On the applicability of GPCR homology models to computer-aided drug discovery: a comparison between in silico and crystal structures of the beta2-adrenergic receptor

In silico identification of new ligands for GPR17: a promising therapeutic target for neurodegenerative diseases

GPR17, a previously orphan receptor responding to both uracil nucleotides and cysteinyl-leukotrienes, has been proposed as a novel promising target for human neurodegenerative diseases. Here, in order to specifically identify novel potent ligands of GPR17, we first modeled in silico the receptor by using a multiple template approach, in which extracellular loops of the receptor, quite complex to treat, were modeled making reference to the most similar parts of all the class-A GPCRs crystallized so far. A high-throughput virtual screening exploration of GPR17 binding site with more than 130,000 lead-like compounds was then applied, followed by the wet functional and pharmacological validation of the top-scoring chemical structures. This approach revealed successful for the proposed aim, and allowed us to identify five agonists or partial agonists with very diverse chemical structure. None of these compounds could have been expected 'a priori' to act on a GPCR, and all of them behaved as much more potent ligands than GPR17 endogenous activators.

Homology Model Versus X-ray Structure in Receptor-based Drug Design: A Retrospective Analysis with the Dopamine D3 Receptor

Structure-based design methods commonly used in medicinal chemistry rely on a three-dimensional representation of the receptor. However, few crystal structures are solved in comparison with the huge number of pharmaceutical targets. This often renders homology models the only information available. It is particularly true for G protein-coupled receptors (GPCRs), one of the most important targets for approved medicines and current drug discovery projects. However, very few studies have tested their validity in comparison with corresponding crystal structures, especially in a lead optimization perspective. The recent solving of dopamine D3 receptor crystal structure allowed us to assess our historical homology model. We performed a statistical analysis, by docking our in-house lead optimization library of 1500 molecules. We demonstrate here that the refined homology model suits at least as well as the X-ray structure. It is concluded that when the crystal structure of a given GPCR is not available, homology modeling can be an excellent surrogate to support drug discovery efforts.

Comparison analysis of primary ligand-binding sites in seven-helix membrane proteins

Seven-helix transmembrane proteins, including the G-protein-coupled receptors (GPCRs), mediate a broad range of fundamental cellular activities through binding to a wide range of ligands. Understanding the structural basis for the ligand-binding selectivity of these proteins is of significance to their structure-based drug design. Comparison analysis of proteins' ligand-binding sites provides a useful way to study their structure-activity relationships. Various computational methods have been developed for the binding-site comparison of soluble proteins. In this work, we applied this approach to the analysis of the primary ligand-binding sites of 92 seven-helix transmembrane proteins. Results of the studies confirmed that the binding site of bacterial rhodopsins is indeed different from all GPCRs. In the latter group, further comparison of the binding sites indicated a group of residues that could be responsible for ligand-binding selectivity and important for structure-based drug design. Furthermore, unexpected binding-site dissimilarities were observed among adrenergic and adenosine receptors, suggesting that the percentage of the overall sequence identity between a target protein and a template protein alone is not sufficient for selecting the best template for homology modeling of seven-helix membrane proteins. These results provided novel insight into the structural basis of ligand-binding selectivity of seven-helix membrane proteins and are of practical use to the computational modeling of these proteins.

In silico analysis of the binding of agonists and blockers to the β2-adrenergic receptor

Activation of G protein-coupled receptors (GPCRs) is a complex phenomenon. Here, we applied Induced Fit Docking (IFD) in tandem with linear discriminant analysis (LDA) to generate hypotheses on the conformational changes induced to the β(2)-adrenergic receptor by agonist binding, preliminary to the sequence of events that characterize activation of the receptor. This analysis, corroborated by a follow-up molecular dynamics study, suggested that agonists induce subtle movements to the fifth transmembrane domain (TM5) of the receptor. Furthermore, molecular dynamics also highlighted a correlation between movements of TM5 and the second extracellular loop (EL2), suggesting that freedom of motion of EL2 is required for the agonist-induced TM5 displacement. Importantly, we also showed that the IFD/LDA procedure can be used as a computational means to distinguish agonists from blockers on the basis of the differential conformational changes induced to the receptor. In particular, the two most predictive models obtained are based on the RMSD induced to Ser207 and on the counterclockwise rotation induced to TM5.

The use of GPCR structures in drug design

Structure-based drug discovery is routinely applied to soluble targets such as proteases and kinases. It is only recently that multiple high-resolution X-ray structures of G protein-coupled receptors (GPCRs) have become available. Here we review the technology developments that have led to the recent plethora of GPCR structures. These include developments in protein expression and purification as well as techniques to stabilize receptors and crystallize them. We discuss the findings derived from the new structures with regard to understanding GPCR function and pharmacology. Finally, we examine the utility of structure-based drug discovery approaches including homology modeling, virtual screening, and fragment screening for GPCRs in the context of what has been learnt from other target classes.

GPCR Conformations: Implications for Rational Drug Design

G protein-coupled receptors (GPCRs) comprise a large class of transmembrane proteins that play critical roles in both normal physiology and pathophysiology. These critical roles offer targets for therapeutic intervention, as exemplified by the substantial fraction of current pharmaceutical agents that target members of this family. Tremendous contributions to our understanding of GPCR structure and dynamics have come from both indirect and direct structural characterization techniques. Key features of GPCR conformations derived from both types of characterization techniques are reviewed.

Docking-based virtual screening for ligands of G protein-coupled receptors: not only crystal structures but also in silico models

G protein-coupled receptors (GPCRs) regulate a wide range of physiological functions and hold great pharmaceutical interest. Using the β(2)-adrenergic receptor as a case study, this article explores the applicability of docking-based virtual screening to the discovery of GPCR ligands and defines methods intended to improve the screening performance. Our controlled computational experiments were performed on a compound dataset containing known agonists and blockers of the receptor as well as a large number of decoys. The screening based on the structure of the receptor crystallized in complex with its inverse agonist carazolol yielded excellent results, with a clearly delineated prioritization of ligands over decoys. Blockers generally were preferred over agonists; however, agonists were also well distinguished from decoys. A method was devised to increase the screening yields by generating an ensemble of alternative conformations of the receptor that accounts for its flexibility. Moreover, a method was devised to improve the retrieval of agonists, based on the optimization of the receptor around a known agonist. Finally, the applicability of docking-based virtual screening also to homology models endowed with different levels of accuracy was proved. This last point is of uttermost importance, since crystal structures are available only for a limited number of GPCRs, and extends our conclusions to the entire superfamily. The outcome of this analysis definitely supports the application of computer-aided techniques to the discovery of novel GPCR ligands, especially in light of the fact that, in the near future, experimental structures are expected to be solved and become available for an ever increasing number of GPCRs.

Functionalized congeners of P2Y1 receptor antagonists: 2-alkynyl (N)-methanocarba 2'-deoxyadenosine 3',5'-bisphosphate analogues and conjugation to a polyamidoamine (PAMAM) dendrimer carrier

The P2Y(1) receptor is a prothrombotic G protein-coupled receptor (GPCR) activated by ADP. Preference for the North (N) ring conformation of the ribose moiety of adenine nucleotide 3',5'-bisphosphate antagonists of the P2Y(1) receptor was established by using a ring-constrained methanocarba (a bicyclo[3.1.0]hexane) ring as a ribose substitute. A series of covalently linkable N(6)-methyl-(N)-methanocarba-2'-deoxyadenosine-3',5'-bisphosphates containing extended 2-alkynyl chains was designed, and binding affinity at the human (h) P2Y(1) receptor determined. The chain of these functionalized congeners contained hydrophilic moieties, a reactive substituent, or biotin, linked via an amide. Variation of the chain length and position of an intermediate amide group revealed high affinity of carboxylic congener 8 (K(i) 23 nM) and extended amine congener 15 (K(i) 132 nM), both having a 2-(1-pentynoyl) group. A biotin conjugate 18 containing an extended epsilon-aminocaproyl spacer chain exhibited higher affinity than a shorter biotinylated analogue. Alternatively, click coupling of terminal alkynes of homologous 2-dialkynyl nucleotide derivatives to alkyl azido groups produced triazole derivatives that bound to the P2Y(1) receptor following deprotection of the bisphosphate groups. The preservation of receptor affinity of the functionalized congeners was consistent with new P2Y(1) receptor modeling and ligand docking. Attempted P2Y(1) antagonist conjugation to PAMAM dendrimer carriers by amide formation or palladium-catalyzed reaction between an alkyne on the dendrimer and a 2-iodopurine-derivatized nucleotide was unsuccessful. A dialkynyl intermediate containing the chain length favored in receptor binding was conjugated to an azide-derivatized dendrimer, and the conjugate inhibited ADP-promoted human platelet aggregation. This is the first example of attaching a strategically functionalized P2Y receptor antagonist to a PAMAM dendrimer to produce a multivalent conjugate exhibiting a desired biological effect, i.e., antithrombotic action.

Design, synthesis and in vitro evaluation of (R)-4-(2-(tert-butylamino)-1-hydroxyethyl)-2-(hydroxymethyl)phenyl hydrogen phenylboronate: a novel salbutamol derivative with high intrinsic efficacy on the β2 adrenoceptor

We tested a set of boron containing arylethanolamine derivatives on the human and guinea pig β(2) adrenoceptor (β(2)AR) 3-D structures by docking methodology. The compound with the highest affinity based on docking analysis, (R)-4-(2-(tert-butylamino)-1-hydroxyethyl)-2-(hydroxymethyl)phenyl hydrogen phenylboronate (boronterol) was synthesized, characterized and tested in guinea pig tracheal rings at basal tone and with histamine-induced contractions. Boronterol was at least eightfold more potent than salbutamol as a smooth muscle relaxant drug (judged by the EC(50) values) and showed a similar maximal relaxant effect as isoproterenol. ICI118,551 showed competitive antagonism on the relaxing effect of boronterol. These results suggest the β(2)AR agonist action of boronterol.

Interaction of novel hybrid compounds with the D3 dopamine receptor: Site-directed mutagenesis and homology modeling studies

The dopamine D3 receptor has been implicated as a potential target for drug development in various complex psychiatric disorders including psychosis, drug dependence, and Parkinson's disease. In our overall goal to develop molecules with preferential affinity at D3 receptors, we undertook a hybrid drug development approach by combining a known dopamine agonist moiety with a substituted piperazine fragment. In the present study, three compounds produced this way with preferential D3 agonist activity, were tested at D3 receptors with mutations in the agonist binding pocket of three residues known to be important for agonist binding activity. At S192A and T369V, the hybrid agonist compounds produced an interaction profile in [(3)H]spiperone binding assays similar to that of the parent 5-OH-DPAT and 7-OH-DPAT molecules. The loss of affinity at the S192A mutant was most prominent for 5-OH-DPAT and its corresponding hybrid compound D237. D110N did not show any radioligand binding. Homology modeling indicated that 7-OH-DPAT-derived D315 uniquely shares H-bonding with Tyr365 which produced favorable interaction and no loss of H-bonding in the S192A mutant, suggesting that agonist activity may not be solely controlled by residues in the binding pocket.

Insights into the binding of Phenyltiocarbamide (PTC) agonist to its target human TAS2R38 bitter receptor

Humans' bitter taste perception is mediated by the hTAS2R subfamily of the G protein-coupled membrane receptors (GPCRs). Structural information on these receptors is currently limited. Here we identify residues involved in the binding of phenylthiocarbamide (PTC) and in receptor activation in one of the most widely studied hTAS2Rs (hTAS2R38) by means of structural bioinformatics and molecular docking. The predictions are validated by site-directed mutagenesis experiments that involve specific residues located in the putative binding site and trans-membrane (TM) helices 6 and 7 putatively involved in receptor activation. Based on our measurements, we suggest that (i) residue N103 participates actively in PTC binding, in line with previous computational studies. (ii) W99, M100 and S259 contribute to define the size and shape of the binding cavity. (iii) W99 and M100, along with F255 and V296, play a key role for receptor activation, providing insights on bitter taste receptor activation not emerging from the previously reported computational models.

Structure-based drug discovery and protein targets in the CNS

Structure-based methods are having an increasing role and impact in drug discovery. The crystal structures of an increasing number of therapeutic targets are becoming available. These structures can transform our understanding of how these proteins perform their biological function and often provide insights into the molecular basis of disease. In addition, the structures can help the discovery process. Methods such as virtual screening and experimental fragment screening can provide starting hit compounds for a discovery project. Crystal structures of compounds bound to the protein can direct or guide the medicinal chemistry optimisation to improve drug-like properties - not only providing ideas on how to improve binding affinity or selectivity, but also showing where the compound can be modified in attempting to modulate physico-chemical properties and biological efficacy. The majority of drug discovery projects against globular protein targets now use these methods at some stage. This review provides a summary of the range of structure-based drug discovery methods that are in use and surveys the suitability of the methods for targets currently identified for CNS drugs. Until recently, structure-based discovery was difficult or unknown for these targets. The recent determination of the structures of a number of GPCR proteins, together with the steady increase in structures for other membrane proteins, is opening up the possibility for these structure-based methods to find increased use in drug discovery for CNS diseases and conditions.

Modern homology modeling of G-protein coupled receptors: which structural template to use?

The recent availability in the literature of new crystal structures of inactive G-protein coupled receptors (GPCRs) prompted us to study the extent to which these crystal structures constitute an advantage over the former prototypic rhodopsin template for homology modeling of the transmembrane (TM) region of human class A GPCRs. Our results suggest that better templates than those currently available are required by the majority of these GPCRs to generate homology models that are accurate enough for simple virtual screening aimed at computer-aided drug discovery. Thus, we investigated: (1) which class A GPCRs would have the highest impact as potential templates for homology modeling of other GPCRs, if their structures were solved, and (2) the extent to which multiple-template homology modeling (using all currently available GPCR crystal structures) provides an improvement over single-template homology modeling, as evaluated by the accuracy of rigid protein-flexible ligand docking on these models.

Molecular modeling studies on the human neuropeptide S receptor and its antagonists

Neuropeptide S (NPS) is a 20-residue peptide of great interest due to its potential involvement in several biological processes such as arousal, anxiety, and food intake. The NPS receptor belongs to the rhodopsin-like G-protein-coupled receptor superfamily, and several polymorphisms and isoforms of this receptor are associated with asthma, allergies, and bronchial hyper-responsiveness, in particular the Asn 107 Ile mutation. Limited structural information is available for this peptide-receptor system, particularly regarding the NPS receptor structure, its nonpeptide ligands, and the molecular aspects of agonist and antagonist binding processes. In this work, rhodopsin-based homology models of the NPS receptor and its Asn 107 Ile variant were built and refined in a membrane bilayer model, and binding modes for nonpeptide antagonists were simulated. This study provides the first structural study of the human NPS receptor, and the results provide a starting point for further characterization of the binding modes of its antagonists, and for the rational design of new NPS receptor ligands.

Non-basic ligands for aminergic GPCRs: the discovery and development diaryl sulfones as selective, orally bioavailable 5-HT2A receptor antagonists for the treatment of sleep disorders

Scaffold hopping from a non-basic series of 5-HT(2A) receptor antagonists developed in-house that possessed reduced activity in vivo enabled the discovery of a novel series of diaryl sulfones that gave excellent occupancy on oral dosing. Not only does this work further demonstrate that oral bioavailability of a given series can be enhanced by improving physicochemical parameters such as log P, but it corroborates the growing evidence that a protonated amine is not essential for affinity at aminergic GPCRs.

Forced unbinding of GPR17 ligands from wild type and R255I mutant receptor models through a computational approach

Background

GPR17 is a hybrid G-protein-coupled receptor (GPCR) activated by two unrelated ligand families, extracellular nucleotides and cysteinyl-leukotrienes (cysteinyl-LTs), and involved in brain damage and repair. Its exploitment as a target for novel neuro-reparative strategies depends on the elucidation of the molecular determinants driving binding of purinergic and leukotrienic ligands. Here, we applied docking and molecular dynamics simulations (MD) to analyse the binding and the forced unbinding of two GPR17 ligands (the endogenous purinergic agonist UDP and the leukotriene receptor antagonist pranlukast from both the wild-type (WT) receptor and a mutant model, where a basic residue hypothesized to be crucial for nucleotide binding had been mutated (R255I) to Ile.

Results

MD suggested that GPR17 nucleotide binding pocket is enclosed between the helical bundle and extracellular loop (EL) 2. The driving interaction involves R255 and the UDP phosphate moiety. To support this hypothesis, steered MD experiments showed that the energy required to unbind UDP is higher for the WT receptor than for R255I. Three potential binding sites for pranlukast where instead found and analysed. In one of its preferential docking conformations, pranlukast tetrazole group is close to R255 and phenyl rings are placed into a subpocket highly conserved among GPCRs. Pulling forces developed to break polar and aromatic interactions of pranlukast were comparable. No differences between the WT receptor and the R255I receptor were found for the unbinding of pranlukast.

Conclusions

These data thus suggest that, in contrast to which has been hypothesized for nucleotides, the lack of the R255 residue doesn't affect the binding of pranlukast a crucial role for R255 in binding of nucleotides to GPR17. Aromatic interactions are instead likely to play a predominant role in the recognition of pranlukast, suggesting that two different binding subsites are present on GPR17.

Unraveling the structure and function of G protein-coupled receptors through NMR spectroscopy

G protein-coupled receptors (GPCRs) are a large superfamily of signaling proteins expressed on the plasma membrane. They are involved in a wide range of physiological processes and, therefore, are exploited as drug targets in a multitude of therapeutic areas. In this extent, knowledge of structural and functional properties of GPCRs may greatly facilitate rational design of modulator compounds. Solution and solid-state nuclear magnetic resonance (NMR) spectroscopy represents a powerful method to gather atomistic insights into protein structure and dynamics. In spite of the difficulties inherent the solution of the structure of membrane proteins through NMR, these methods have been successfully applied, sometimes in combination with molecular modeling, to the determination of the structure of GPCR fragments, the mapping of receptor-ligand interactions, and the study of the conformational changes associated with the activation of the receptors. In this review, we provide a summary of the NMR contributions to the study of the structure and function of GPCRs, also in light of the published crystal structures.

Progress in elucidating the structural and dynamic character of G Protein-Coupled Receptor oligomers for use in drug discovery

G Protein-Coupled Receptors (GPCRs) are the most targeted group of proteins for the development of therapeutic drugs. Until the last decade, structural information about this family of membrane proteins was relatively scarce, and their mechanisms of ligand binding and signal transduction were modeled on the assumption that GPCRs existed and functioned as monomeric entities. New crystal structures of native and engineered GPCRs, together with important biochemical and biophysical data that reveal structural details of the activation mechanism(s) of this receptor family, provide a valuable framework to improve dynamic molecular models of GPCRs with the ultimate goal of elucidating their allostery and functional selectivity. Since the dynamic movements of single GPCR protomers are likely to be affected by the presence of neighboring interacting subunits, oligomeric arrangements should be taken into account to improve the predictive ability of computer-assisted structural models of GPCRs for effective use in drug design.

Docking studies on a refined human beta(2) adrenoceptor model yield theoretical affinity values in function with experimental values for R-ligands, but not for S-antagonists

G-protein coupled receptors (GPCR) belong to the largest group of membrane proteins involved in signal transduction. These receptors are implicated in diverse physiological and pathological events. The human beta(2) adrenergic receptor (hbeta(2)AR) is one of the few GPCRs whose 3-D structures are available on the Protein Data Bank. Because there is great interest by drug developers for hbeta(2)AR as a target, it is necessary to study its ligand-recognition process at the atomic level. The hbeta(2)AR can recognize both R/S enantiomeric ligands, R-agonists result in a greater activation than do S-agonists (eutomers and distomers for activation, respectively), according to experimental results. In this work is reported the ligand recognition on a refined hbeta(2)AR-structure of a set of well-known R/S-ligands by means of docking studies. Data obtained in silico were analyzed and compared with those reported in vitro. The theoretical affinity values were reproduced for agonists, but not for antagonist (or inverse agonists). However, theoretical data for R-antagonists are in function to experimental data. The theoretical results confirm the role of amino acids previously reported by mutagenesis studies due to their important roles in drug affinity and stereoselectivity.

Ligand and structure-based models for the prediction of ligand-receptor affinities and virtual screenings: Development and application to the beta(2)-adrenergic receptor

In this study, we evaluated the applicability of ligand-based and structure-based models to quantitative affinity predictions and virtual screenings for ligands of the beta(2)-adrenergic receptor, a G protein-coupled receptor (GPCR). We also devised and evaluated a number of consensus models obtained through partial least square regressions, to combine the strengths of the individual components. In all cases, the bioactive conformation of each ligand was derived from molecular docking at the crystal structure of the receptor. We identified the most effective models applicable to the different scenarios, in the presence or in the absence of a training set. For ranking the affinity of closely related analogs when a training set is available, a ligand-based consensus model (LI-CM) seems to be the best choice, while the structure-based MM-GBSA score seems the best alternative in the absence of a training set. For virtual screening purposes, the structure-based MM-GBSA score was found to be the method of choice. Consensus models consistently had performances superior or close to those of the best individual components, and were endowed with a significantly increased robustness. Given multiple models with no a priori knowledge of their predictive capabilities, constructing a consensus model ensures results very close to those that the best model alone would have yielded.

Beyond rhodopsin: G protein-coupled receptor structure and modeling incorporating the beta2-adrenergic and adenosine A(2A) crystal structures

For quite some time, the majority of GPCR models have been based on a single template structure: dark-adapted bovine rhodopsin. The recent solution of β2AR, β1AR and adenosine A(2A) receptor crystal structures has dramatically expanded the GPCR structural landscape and provided many new insights into receptor conformation and ligand binding. They will serve as templates for the next generation of GPCR models, but also allow direct validation of previous models and computational techniques. This review summarizes key findings from the new structures, comparison of existing models to these structures and highlights new models constructed from these templates.

Modeling G Protein-Coupled Receptors: a Concrete Possibility

G protein-coupled receptors (GPCRs) are a large superfamily of membrane bound signaling proteins that are involved in the regulation of a wide range of physiological functions and constitute the most common target for therapeutic intervention. Due to the paucity of crystal structures, homology modeling has become a widespread technique for the construction of GPCR models, which have been applied to the study of their structure-function relationships and to the identification of lead ligands through virtual screening. Rhodopsin has been for years the only available template. However, recent breakthroughs in GPCR crystallography have led to the solution of the structures of a few additional receptors. In light of these newly elucidated crystal structures, we have been able to produce a substantial amount of data to demonstrate that accurate models of GPCRs in complex with their ligands can be constructed through homology modeling followed by fully flexible molecular docking. These results have been confirmed by our success in the first blind assessment of GPCR modeling and docking, organized in coordination with the solution of the X-ray structure of the adenosine A(2A) receptor. Taken together, these data indicate that: a) the transmembrane helical bundle can be modeled with considerable accuracy; b) predicting the binding mode of a ligand, although doable, is challenging; c) modeling of the extracellular and intracellular loops is still problematic.

Toward the discovery of vaccine adjuvants: coupling in silico screening and in vitro analysis of antagonist binding to human and mouse CCR4 receptors

Background

Adjuvants enhance or modify an immune response that is made to an antigen. An antagonist of the chemokine CCR4 receptor can display adjuvant-like properties by diminishing the ability of CD4+CD25+ regulatory T cells (Tregs) to down-regulate immune responses.

Methodology

Here, we have used protein modelling to create a plausible chemokine receptor model with the aim of using virtual screening to identify potential small molecule chemokine antagonists. A combination of homology modelling and molecular docking was used to create a model of the CCR4 receptor in order to investigate potential lead compounds that display antagonistic properties. Three-dimensional structure-based virtual screening of the CCR4 receptor identified 116 small molecules that were calculated to have a high affinity for the receptor; these were tested experimentally for CCR4 antagonism. Fifteen of these small molecules were shown to inhibit specifically CCR4-mediated cell migration, including that of CCR4⁺ Tregs.

Significance

Our CCR4 antagonists act as adjuvants augmenting human T cell proliferation in an in vitro immune response model and compound SP50 increases T cell and antibody responses in vivo when combined with vaccine antigens of Mycobacterium tuberculosis and Plasmodium yoelii in mice.

A Selective Pharmacophore Model for beta(2)-Adrenoceptor Agonists

β₂-Adrenoceptor selectivity is an important consideration in drug design in order to minimize the possibility of side effects. A selective pharmacophore model was developed based on a series of selective β₂-adrenoceptor agonists. The best pharmacophore hypothesis consisted of five chemical features (one hydrogen-bond acceptor, one hydrogen-bond donor, two ring aromatic and one positive ionizable feature). The result was nearly in accordance with the reported interactions between the β₂-adrenoceptor and agonists, and it shared enough similar features with the result of field point patterns by FieldTemplater, which mainly validated the pharmacophore model. Moreover, the pharmacophore could predict the selectivity over the β₁-adrenoceptor. These results might provide guidance for the rational design of novel potent and selective β₂-adrenoceptor agonists.

Ligand and structure-based methodologies for the prediction of the activity of G protein-coupled receptor ligands

Accurate in silico models for the quantitative prediction of the activity of G protein-coupled receptor (GPCR) ligands would greatly facilitate the process of drug discovery and development. Several methodologies have been developed based on the properties of the ligands, the direct study of the receptor-ligand interactions, or a combination of both approaches. Ligand-based three-dimensional quantitative structure-activity relationships (3D-QSAR) techniques, not requiring knowledge of the receptor structure, have been historically the first to be applied to the prediction of the activity of GPCR ligands. They are generally endowed with robustness and good ranking ability; however they are highly dependent on training sets. Structure-based techniques generally do not provide the level of accuracy necessary to yield meaningful rankings when applied to GPCR homology models. However, they are essentially independent from training sets and have a sufficient level of accuracy to allow an effective discrimination between binders and nonbinders, thus qualifying as viable lead discovery tools. The combination of ligand and structure-based methodologies in the form of receptor-based 3D-QSAR and ligand and structure-based consensus models results in robust and accurate quantitative predictions. The contribution of the structure-based component to these combined approaches is expected to become more substantial and effective in the future, as more sophisticated scoring functions are developed and more detailed structural information on GPCRs is gathered.

Structural basis of the selectivity of the beta(2)-adrenergic receptor for fluorinated catecholamines

The important and diverse biological functions of adrenergic receptors, a subclass of G protein-coupled receptors (GPCRs), have made the search for compounds that selectively stimulate or inhibit the activity of different adrenergic receptor subtypes an important area of medicinal chemistry. We previously synthesized 2-, 5-, and 6-fluoronorepinehprine (FNE) and 2-, 5-, and 6-fluoroepinephrine (FEPI) and found that 2FNE and 2FEPI were selective beta-adrenergic agonists and that 6FNE and 6FEPI were selective alpha-adrenergic agonists, while 5FNE and 5FEPI were unselective. Agonist potencies correlated well with receptor binding affinities. Here, through a combination of molecular modeling and site-directed mutagenesis, we have identified N293 in the beta(2)-adrenergic receptor as a crucial residue for the selectivity of the receptor for catecholamines fluorinated at different positions.

Comparative sequence and structural analyses of G-protein-coupled receptor crystal structures and implications for molecular models

BACKGROUND

Up until recently the only available experimental (high resolution) structure of a G-protein-coupled receptor (GPCR) was that of bovine rhodopsin. In the past few years the determination of GPCR structures has accelerated with three new receptors, as well as squid rhodopsin, being successfully crystallized. All share a common molecular architecture of seven transmembrane helices and can therefore serve as templates for building molecular models of homologous GPCRs. However, despite the common general architecture of these structures key differences do exist between them. The choice of which experimental GPCR structure(s) to use for building a comparative model of a particular GPCR is unclear and without detailed structural and sequence analyses, could be arbitrary. The aim of this study is therefore to perform a systematic and detailed analysis of sequence-structure relationships of known GPCR structures.

METHODOLOGY

We analyzed in detail conserved and unique sequence motifs and structural features in experimentally-determined GPCR structures. Deeper insight into specific and important structural features of GPCRs as well as valuable information for template selection has been gained. Using key features a workflow has been formulated for identifying the most appropriate template(s) for building homology models of GPCRs of unknown structure. This workflow was applied to a set of 14 human family A GPCRs suggesting for each the most appropriate template(s) for building a comparative molecular model.

CONCLUSIONS

The available crystal structures represent only a subset of all possible structural variation in family A GPCRs. Some GPCRs have structural features that are distributed over different crystal structures or which are not present in the templates suggesting that homology models should be built using multiple templates. This study provides a systematic analysis of GPCR crystal structures and a consistent method for identifying suitable templates for GPCR homology modelling that will help to produce more reliable three-dimensional models.

Molecular dynamics simulation of the heterodimeric mGluR2/5HT(2A) complex. An atomistic resolution study of a potential new target in psychiatric conditions

Homo- and heterodimerization is becoming an assessed concept in G-protein coupled receptor (GPCR) pharmacology, and the notion that GPCRs may dimerize or oligomerize is allowing for a reinterpretation of some inconsistencies or anomalies and is providing medicinal chemists with potentially relevant novel molecular targets for a variety of therapeutic conditions. Recently, it has been reported that two unrelated GPCRs, namely class C metabotropic glutamate receptor type-2 (mGluR2) and class A 5HT(2A) serotoninergic receptor, can heterodimerize at the transmembrane domain level. We performed a 40 ns molecular dynamics simulation of the mGluR2/5HT(2A) heterocomplex constructed around a TM4/TM5 interface and embedded in an explicit phospholipidic bilayer surrounded by water molecules. In a separate experiment, the monomeric 5HT(2A) receptor was simulated for additional 40 ns under the same conditions. The analysis and the comparison of the two simulations allowed us to clearly identify a cross-talk between the two protomers and to put forward an effect of the heterodimerization on the shape of the binding pocket of 5HT(2A). This result provides the first molecular explanation for the reported allosteric effect of mGluR2 on 5HT(2A)-mediated response and suggests that the heterocomplex can be a more suitable target for in silico screening than the monomeric protomers.

Computational toxicology: an overview of the sources of data and of modelling methods

BACKGROUND

Toxicology has the goal of ensuring the safety of humans, animals and the environment. Computational toxicology is an area of active development and great potential. There are tangible reasons for the emerging interest in this discipline from academia, industry, regulatory bodies and governments.

RESULTS

Pharmaceuticals, personal health care products, nutritional ingredients and products of the chemical industries are all potential hazards and need to be assessed. Toxicological tests for these products are costly, frequently use laboratory animals and are time-consuming. This delays end-user access to improved products or, conversely, the timely withdrawal of dangerous substances from the market. The aim of computational toxicology is to accelerate the assessment of potentially dangerous substances through in silico models.

CONCLUSIONS

In this review, we provide an overview of the development of models for computational toxicology. Addressing the significant divide between the experimental and computational worlds-believed to be a prime hindrance to computational toxicology-we briefly consider the fundamental issue of toxicological data and the assays they stem from. Different kinds of models that can be built using such data are presented: computational filters, models for specific toxicological endpoints and tools for the generation of testable hypotheses.

Key determinants of nucleotide-activated G protein-coupled P2Y(2) receptor function revealed by chemical and pharmacological experiments, mutagenesis and homology modeling

The P2Y(2) receptor, which is activated by UTP, ATP, and dinucleotides, was studied as a prototypical nucleotide-activated GPCR. A combination of receptor mutagenesis, determination of its effects on potency and efficacy of agonists and antagonists, homology modeling, and chemical experiments was applied. R272 (extracellular loop EL3) was found to play a gatekeeper role, presumably responsible for recognition and orientation of the nucleotides. R272 is also directly involved in binding of dinucleotides, which behaved as partial agonists. Y118A (3.37) mutation led to dramatically reduced efficacy of agonists; it is part of the entry channel as well as the triphosphate binding site. While the Y114A (3.33) mutation did not have any effect on agonist activities, the antagonist Reactive Blue 2 (6) was completely inactive at that mutant. The disulfide bridge Cys25-Cys278 was found to be important for agonist potency but neither for agonist efficacy nor for antagonist potency.

Evaluation of homology modeling of G-protein-coupled receptors in light of the A(2A) adenosine receptor crystallographic structure

Homology modeling of the human A(2A) adenosine receptor (AR) based on bovine rhodopsin predicted a protein structure that was very similar to the recently determined crystallographic structure. The discrepancy between the experimentally observed orientation of the antagonist and those obtained by previous antagonist docking is related to the loop structure of rhodopsin being carried over to the model of the A(2A) AR and was rectified when the beta(2)-adrenergic receptor was used as a template for homology modeling. Docking of the triazolotriazine antagonist ligand ZM241385 1 was greatly improved by including water molecules of the X-ray structure or by using a constraint from mutagenesis. Automatic agonists docking to both a new homology modeled receptor and the A(2A) AR crystallographic structure produced similar results. Heterocyclic nitrogen atoms closely corresponded when the docked adenine moiety of agonists and 1 were overlaid. The cumulative mutagenesis data, which support the proposed mode of agonist docking, can be reexamined in light of the crystallographic structure. Thus, homology modeling of GPCRs remains a useful technique in probing the structure of the protein and predicting modes of ligand docking.

Increasingly accurate dynamic molecular models of G-protein coupled receptor oligomers: Panacea or Pandora's box for novel drug discovery?

For years, conventional drug design at G-protein coupled receptors (GPCRs) has mainly focused on the inhibition of a single receptor at a usually well-defined ligand-binding site. The recent discovery of more and more physiologically relevant GPCR dimers/oligomers suggests that selectively targeting these complexes or designing small molecules that inhibit receptor-receptor interactions might provide new opportunities for novel drug discovery. To uncover the fundamental mechanisms and dynamics governing GPCR dimerization/oligomerization, it is crucial to understand the dynamic process of receptor-receptor association, and to identify regions that are suitable for selective drug binding. This minireview highlights current progress in the development of increasingly accurate dynamic molecular models of GPCR oligomers based on structural, biochemical, and biophysical information that has recently appeared in the literature. In view of this new information, there has never been a more exciting time for computational research into GPCRs than at present. Information-driven modern molecular models of GPCR complexes are expected to efficiently guide the rational design of GPCR oligomer-specific drugs, possibly allowing researchers to reach for the high-hanging fruits in GPCR drug discovery, i.e. more potent and selective drugs for efficient therapeutic interventions.

Homology modeling in drug discovery: current trends and applications

As structural genomics (SG) projects continue to deposit representative 3D structures of proteins, homology modeling methods will play an increasing role in structure-based drug discovery. Although computational structure prediction methods provide a cost-effective alternative in the absence of experimental structures, developing accurate enough models still remains a big challenge. In this contribution, we report the current developments in this field, discuss in silico modeling limitations, and review the successful application of this technique to different stages of the drug discovery process.

Comparative docking study of anibamine as the first natural product CCR5 antagonist in CCR5 homology models

Anibamine, a novel pyridine quaternary alkaloid recently isolated from Aniba sp., has been found to effectively bind to the chemokine receptor CCR5 with an IC(50) at 1 microM in competition with (125)I-gp120, an HIV viral envelope protein binding to CCR5 with high affinity. Since CCR5, a G-protein-coupled receptor, is an essential coreceptor for the human immunodeficiency virus type I (HIV-1) entry to host cells, a CCR5 antagonist that inhibits the cellular entry of HIV-1 provides a new therapy choice for the treatment of HIV. Anibamine provides a novel structural skeleton that is remarkably different from all lead compounds previously identified as CCR5 antagonists. Here, we report comparative docking studies of anibamine with several other known CCR5 antagonists in two CCR5 homology models built based on the crystal structures of bovine rhodopsin and human beta(2)-adrenergic receptor. The binding pocket of anibamine has some common features shared with other high affinity CCR5 antagonists, suggesting that they may bind in similar binding sites and/or modes. At the same time, several unique binding features of anibamine were identified, and it will likely prove beneficial in future molecular design of novel CCR5 antagonists based on the anibamine scaffold.

Computational molecular biology approaches to ligand-target interactions

Binding of small molecules to their targets triggers complex pathways. Computational approaches are keys for predictions of the molecular events involved in such cascades. Here we review current efforts at characterizing the molecular determinants in the largest membrane-bound receptor family, the G-protein-coupled receptors (GPCRs). We focus on odorant receptors, which constitute more than half GPCRs. The work presented in this review uncovers structural and energetic aspects of components of the cellular cascade. Finally, a computational approach in the context of radioactive boron-based antitumoral therapies is briefly described.

Computing highly correlated positions using mutual information and graph theory for G protein-coupled receptors

G protein-coupled receptors (GPCRs) are a superfamily of seven transmembrane-spanning proteins involved in a wide array of physiological functions and are the most common targets of pharmaceuticals. This study aims to identify a cohort or clique of positions that share high mutual information. Using a multiple sequence alignment of the transmembrane (TM) domains, we calculated the mutual information between all inter-TM pairs of aligned positions and ranked the pairs by mutual information. A mutual information graph was constructed with vertices that corresponded to TM positions and edges between vertices were drawn if the mutual information exceeded a threshold of statistical significance. Positions with high degree (i.e. had significant mutual information with a large number of other positions) were found to line a well defined inter-TM ligand binding cavity for class A as well as class C GPCRs. Although the natural ligands of class C receptors bind to their extracellular N-terminal domains, the possibility of modulating their activity through ligands that bind to their helical bundle has been reported. Such positions were not found for class B GPCRs, in agreement with the observation that there are not known ligands that bind within their TM helical bundle. All identified key positions formed a clique within the MI graph of interest. For a subset of class A receptors we also considered the alignment of a portion of the second extracellular loop, and found that the two positions adjacent to the conserved Cys that bridges the loop with the TM3 qualified as key positions. Our algorithm may be useful for localizing topologically conserved regions in other protein families.

Comparative analysis of GPCR crystal structures

The phototransduction cascade is perhaps the best understood model system for G protein-coupled receptor (GPCR) signaling. Phototransduction links the absorption of a single photon of light to a decrease in cytosolic cGMP. Depletion of the cGMP pool induces closure of cGMP-gated cation channels resulting in the hyperpolarization of photoreceptor cells and consequently a neuronal response. Many biochemical and both low- and high-resolution structural approaches have been utilized to increase our understanding of rhodopsin, the key molecule of this signaling cascade. Rhodopsin, a member of the GPCR or seven-transmembrane spanning receptor superfamily, is composed of a chromophore, 11-cis-retinal that is covalently bound by a protonated Schiff base linkage to the apo-protein opsin at Lys(296) (in bovine opsin). Upon absorption of a photon, isomerization of the chromophore to an all-trans-retinylidene conformation induces changes in the rhodopsin structure, ultimately converting it from an inactive to an activated state. This state allows it to activate the heterotrimeric G protein, transducin, by triggering nucleotide exchange. To fully understand the structural and functional aspects of rhodopsin it is necessary to critically examine crystal structures of its different photointermediates. In this review we summarize recent progress on the structure and activation of rhodopsin in the context of other GPCR structures.

Identifying conformational changes of the beta(2) adrenoceptor that enable accurate prediction of ligand/receptor interactions and screening for GPCR modulators

The new beta(2) Adrenoceptor (beta(2)AR) crystal structures provide a high-resolution snapshot of receptor interactions with two particular partial inverse agonists, (-)-carazolol and timolol. However, both experimental and computational studies of GPCR structure are significantly complicated by the existence of multiple conformational states coupled to ligand type and receptor activity. Agonists and antagonists induce or stabilize distinct changes in receptor structure that mediate a range of pharmacological activities. In this work, we (1) established that the existing beta(2)AR crystallographic conformers can be extended to describe ligand/receptor interactions for additional antagonist types, (2) generated agonist-bound receptor conformations, and (3) validated these models for agonist and antagonist virtual ligand screening (VLS). Using a ligand directed refinement protocol, we derived a single agonist-bound receptor conformation that selectively retrieved a diverse set of full and partial beta(2)AR agonists in VLS trials. Additionally, the impact of extracellular loop two conformation on VLS was assessed by docking studies with rhodopsin-based beta(2)AR homology models, and loop-deleted receptor models. A general strategy for constructing and selecting agonist-bound receptor pocket conformations is presented, which may prove broadly useful in creating agonist and antagonist bound models for other GPCRs.