W2466.48 Opens a Gate for a Continuous Intrinsic Water Pathway during Activation of the Adenosine A2A Receptor

The question how G‐protein‐coupled receptors transduce an extracellular signal by a sequence of transmembrane conformational transitions into an intracellular response remains to be solved at molecular detail. Herein, we use molecular dynamics simulations to reveal distinct conformational transitions of the adenosine A_2A receptor, and we found that the conserved W246^6.48 residue in transmembrane helix TM6 performs a key rotamer toggle switch. Agonist binding induces the sidechain of W246^6.48 to fluctuate between two distinct conformations enabling the diffusion of water molecules from the bulk into the center of the receptor. After passing the W246^6.48 gate, the internal water molecules induce another conserved residue, Y288^7.53, to switch to a distinct rotamer conformation establishing a continuous transmembrane water pathway. Further, structural changes of TM6 and TM7 induce local structural changes of the adjacent lipid bilayer.     

GPCR A2A AR腺苷受体蛋白的激动剂结合及其诱导的蛋白活性开关构象变化

运用分子动力学模拟,研究了腺苷酸（激动剂）与A2AAR腺苷受体蛋白的相互作用和配体结合诱导的蛋白动力学变化．识别了与腺苷酸结合力强于0．5kcal／mol的关键基团：A63^2．61,I66^2．64,V84^3.32,L85^3.33,T88^3.36,F168^5.29,M177^5.38,L249^6.51,H250^6.52和N253^6.55,观察到腺苷酸没有与L167^5.28相互作用,这一结果支持了L167^5.28是抑制剂特异性结合位点,不与激动剂结合．未结合配体（激动剂或抑制剂）的单体A2AAR和腺苷酸结合后的A2AAR在构象上有三个不同功能性开关．腺苷酸结合可以诱导A2AAR腺苷受体蛋白的构象调整,使得三个功能性开关器件的构象与单体A2AAR不同．     

Modelling of ORL1 receptor-ligand interactions

An opioid receptor like (ORL1) receptor is one of a family of G-protein-coupled receptors (GPCR); it represents a new pharmaceutical target with extensive therapeutic potential for the regulation of important biological functions such as nociception, mood disorders, drug abuse, learning or cardiovascular control. Although the crystal structure of the inactive form of the ORL1 receptor has been determined, little is known about its activation. By using X-ray structures of the β2-adrenegic receptor in its inactive (2RH1) and active (3P0G) states as templates, inactive and active homology models of the ORL1 receptor were constructed. Structurally diverse sets of strongly binding antagonists and agonists were docked with both ORL1 receptor forms. The major receptor-ligand interactions responsible for antagonist and agonist binding were identified. Although both sets of ligands, agonists and antagonists, bind to the same region of the receptor, they occupy partially different binding pockets. Agonists bind to the inactive receptor in a slightly different manner than antagonists. This difference is more pronounced in binding to the active ORL1 receptor model and points to the amino acids at the extracellular end of TM6, suggesting that this region is important for receptor-activation.     

In silico analysis of the histaprodifen induced activation pathway of the guinea-pig histamine H<Subscript>1</Subscript>-receptor

The binding of (partial) agonists in the binding pocket of biogenic amine receptors induces a conformational change from the inactive to the active state of the receptors. There is only little knowledge about the binding pathways of ligands into binding pocket on molecular level. So far, it was not possible with molecular dynamic simulations to observe the ligand binding and receptor activation. Furthermore, there is nearly nothing known, in which state of ligand binding, the receptor gets activated. The aim of this study was to get more detailed insight into the process of ligand binding and receptor activation. With the recently developed LigPath algorithm, we scanned the potential energy surface of the binding process of dimeric histaprodifen, a partial agonist at the histamine H₁-receptor, into the guinea pig histamine H₁-receptor, taking also into account the receptor activation. The calculations exhibited large conformational changes of Trp^6.48 and Phe^6.55 during ligand binding and receptor activation. Additionally, conformational changes were also observed for Phe^6.52, Tyr^6.51 and Phe^6.44. Conformational changes of Trp^6.48 and Phe^6.52 are discussed in literature as rotamer toggle switch in context with receptor activation. Additionally, the calculations indicate that the binding of dimeric histaprodifen, accompanied by receptor activation is energetically preferred. In general, this study gives new, theoretical insights onto ligand binding and receptor activation on molecular level.     

神经介素B受体与拮抗剂、激动剂的分子模拟研究

大鼠神经介素B受体(rat neuromedin B receptor, rNMBR)属于G蛋白偶联受体(G-protein coupled receptor, GPCR) A家族的成员. GPCR的结构特征和在信号传导中的重要作用决定了其可以作为很好的药物靶标. 关于rNMBR与内源性激动剂神经介素B (neuromedin B, NMB)以及与非肽类拮抗剂pd168368作用机制的研究对于合理设计受体药物分子有重要的指导意义. 在这一研究中, 我们使用同源模建, 构建受体的三维结构, 进行分子对接和分子动力学的计算. 基于受体三维结构, 通过10 ns的空载受体、激动剂-受体、拮抗剂-受体的分子动力学模拟, 探讨受体与激动剂与拮抗剂的作用机制. 研究表明rNMB-R中跨膜(transmembrane, TM)螺旋3, 5, 6, 7参与配体的结合. NMB与受体的结合, 使受体转变为活性构象, 而受体同拮抗剂pd168368恰好相反.     

Chemogenomic discovery of allosteric antagonists at the GPRC6A receptor

GPRC6A is a Family C G protein-coupled receptor recently discovered and deorphanized by our group. This study integrates chemogenomic ligand inference, homology modeling, compound synthesis, and pharmacological mechanism-of-action studies to disclose two noticeable results of methodological and pharmacological character: (1) chemogenomic lead identification through the first, to our knowledge, ligand inference between two different GPCR families, Families A and C; and (2) the discovery of the most selective GPRC6A allosteric antagonists discovered to date. The unprecedented inference of?pharmacological activity across GPCR families provides proof-of-concept for in?silico approaches against Family C targets based on Family A templates, greatly expanding the prospects of successful drug design and discovery. The antagonists were tested against a panel of seven Family A and C G protein-coupled receptors containing the chemogenomic binding sequence motif where some of the identified GPRC6A antagonists showed some activity. However, three compounds with at least ～3-fold selectivity for GPRC6A were discovered, which present a significant step forward compared with the previously published GPRC6A antagonists, calindol and NPS 2143, which both display ～30-fold selectivity for the calcium-sensing receptor compared to GPRC6A. The antagonists constitute novel research tools toward investigating the signaling mechanism of the GPRC6A receptor at the cellular level and serve as initial ligands for further optimization of potency and selectivity enabling future ex?vivo/in?vivo pharmacological studies.     

High-throughput modeling of human G-protein coupled receptors: amino acid sequence alignment, three-dimensional model building, and receptor library screening

The current study describes the development of a computer package (GPCRmod) aimed at the high-throughput modeling of the therapeutically important family of human G-protein coupled receptors (GPCRs). GPCRmod first proposes a reliable alignment of the seven transmembrane domains (7 TMs) of most druggable human GPCRs based on pattern/motif recognition for each of the 7 TMs that are considered independently. It then converts the alignment into knowledge-based three-dimensional (3-D) models starting from a set of 3-D backbone templates and two separate rotamer libraries for side chain positioning. The 7 TMs of 277 human GPCRs have been accurately aligned, unambiguously clustered in three different classes (rhodopsin-like, secretin-like, metabotropic glutamate-like), and converted into high-quality 3-D models at a remarkable throughput (ca. 3s/model). A 3-D GPCR target library of 277 receptors has consequently been setup. Its utility for "in silico" inverse screening purpose has been demonstrated by recovering among top scorers the receptor of a selective GPCR antagonist as well as the receptors of a promiscuous antagonist. The current GPCR target library thus constitutes a 3-D database of choice to address as soon as possible the "virtual selectivity" profile of any GPCR antagonist or inverse agonist in an early hit optimization process.     

Evaluation of pharmaceutical activities of G-protein coupled receptor targeted pharmaceuticals in Chinese wastewater effluent

The occurrence of biologically active pharmaceuticals in aquatic environments raised the potential risks to aquatic species. Among these marketed biological active pharmaceuticals, it has been estimated that 40% of them target G-protein-coupled receptors (GPCRs). We have illustrated pharmaceutical activities of GPCR targeted pharmaceuticals in English and Japanese wastewater by the in vitro transforming growth factor-α (TGFα) shedding assay. However, as the most important producer and consumer of pharmaceuticals, the occurrence of GPCR targeted pharmaceuticals in China had remained unclear. In this study, we investigated the pharmaceutical activities of GPCR targeted pharmaceuticals in secondary effluents of Chinese wastewater treatment plants. We discovered antagonistic activities against angiotensin (AT1) receptor at up to 7.2 × 102 ng-valsartan-equivalent quantity/L in Chinese wastewater for the first time as well as agonistic activities against dopamine (D2) receptor. Furthermore, in parallel with the assay, we determined concentrations of GPCR targeted pharmaceuticals in target wastewater by liquid chromatography coupled with tandem mass spectrometry (LC–MS/MS). Through the comparison of predicted antagonistic activities calculated by concentrations and potency values from the assay, we found that the measured antagonistic activities against AT1 receptor from the assay were higher than the predicted AT1 activities from valsartan, irbesartan, and losartan, indicating the potential existence of other unknown AT1 antagonists in wastewater.     

GPCR structure-based virtual screening approach for CB2 antagonist search

The potential for therapeutic specificity in regulating diseases has made cannabinoid (CB) receptors one of the most important G-protein-coupled receptor (GPCR) targets in search for new drugs. Considering the lack of related 3D experimental structures, we have established a structure-based virtual screening protocol to search for CB2 bioactive antagonists based on the 3D CB2 homology structure model. However, the existing homology-predicted 3D models often deviate from the native structure and therefore may incorrectly bias the in silico design. To overcome this problem, we have developed a 3D testing database query algorithm to examine the constructed 3D CB2 receptor structure model as well as the predicted binding pocket. In the present study, an antagonist-bound CB2 receptor complex model was initially generated using flexible docking simulation and then further optimized by molecular dynamic and mechanical (MD/MM) calculations. The refined 3D structural model of the CB2-ligand complex was then inspected by exploring the interactions between the receptor and ligands in order to predict the potential CB2 binding pocket for its antagonist. The ligand-receptor complex model and the predicted antagonist binding pockets were further processed and validated by FlexX-Pharm docking against a testing compound database that contains known antagonists. Furthermore, a consensus scoring (CScore) function algorithm was established to rank the binding interaction modes of a ligand on the CB2 receptor. Our results indicated that the known antagonists seeded in the testing database can be distinguished from a significant amount of randomly chosen molecules. Our studies demonstrated that the established GPCR structure-based virtual screening approach provided a new strategy with a high potential for in silico identifying novel CB2 antagonist leads based on the homology-generated 3D CB2 structure model.     

Rare cis-configured 2,4-disubstituted 1-alkylpiperidines: synthesized and tested against trace-amine-associated receptor 1 (TAAR1)

Rare cis-configured 2,4-disubstituted 1-alkylpyridines were envisioned as ligands for trace amine associated receptor 1 (TAAR1). They were synthesized in diastereomerically pure form with the decarboxylative Castagnoli–Cushman reac-tion followed by two reduction events. Despite showing no affinity to TAAR1 as was anticipated, these novel, druglike and CNS-focused compounds will be of much utility in sub-sequent lead generation pursuits.     

An automated system for the analysis of G protein-coupled receptor transmembrane binding pockets: alignment, receptor-based pharmacophores, and their application

G protein-coupled receptors (GPCRs) share a common architecture consisting of seven transmembrane (TM) domains. Various lines of evidence suggest that this fold provides a generic binding pocket within the TM region for hosting agonists, antagonists, and allosteric modulators. Here, a comprehensive and automated method allowing fast analysis and comparison of these putative binding pockets across the entire GPCR family is presented. The method relies on a robust alignment algorithm based on conservation indices, focusing on pharmacophore-like relationships between amino acids. Analysis of conservation patterns across the GPCR family and alignment to the rhodopsin X-ray structure allows the extraction of the amino acids lining the TM binding pocket in a so-called ligand binding pocket vector (LPV). In a second step, LPVs are translated to simple 3D receptor pharmacophore models, where each amino acid is represented by a single spherical pharmacophore feature and all atomic detail is omitted. Applications of the method include the assessment of selectivity issues, support of mutagenesis studies, and the derivation of rules for focused screening to identify chemical starting points in early drug discovery projects. Because of the coarseness of this 3D receptor pharmacophore model, however, meaningful scoring and ranking procedures of large sets of molecules are not justified. The LPV analysis of the trace amine-associated receptor family and its experimental validation is discussed as an example. The value of the 3D receptor model is demonstrated for a class C GPCR family, the metabotropic glutamate receptors.     

A virtual screen for diverse ligands: discovery of selective G protein-coupled receptor antagonists

Virtual screening has become a major focus of bioactive small molecule lead identification, and reports of agonists and antagonists discovered via virtual methods are becoming more frequent. G protein-coupled receptors (GPCRs) are the one class of protein targets for which success with this approach has been limited. This is likely due to the paucity of detailed experimental information describing GPCR structure and the intrinsic function-associated structural flexibility of GPCRs which present major challenges in the application of receptor-based virtual screening. Here we describe an in silico methodology that diminishes the effects of structural uncertainty, allowing for more inclusive representation of a potential docking interaction with exogenous ligands. Using this approach, we screened one million compounds from a virtual database, and a diverse subgroup of 100 compounds was selected, leading to experimental identification of five structurally diverse antagonists of the thyrotropin-releasing hormone receptors (TRH-R1 and TRH-R2). The chirality of the most potent chemotype was demonstrated to be important in its binding affinity to TRH receptors; the most potent stereoisomer was noted to have a 13-fold selectivity for TRH-R1 over TRH-R2. A comprehensive mutational analysis of key amino acid residues that form the putative binding pocket of TRH receptors further verified the binding modality of these small molecule antagonists. The described virtual screening approach may prove applicable in the search for novel small molecule agonists and antagonists of other GPCRs.     

A CE assay for the detection of agonist-stimulated adenylyl cyclase activity

A CE assay was developed for the detection of adenylyl cyclase (AC) activity stimulated at the AC and G protein-coupled receptor (GPCR) level. In the assay, cell membranes overexpressing GPCR and/or AC were incubated with modulators and substrate ATP to produce cAMP in a dose-dependent manner. In both the CE-UV and a radiochemical assay, the addition of forskolin (FSK) resulted in a two- to three-fold maximum increase in AC activity with EC50s of 4.2 +/- 0.7 and 2.4 +/- 0.7 microM, respectively, demonstrating that similar results were obtained by both assays. GPCR activation was also detected using cell membranes overexpressing AC and the beta2-adrenergic receptor (beta2AR) fused to the stimulatory G protein. Terbutaline (beta2AR agonist) increased the basal rate of cAMP formation 1.7 +/- 0.1-fold resulting in an EC50 of 62 +/- 10 nM. The assay's ability to detect antagonists is demonstrated by the expected right-shifted EC50 of terbutaline by the beta2AR antagonist propranolol. The CE-UV assay offers advantages over the traditional radioactivity assay in terms of safety and labor.     

Functional GPCR microarrays

This paper describes G-protein-coupled receptor (GPCR) microarrays on porous glass substrates and functional assays based on the binding of a europium-labeled GTP analogue. The porous glass slides were made by casting a glass frit on impermeable glass slides and then coating with gamma-aminopropyl silane (GAPS). The emitted fluorescence was captured on an imager with a time-gated intensified CCD detector. Microarrays of the neurotensin receptor 1, the cholinergic receptor muscarinic 2, the opioid receptor mu, and the cannabinoid receptor 1 were fabricated by pin printing. The selective agonism of each of the receptors was observed. The screening of potential antagonists was demonstrated using a cocktail of agonists. The amount of activation observed was sufficient to permit determinations of EC50 and IC50. Such microarrays could potentially streamline drug discovery by helping integrate primary screening with selectivity and safety screening without compromising the essential functional information obtainable from cellular assays.     

Homology model-based virtual screening for GPCR ligands using docking and target-biased scoring

The current study investigates the combination of two recently reported techniques for the improvement of homology model-based virtual screening for G-protein coupled receptor (GPCR) ligands. First, ligand-supported homology modeling was used to generate receptor models that were in agreement with mutagenesis data and structure-activity relationship information of the ligands. Second, interaction patterns from known ligands to the receptor were applied for scoring and rank ordering compounds from a virtual library using ligand-receptor interaction fingerprint-based similarity (IFS). Our approach was evaluated in retrospective virtual screening experiments for antagonists of the metabotropic glutamate receptor (mGluR) subtype 5. The results of our approach were compared to the results obtained by conventional scoring functions (Dock-Score, PMF-Score, Gold-Score, ChemScore, and FlexX-Score). The IFS lead to significantly higher enrichment rates, relative to the competing scoring functions. Though using a target-biased scoring approach, the results were not biased toward the chemical classes of the reference structures. Our results indicate that the presented approach has the potential to serve as a general setup for successful structure-based GPCR virtual screening.     

Generation of a homology model of the human histamine H<Subscript>3</Subscript> receptor for ligand docking and pharmacophore-based screening

The human histamine H(3) receptor (hH(3)R) is a G-protein coupled receptor (GPCR), which modulates the release of various neurotransmitters in the central and peripheral nervous system and therefore is a potential target in the therapy of numerous diseases. Although ligands addressing this receptor are already known, the discovery of alternative lead structures represents an important goal in drug design. The goal of this work was to study the hH(3)R and its antagonists by means of molecular modelling tools. For this purpose, a strategy was pursued in which a homology model of the hH(3)R based on the crystal structure of bovine rhodopsin was generated and refined by molecular dynamics simulations in a dipalmitoylphosphatidylcholine (DPPC)/water membrane mimic before the resulting binding pocket was used for high-throughput docking using the program GOLD. Alternatively, a pharmacophore-based procedure was carried out where the alleged bioactive conformations of three different potent hH(3)R antagonists were used as templates for the generation of pharmacophore models. A pharmacophore-based screening was then carried out using the program Catalyst. Based upon a database of 418 validated hH(3)R antagonists both strategies could be validated in respect of their performance. Seven hits obtained during this screening procedure were commercially purchased, and experimentally tested in a [(3)H]N(alpha)-methylhistamine binding assay. The compounds tested showed affinities at hH(3)R with K ( i ) values ranging from 0.079 to 6.3 muM.     

Exact rotamer optimization for protein design

Computational methods play a central role in the rational design of novel proteins. The present work describes a new hybrid exact rotamer optimization (HERO) method that builds on previous dead-end elimination algorithms to yield dramatic performance enhancements. Measured on experimentally validated physical models, these improvements make it possible to perform previously intractable designs of entire protein core, surface, or boundary regions. Computational demonstrations include a full core design of the variable domains of the light and heavy chains of catalytic antibody 48G7 FAB with 74 residues and 10(128) conformations, a full core/boundary design of the beta1 domain of protein G with 25 residues and 10(53) conformations, and a full surface design of the beta1 domain of protein G with 27 residues and 10(60) conformations. In addition, a full sequence design of the beta1 domain of protein G is used to demonstrate the strong dependence of algorithm performance on the exact form of the potential function and the fidelity of the rotamer library. These results emphasize that search algorithm performance for protein design can only be meaningfully evaluated on physical models that have been subjected to experimental scrutiny. The new algorithm greatly facilitates ongoing efforts to engineer increasingly complex protein features.     

The Molecular Mechanism of P2Y1 Receptor Activation

Human purinergic G protein‐coupled receptor P2Y₁ (P2Y₁R) is activated by adenosine 5′‐diphosphate (ADP) to induce platelet activation and thereby serves as an important antithrombotic drug target. Crystal structures of P2Y₁R revealed that one ligand (MRS2500) binds to the extracellular vestibule of this GPCR, whereas another (BPTU) occupies the surface between transmembrane (TM) helices TM2 and TM3. We introduced a total of 20 μs all‐atom long‐timescale molecular dynamic (MD) simulations to inquire why two molecules in completely different locations both serve as antagonists while ADP activates the receptor. Our results indicate that BPTU acts as an antagonist by stabilizing extracellular helix bundles leading to an increase of the lipid order, whereas MRS2500 blocks signaling by occupying the ligand binding site. Both antagonists stabilize an ionic lock within the receptor. However, binding of ADP breaks this ionic lock, forming a continuous water channel that leads to P2Y₁R activation.     

Dynamics and intrinsic statistical fluctuations of a gene switch

We studied a simple gene regulatory network, the toggle switch. Specifically, we examined the means and statistical fluctuations in numbers of proteins. We found that when omega, the ratio of rates of protein-gene unbinding to protein degradation, was between approximately 10(-3) and approximately 10, the fluctuations were much larger than those we would have expected from Poisson statistics. In addition, we examined characteristic time values for system relaxation and found both that they increased with omega and that they have significant phase transition effects, with a secondary time scale appearing near the boundary between bistable and other phases. Last, we discuss the bistability of the toggle switch.     

Prediction of the 3D structure and dynamics of human DP G-protein coupled receptor bound to an agonist and an antagonist

Prostanoids play important physiological roles in the cardiovascular and immune systems and in pain sensation in peripheral systems through their interactions with eight G-protein coupled receptors. These receptors are important drug targets, but development of subtype specific agonists and antagonists has been hampered by the lack of 3D structures for these receptors. We report here the 3D structure for the human DP G-protein coupled receptor (GPCR) predicted by the MembStruk computational method. To validate this structure, we use the HierDock computational method to predict the binding mode for the endogenous agonist (PGD2) to DP. Based on our structure, we predicted the binding of different antagonists and optimized them. We find that PGD2 binds vertically to DP in the TM1237 region with the alpha chain toward the extracellular (EC) region and the omega chain toward the middle of the membrane. This structure explains the selectivity of the DP receptor and the residues involved in the predicted binding site correlate very well with available mutation experiments on DP, IP, TP, FP, and EP subtypes. We report molecular dynamics of DP in explicit lipid and water and find that the binding of the PGD2 agonist leads to correlated rotations of helices of TM3 and TM7, whereas binding of antagonist leads to no such rotations. Thus, these motions may be related to the mechanism of activation.