteric modulation. Finally, the ability of tBPC to selectively potentiate Y4R agonism initiated by PP was confirmed in mouse descending colon mucosa preparations expressing native Y4R, demonstrating Y4R positive allosteric modulation in vitro.

Prostaglandin E2 glyceryl ester is an endogenous agonist of the nucleotide receptor P2Y6.

Cyclooxygenase-2 catalyses the biosynthesis of prostaglandins from arachidonic acid but also the biosynthesis of prostaglandin glycerol esters (PG-Gs) from 2-arachidonoylglycerol. Previous studies identified PG-Gs as signalling molecules involved in inflammation. Thus, the glyceryl ester of prostaglandin E2, PGE2-G, mobilizes Ca2+ and activates protein kinase C and ERK, suggesting the involvement of a G protein-coupled receptor (GPCR). To identify the endogenous receptor for PGE2-G, we performed a subtractive screening approach where mRNA from PGE2-G response-positive and -negative cell lines was subjected to transcriptome-wide RNA sequencing analysis. We found several GPCRs that are only expressed in the PGE2-G responder cell lines. Using a set of functional readouts in heterologous and endogenous expression systems, we identified the UDP receptor P2Y6 as the specific target of PGE2-G. We show that PGE2-G and UDP are both agonists at P2Y6, but they activate the receptor with extremely different EC50 values of ~1 pM and ~50 nM, respectively. The identification of the PGE2-G/P2Y6 pair uncovers the signalling mode of PG-Gs as previously under-appreciated products of cyclooxygenase-2.

An Acquired HER2T798I Gatekeeper Mutation Induces Resistance to Neratinib in a Patient with HER2 Mutant-Driven Breast Cancer.

We report a HER2T798I gatekeeper mutation in a patient with HER2L869R-mutant breast cancer with acquired resistance to neratinib. Laboratory studies suggested that HER2L869R is a neratinib-sensitive, gain-of-function mutation that upon dimerization with mutant HER3E928G, also present in the breast cancer, amplifies HER2 signaling. The patient was treated with neratinib and exhibited a sustained partial response. Upon clinical progression, HER2T798I was detected in plasma tumor cell-free DNA. Structural modeling of this acquired mutation suggested that the increased bulk of isoleucine in HER2T798I reduces neratinib binding. Neratinib blocked HER2-mediated signaling and growth in cells expressing HER2L869R but not HER2L869R/T798I In contrast, afatinib and the osimertinib metabolite AZ5104 strongly suppressed HER2L869R/T798I-induced signaling and cell growth. Acquisition of HER2T798I upon development of resistance to neratinib in a breast cancer with an initial activating HER2 mutation suggests HER2L869R is a driver mutation. HER2T798I-mediated neratinib resistance may be overcome by other irreversible HER2 inhibitors like afatinib.Significance: We found an acquired HER2 gatekeeper mutation in a patient with HER2-mutant breast cancer upon clinical progression on neratinib. We speculate that HER2T798I may arise as a secondary mutation following response to effective HER2 tyrosine kinase inhibitors (TKI) in other cancers with HER2-activating mutations. This resistance may be overcome by other irreversible HER2 TKIs, such as afatinib. Cancer Discov; 7(6); 575-85. ©2017 AACR.This article is highlighted in the In This Issue feature, p. 539.

Protocols for Molecular Modeling with Rosetta3 and RosettaScripts.

Previously, we published an article providing an overview of the Rosetta suite of biomacromolecular modeling software and a series of step-by-step tutorials [Kaufmann, K. W., et al. (2010) Biochemistry 49, 2987-2998]. The overwhelming positive response to this publication we received motivates us to here share the next iteration of these tutorials that feature de novo folding, comparative modeling, loop construction, protein docking, small molecule docking, and protein design. This updated and expanded set of tutorials is needed, as since 2010 Rosetta has been fully redesigned into an object-oriented protein modeling program Rosetta3. Notable improvements include a substantially improved energy function, an XML-like language termed "RosettaScripts" for flexibly specifying modeling task, new analysis tools, the addition of the TopologyBroker to control conformational sampling, and support for multiple templates in comparative modeling. Rosetta's ability to model systems with symmetric proteins, membrane proteins, noncanonical amino acids, and RNA has also been greatly expanded and improved.

Discovery of Small-Molecule Modulators of the Human Y4 Receptor.

The human neuropeptide Y4 receptor (Y4R) and its native ligand, pancreatic polypeptide, are critically involved in the regulation of human metabolism by signaling satiety and regulating food intake, as well as increasing energy expenditure. Thus, this receptor represents a putative target for treatment of obesity. With respect to new approaches to treat complex metabolic disorders, especially in multi-receptor systems, small molecule allosteric modulators have been in the focus of research in the last years. However, no positive allosteric modulators or agonists of the Y4R have been described so far. In this study, small molecule compounds derived from the Niclosamide scaffold were identified by high-throughput screening to increase Y4R activity. Compounds were characterized for their potency and their effects at the human Y4R and as well as their selectivity towards Y1R, Y2R and Y5R. These compounds provide a structure-activity relationship profile around this common scaffold and lay the groundwork for hit-to-lead optimization and characterization of positive allosteric modulators of the Y4R.

Autocorrelation descriptor improvements for QSAR: 2DA_Sign and 3DA_Sign.

Quantitative structure-activity relationship (QSAR) is a branch of computer aided drug discovery that relates chemical structures to biological activity. Two well established and related QSAR descriptors are two- and three-dimensional autocorrelation (2DA and 3DA). These descriptors encode the relative position of atoms or atom properties by calculating the separation between atom pairs in terms of number of bonds (2DA) or Euclidean distance (3DA). The sums of all values computed for a given small molecule are collected in a histogram. Atom properties can be added with a coefficient that is the product of atom properties for each pair. This procedure can lead to information loss when signed atom properties are considered such as partial charge. For example, the product of two positive charges is indistinguishable from the product of two equivalent negative charges. In this paper, we present variations of 2DA and 3DA called 2DA_Sign and 3DA_Sign that avoid information loss by splitting unique sign pairs into individual histograms. We evaluate these variations with models trained on nine datasets spanning a range of drug target classes. Both 2DA_Sign and 3DA_Sign significantly increase model performance across all datasets when compared with traditional 2DA and 3DA. Lastly, we find that limiting 3DA_Sign to maximum atom pair distances of 6 Å instead of 12 Å further increases model performance, suggesting that conformational flexibility may hinder performance with longer 3DA descriptors. Consistent with this finding, limiting the number of bonds in 2DA_Sign from 11 to 5 fails to improve performance.

Computational methods in drug discovery.

Computer-aided drug discovery/design methods have played a major role in the development of therapeutically important small molecules for over three decades. These methods are broadly classified as either structure-based or ligand-based methods. Structure-based methods are in principle analogous to high-throughput screening in that both target and ligand structure information is imperative. Structure-based approaches include ligand docking, pharmacophore, and ligand design methods. The article discusses theory behind the most important methods and recent successful applications. Ligand-based methods use only ligand information for predicting activity depending on its similarity/dissimilarity to previously known active ligands. We review widely used ligand-based methods such as ligand-based pharmacophores, molecular descriptors, and quantitative structure-activity relationships. In addition, important tools such as target/ligand data bases, homology modeling, ligand fingerprint methods, etc., necessary for successful implementation of various computer-aided drug discovery/design methods in a drug discovery campaign are discussed. Finally, computational methods for toxicity prediction and optimization for favorable physiologic properties are discussed with successful examples from literature.

Pancreatic polypeptide is recognized by two hydrophobic domains of the human Y4 receptor binding pocket.

Structural characterization of the human Y4 receptor (hY4R) interaction with human pancreatic polypeptide (hPP) is crucial, not only for understanding its biological function but also for testing treatment strategies for obesity that target this interaction. Here, the interaction of receptor mutants with pancreatic polypeptide analogs was studied through double-cycle mutagenesis. To guide mutagenesis and interpret results, a three-dimensional comparative model of the hY4R-hPP complex was constructed based on all available class A G protein-coupled receptor crystal structures and refined using experimental data. Our study reveals that residues of the hPP and the hY4R form a complex network consisting of ionic interactions, hydrophobic interactions, and hydrogen binding. Residues Tyr(2.64), Asp(2.68), Asn(6.55), Asn(7.32), and Phe(7.35) of Y4R are found to be important in receptor activation by hPP. Specifically, Tyr(2.64) interacts with Tyr(27) of hPP through hydrophobic contacts. Asn(7.32) is affected by modifications on position Arg(33) of hPP, suggesting a hydrogen bond between these two residues. Likewise, we find that Phe(7.35) is affected by modifications of hPP at positions 33 and 36, indicating interactions between these three amino acids. Taken together, we demonstrate that the top of transmembrane helix 2 (TM2) and the top of transmembrane helices 6 and 7 (TM6-TM7) form the core of the peptide binding pocket. These findings will contribute to the rational design of ligands that bind the receptor more effectively to produce an enhanced agonistic or antagonistic effect.

A genome-wide RNAi screen in Caenorhabditis elegans identifies the nicotinic acetylcholine receptor subunit ACR-7 as an antipsychotic drug target.

We report a genome-wide RNA interference (RNAi) screen for Suppressors of Clozapine-induced Larval Arrest (scla genes) in Caenorhabditis elegans, the first genetic suppressor screen for antipsychotic drug (APD) targets in an animal. The screen identifies 40 suppressors, including the α-like nicotinic acetylcholine receptor (nAChR) homolog acr-7. We validate the requirement for acr-7 by showing that acr-7 knockout suppresses clozapine-induced larval arrest and that expression of a full-length translational GFP fusion construct rescues this phenotype. nAChR agonists phenocopy the developmental effects of clozapine, while nAChR antagonists partially block these effects. ACR-7 is strongly expressed in the pharynx, and clozapine inhibits pharyngeal pumping. acr-7 knockout and nAChR antagonists suppress clozapine-induced inhibition of pharyngeal pumping. These findings suggest that clozapine activates ACR-7 channels in pharyngeal muscle, leading to tetanus of pharyngeal muscle with consequent larval arrest. No APDs are known to activate nAChRs, but a number of studies indicate that α7-nAChR agonists may prove effective for the treatment of psychosis. α-like nAChR signaling is a mechanism through which clozapine may produce its therapeutic and/or toxic effects in humans, a hypothesis that could be tested following identification of the mammalian ortholog of C. elegans acr-7.

BCL::EMAS--enantioselective molecular asymmetry descriptor for 3D-QSAR.

Stereochemistry is an important determinant of a molecule's biological activity. Stereoisomers can have different degrees of efficacy or even opposing effects when interacting with a target protein. Stereochemistry is a molecular property difficult to represent in 2D-QSAR as it is an inherently three-dimensional phenomenon. A major drawback of most proposed descriptors for 3D-QSAR that encode stereochemistry is that they require a heuristic for defining all stereocenters and rank-ordering its substituents. Here we propose a novel 3D-QSAR descriptor termed Enantioselective Molecular ASymmetry (EMAS) that is capable of distinguishing between enantiomers in the absence of such heuristics. The descriptor aims to measure the deviation from an overall symmetric shape of the molecule. A radial-distribution function (RDF) determines a signed volume of tetrahedrons of all triplets of atoms and the molecule center. The descriptor can be enriched with atom-centric properties such as partial charge. This descriptor showed good predictability when tested with a dataset of thirty-one steroids commonly used to benchmark stereochemistry descriptors (r² = 0.89, q² = 0.78). Additionally, EMAS improved enrichment of 4.38 versus 3.94 without EMAS in a simulated virtual high-throughput screening (vHTS) for inhibitors and substrates of cytochrome P450 (PUBCHEM AID891).

Clozapine interaction with phosphatidyl inositol 3-kinase (PI3K)/insulin-signaling pathway in Caenorhabditis elegans.

Clozapine has superior and unique effects as an antipsychotic agent, but the mediators of these effects are not known. We studied behavioral and developmental effects of clozapine in Caenorhabditis elegans, as a model system to identify previously undiscovered mechanisms of drug action. Clozapine induced early larval arrest, a phenotype that was also seen with the clozapine metabolite N-desmethyl clozapine but not with any other typical or atypical antipsychotic drug tested. Mutations in the insulin receptor/daf-2 and phosphatidyl inositol 3-kinase (PI3K)/age-1 suppressed clozapine-induced larval arrest, suggesting that clozapine may activate the insulin-signaling pathway. Consistent with this notion, clozapine also increased the expression of an age-1::GFP reporter. Activation of the insulin-signaling pathway leads to cytoplasmic localization of the fork head transcription factor FOXO/daf-16. Clozapine produced cytoplasmic localization of DAF-16::GFP in arrested L1 larvae, in contrast to stressors such as starvation or high temperature, which produce nuclear localization of DAF-16::GFP in arrested L1 larvae. Clozapine also inhibited pharyngeal pumping in C. elegans, an effect that may contribute to, but did not explain, clozapine-induced larval arrest. Our findings demonstrate a drug-specific interaction between clozapine and the PI3K/insulin-signaling pathway in C. elegans. As this pathway is conserved across species, the results may have implications for understanding the unique effects of clozapine in humans.