Structure-based discovery of A2A adenosine receptor ligands

C(X)CR in silico: Computer-aided prediction of chemokine receptor-ligand interactions

This review will focus on the construction, refinement, and validation of chemokine receptor models for the purpose of structure-based virtual screening and ligand design. The review will present a comparative analysis of ligand binding pockets in chemokine receptors, including a review of the recently released CXCR4 X-ray structures, and their implication on chemokine receptor (homology) modeling. The recommended protein-ligand modeling procedure as well as the use of experimental anchors to steer the modeling procedure is discussed and an overview of several successful structure-based ligand discovery and design studies is provided. This review shows that receptor models, despite structural inaccuracies, can be efficiently used to find novel ligands for chemokine receptors.:

Polypharmacology: challenges and opportunities in drug discovery

At present, the legendary magic bullet, i.e., a drug with high potency and selectivity toward a specific biological target, shares the spotlight with an emerging and alternative polypharmacology approach. Polypharmacology suggests that more effective drugs can be developed by specifically modulating multiple targets. It is generally thought that complex diseases such as cancer and central nervous system diseases may require complex therapeutic approaches. In this respect, a drug that "hits" multiple sensitive nodes belonging to a network of interacting targets offers the potential for higher efficacy and may limit drawbacks generally arising from the use of a single-target drug or a combination of multiple drugs. In this review, we will compare advantages and disadvantages of multitarget versus combination therapies, discuss potential drug promiscuity arising from off-target effects, comment on drug repurposing, and introduce approaches to the computational design of multitarget drugs.

Selecting an optimal number of binding site waters to improve virtual screening enrichments against the adenosine A2A receptor

A major challenge in structure-based virtual screening (VS) involves the treatment of explicit water molecules during docking in order to improve the enrichment of active compounds over decoys. Here we have investigated this in the context of the adenosine A2A receptor, where water molecules have previously been shown to be important for achieving high enrichment rates with docking, and where the positions of some binding site waters are known from a high-resolution crystal structure. The effect of these waters (both their presence and orientations) on VS enrichment was assessed using a carefully curated set of 299 high affinity A2A antagonists and 17,337 decoys. We show that including certain crystal waters greatly improves VS enrichment and that optimization of water hydrogen positions is needed in order to achieve the best results. We also show that waters derived from a molecular dynamics simulation - without any knowledge of crystallographic waters - can improve enrichments to a similar degree as the crystallographic waters, which makes this strategy applicable to structures without experimental knowledge of water positions. Finally, we used decision trees to select an ensemble of structures with different water molecule positions and orientations that outperforms any single structure with water molecules. The approach presented here is validated against independent test sets of A2A receptor antagonists and decoys from the literature. In general, this water optimization strategy could be applied to any target with waters-mediated protein-ligand interactions.

Compound activity prediction using models of binding pockets or ligand properties in 3D

Transient interactions of endogenous and exogenous small molecules with flexible binding sites in proteins or macromolecular assemblies play a critical role in all biological processes. Current advances in high-resolution protein structure determination, database development, and docking methodology make it possible to design three-dimensional models for prediction of such interactions with increasing accuracy and specificity. Using the data collected in the Pocketome encyclopedia, we here provide an overview of two types of the three-dimensional ligand activity models, pocketbased and ligand property-based, for two important classes of proteins, nuclear and G-protein coupled receptors. For half the targets, the pocket models discriminate actives from property matched decoys with acceptable accuracy (the area under ROC curve, AUC, exceeding 84%) and for about one fifth of the targets with high accuracy (AUC > 95%). The 3D ligand property field models performed better than 95% in half of the cases. The high performance models can already become a basis of activity predictions for new chemicals. Family-wide benchmarking of the models highlights strengths of both approaches and helps identify their inherent bottlenecks and challenges.

SAMPL4 & DOCK3.7: lessons for automated docking procedures

The SAMPL4 challenges were used to test current automated methods for solvation energy, virtual screening, pose and affinity prediction of the molecular docking pipeline DOCK 3.7. Additionally, first-order models of binding affinity were proposed as milestones for any method predicting binding affinity. Several important discoveries about the molecular docking software were made during the challenge: (1) Solvation energies of ligands were five-fold worse than any other method used in SAMPL4, including methods that were similarly fast, (2) HIV Integrase is a challenging target, but automated docking on the correct allosteric site performed well in terms of virtual screening and pose prediction (compared to other methods) but affinity prediction, as expected, was very poor, (3) Molecular docking grid sizes can be very important, serious errors were discovered with default settings that have been adjusted for all future work. Overall, lessons from SAMPL4 suggest many changes to molecular docking tools, not just DOCK 3.7, that could improve the state of the art. Future difficulties and projects will be discussed.

PeptiSite: a structural database of peptide binding sites in 4D

We developed PeptiSite, a comprehensive and reliable database of biologically and structurally characterized peptide-binding sites, in which each site is represented by an ensemble of its complexes with protein, peptide and small molecule partners. The unique features of the database include: (1) the ensemble site representation that provides a fourth dimension to the otherwise three dimensional data, (2) comprehensive characterization of the binding site architecture that may consist of a multimeric protein assembly with cofactors and metal ions and (3) analysis of consensus interaction motifs within the ensembles and identification of conserved determinants of these interactions. Currently the database contains 585 proteins with 650 peptide-binding sites. http://peptisite.ucsd.edu/ link allows searching for the sites of interest and interactive visualization of the ensembles using the ActiveICM web-browser plugin. This structural database for protein-peptide interactions enables understanding of structural principles of these interactions and may assist the development of an efficient peptide docking benchmark.

Crystal structures of the A2A adenosine receptor and their use in medicinal chemistry

New insights into drug design are derived from the X-ray crystallographic structures of G protein-coupled receptors (GPCRs), and the adenosine receptors (ARs) are at the forefront of this effort. The 3D knowledge of receptor binding and activation promises to enable drug discovery for GPCRs in general, and specifically for the ARs. The predictability of modeling based on the X-ray structures of the A_2AAR has been well demonstrated in the identification, design and modification of both known and novel AR agonists and antagonists. It is expected that structure-based design of drugs acting through ARs will provide new avenues to clinically useful agents.

Ligand pose and orientational sampling in molecular docking

Molecular docking remains an important tool for structure-based screening to find new ligands and chemical probes. As docking ambitions grow to include new scoring function terms, and to address ever more targets, the reliability and extendability of the orientation sampling, and the throughput of the method, become pressing. Here we explore sampling techniques that eliminate stochastic behavior in DOCK3.6, allowing us to optimize the method for regularly variable sampling of orientations. This also enabled a focused effort to optimize the code for efficiency, with a three-fold increase in the speed of the program. This, in turn, facilitated extensive testing of the method on the 102 targets, 22,805 ligands and 1,411,214 decoys of the Directory of Useful Decoys - Enhanced (DUD-E) benchmarking set, at multiple levels of sampling. Encouragingly, we observe that as sampling increases from 50 to 500 to 2000 to 5000 to 20000 molecular orientations in the binding site (and so from about 1×10¹⁰ to 4×10¹⁰ to 1×10¹¹ to 2×10¹¹ to 5×10¹¹ mean atoms scored per target, since multiple conformations are sampled per orientation), the enrichment of ligands over decoys monotonically increases for most DUD-E targets. Meanwhile, including internal electrostatics in the evaluation ligand conformational energies, and restricting aromatic hydroxyls to low energy rotamers, further improved enrichment values. Several of the strategies used here to improve the efficiency of the code are broadly applicable in the field.

Complementarity between in silico and biophysical screening approaches in fragment-based lead discovery against the A(2A) adenosine receptor

Fragment-based lead discovery (FBLD) is becoming an increasingly important method in drug development. We have explored the potential to complement NMR-based biophysical screening of chemical libraries with molecular docking in FBLD against the A(2A) adenosine receptor (A(2A)AR), a drug target for inflammation and Parkinson's disease. Prior to an NMR-based screen of a fragment library against the A(2A)AR, molecular docking against a crystal structure was used to rank the same set of molecules by their predicted affinities. Molecular docking was able to predict four out of the five orthosteric ligands discovered by NMR among the top 5% of the ranked library, suggesting that structure-based methods could be used to prioritize among primary hits from biophysical screens. In addition, three fragments that were top-ranked by molecular docking, but had not been picked up by the NMR-based method, were demonstrated to be A(2A)AR ligands. While biophysical approaches for fragment screening are typically limited to a few thousand compounds, the docking screen was extended to include 328,000 commercially available fragments. Twenty-two top-ranked compounds were tested in radioligand binding assays, and 14 of these were A(2A)AR ligands with K(i) values ranging from 2 to 240 μM. Optimization of fragments was guided by molecular dynamics simulations and free energy calculations. The results illuminate strengths and weaknesses of molecular docking and demonstrate that this method can serve as a valuable complementary tool to biophysical screening in FBLD.

Structure-based ligand discovery targeting orthosteric and allosteric pockets of dopamine receptors

Small molecules targeting allosteric pockets of G protein-coupled receptors (GPCRs) have a great therapeutic potential for the treatment of neurologic and other chronic disorders. Here we performed virtual screening for orthosteric and putative allosteric ligands of the human dopamine D3 receptor (D3R) using two optimized crystal-structure-based models: the receptor with an empty binding pocket (D3R(APO)), and the receptor complex with dopamine (D3R(Dopa)). Subsequent biochemical and functional characterization revealed 14 novel ligands with a binding affinity of better than 10 μM in the D3R(APO) candidate list (56% hit rate), and 8 novel ligands in the D3R(Dopa) list (32% hit rate). Most ligands in the D3R(APO) model span both orthosteric and extended pockets and behave as antagonists at D3R, with compound 7 showing the highest potency of dopamine inhibition (IC₅₀ = 7 nM). In contrast, compounds identified by the D3R(Dopa) model are predicted to occupy an allosteric site at the extracellular extension of the pocket, and they all lack the anchoring amino group. Compounds targeting the allosteric site display a variety of functional activity profiles, where behavior of at least two compounds (23 and 26) is consistent with noncompetitive allosteric modulation of dopamine signaling in the extracellular signal-regulated kinase 1 and 2 phosphorylation and β-arrestin recruitment assays. The high affinity and ligand efficiency of the chemically diverse hits identified in this study suggest utility of structure-based screening targeting allosteric sites of GPCRs.

Functional validation of virtual screening for novel agents with general anesthetic action at ligand-gated ion channels

GABA(A) receptors play a crucial role in the actions of general anesthetics. The recently published crystal structure of the general anesthetic propofol bound to Gloeobacter violaceus ligand-gated ion channel (GLIC), a bacterial homolog of GABA(A) receptors, provided an opportunity to explore structure-based ligand discovery for pentameric ligand-gated ion channels (pLGICs). We used molecular docking of 153,000 commercially available compounds to identify molecules that interact with the propofol binding site in GLIC. In total, 29 compounds were selected for functional testing on recombinant GLIC, and 16 of these compounds modulated GLIC function. Active compounds were also tested on recombinant GABA(A) receptors, and point mutations around the presumed binding pocket were introduced into GLIC and GABA(A) receptors to test for binding specificity. The potency of active compounds was only weakly correlated with properties such as lipophilicity or molecular weight. One compound was found to mimic the actions of propofol on GLIC and GABA(A), and to be sensitive to mutations that reduce the action of propofol in both receptors. Mutant receptors also provided insight about the position of the binding sites and the relevance of the receptor's conformation for anesthetic actions. Overall, the findings support the feasibility of the use of virtual screening to discover allosteric modulators of pLGICs, and suggest that GLIC is a valid model system to identify novel GABA(A) receptor ligands.

Muscarinic receptors as model targets and antitargets for structure-based ligand discovery

G protein-coupled receptors (GPCRs) regulate virtually all aspects of human physiology and represent an important class of therapeutic drug targets. Many GPCR-targeted drugs resemble endogenous agonists, often resulting in poor selectivity among receptor subtypes and restricted pharmacologic profiles. The muscarinic acetylcholine receptor family exemplifies these problems; thousands of ligands are known, but few are receptor subtype-selective and nearly all are cationic in nature. Using structure-based docking against the M2 and M3 muscarinic receptors, we screened 3.1 million molecules for ligands with new physical properties, chemotypes, and receptor subtype selectivities. Of 19 docking-prioritized molecules tested against the M2 subtype, 11 had substantial activity and 8 represented new chemotypes. Intriguingly, two were uncharged ligands with low micromolar to high nanomolar Ki values, an observation with few precedents among aminergic GPCRs. To exploit a single amino-acid substitution among the binding pockets between the M2 and M3 receptors, we selected molecules predicted by docking to bind to the M3 and but not the M2 receptor. Of 16 molecules tested, 8 bound to the M3 receptor. Whereas selectivity remained modest for most of these, one was a partial agonist at the M3 receptor without measurable M2 agonism. Consistent with this activity, this compound stimulated insulin release from a mouse β-cell line. These results support the ability of structure-based discovery to identify new ligands with unexplored chemotypes and physical properties, leading to new biologic functions, even in an area as heavily explored as muscarinic pharmacology.

Adenosine and its receptors as therapeutic targets: An overview

The main goal of the authors is to present an overview of adenosine and its receptors, which are G-protein coupled receptors. The four known adenosine receptor subtypes are discussed along with the therapeutic potential indicating that these receptors can serve as targets for various dreadful diseases.

Revisiting a receptor-based pharmacophore hypothesis for human A(2A) adenosine receptor antagonists

The application of both structure- and ligand-based design approaches represents to date one of the most useful strategies in the discovery of new drug candidates. In the present paper, we investigated how the application of docking-driven conformational analysis can improve the predictive ability of 3D-QSAR statistical models. With the use of the crystallographic structure in complex with the high affinity antagonist ZM 241385 (4-(2-[7-amino-2-(2-furyl)[1,2,4]-triazolo[2,3-a][1,3,5]triazin-5-ylamino]ethyl)phenol), we revisited a general pharmacophore hypothesis for the human A(2A) adenosine receptor of a set of 751 known antagonists, by applying an integrated ligand- and structure-based approach. Our novel pharmacophore hypothesis has been validated by using an external test set of 29 newly synthesized human adenosine receptor antagonists.

Dual targeting of adenosine A(2A) receptors and monoamine oxidase B by 4H-3,1-benzothiazin-4-ones

Blockade of A2A adenosine receptors (A2AARs) and inhibition of monoamine oxidase B (MAO-B) in the brain are considered attractive strategies for the treatment of neurodegenerative diseases such as Parkinson's disease (PD). In the present study, benzothiazinones, e.g., 2-(3-chlorophenoxy)-N-(4-oxo-4H-3,1-benzothiazin-2-yl)acetamide (13), were identified as a novel class of potent MAO-B inhibitors (IC50 human MAO-B: 1.63 nM). Benzothiazinones with large substituents in the 2-position, e.g., methoxycinnamoylamino, phenylbutyrylamino, or chlorobenzylpiperazinylbenzamido residues (14, 17, 27, and 28), showed high affinity and selectivity for A2AARs (Ki human A2AAR: 39.5-69.5 nM). By optimizing benzothiazinones for both targets, the first potent, dual-acting A2AAR/MAO-B inhibitors with a nonxanthine structure were developed. The best derivative was N-(4-oxo-4H-3,1-benzothiazin-2-yl)-4-phenylbutanamide (17, Ki human A2A, 39.5 nM; IC50 human MAO-B, 34.9 nM; selective versus other AR subtypes and MAO-A), which inhibited A2AAR-induced cAMP accumulation and showed competitive, reversible MAO-B inhibition. The new compounds may be useful tools for validating the A2AAR/MAO-B dual target approach in PD.

Optimized method of G-protein-coupled receptor homology modeling: its application to the discovery of novel CXCR7 ligands

Homology modeling of G-protein-coupled seven-transmembrane receptors (GPCRs) remains a challenge despite the increasing number of released GPCR crystal structures. This challenge can be attributed to the low sequence identity and structural diversity of the ligand-binding pocket of GPCRs. We have developed an optimized GPCR structure modeling method based on multiple GPCR crystal structures. This method was designed to be applicable to distantly related receptors of known structural templates. CXC chemokine receptor (CXCR7) is a potential drug target for cancer chemotherapy. Homology modeling, docking, and virtual screening for CXCR7 were carried out using our method. The predicted docking poses of the known antagonists were different from the crystal structure of human CXCR4 with the small-molecule antagonist IT1t. Furthermore, 21 novel CXCR7 ligands with IC50 values of 1.29-11.4 μM with various scaffolds were identified by structure-based virtual screening.

Structure-based approaches to ligands for G-protein-coupled adenosine and P2Y receptors, from small molecules to nanoconjugates

Adenosine receptor (ARs) and P2Y receptors (P2YRs) that respond to extracellular nucleosides/nucleotides are associated with new directions for therapeutics. The X-ray structures of the A2AAR complexes with agonists and antagonists are examined in relationship to the G-protein-coupled receptor (GPCR) superfamily and applied to drug discovery. Much of the data on AR ligand structure from early SAR studies now are explainable from the A2AAR X-ray crystallography. The ligand-receptor interactions in related GPCR complexes can be identified by means of modeling approaches, e.g., molecular docking. Thus, molecular recognition in binding and activation processes has been studied effectively using homology modeling and applied to ligand design. Virtual screening has yielded new nonnucleoside AR antagonists, and existing ligands have been improved with knowledge of the receptor interactions. New agonists are being explored for central nervous system and peripheral therapeutics based on in vivo activity, such as chronic neuropathic pain. Ligands for receptors more distantly related to the X-ray template, i.e., P2YRs, have been introduced and are mainly used as pharmacological tools for elucidating the physiological role of extracellular nucleotides. Other ligand tools for drug discovery include fluorescent probes, radioactive probes, multivalent probes, and functionalized nanoparticles.

Conformation guides molecular efficacy in docking screens of activated β-2 adrenergic G protein coupled receptor

A prospective, large library virtual screen against an activated β2-adrenergic receptor (β2AR) structure returned potent agonists to the exclusion of inverse-agonists, providing the first complement to the previous virtual screening campaigns against inverse-agonist-bound G protein coupled receptor (GPCR) structures, which predicted only inverse-agonists. In addition, two hits recapitulated the signaling profile of the co-crystal ligand with respect to the G protein and arrestin mediated signaling. This functional fidelity has important implications in drug design, as the ability to predict ligands with predefined signaling properties is highly desirable. However, the agonist-bound state provides an uncertain template for modeling the activated conformation of other GPCRs, as a dopamine D2 receptor (DRD2) activated model templated on the activated β2AR structure returned few hits of only marginal potency.

Structure-based discovery of antagonists of nuclear receptor LRH-1

Liver receptor homolog 1 (nuclear receptor LRH-1, NR5A2) is an essential regulator of gene transcription, critical for maintenance of cell pluripotency in early development and imperative for the proper functions of the liver, pancreas, and intestines during the adult life. Although physiological hormones of LRH-1 have not yet been identified, crystallographic and biochemical studies demonstrated that LRH-1 could bind regulatory ligands and suggested phosphatidylinositols as potential hormone candidates for this receptor. No synthetic antagonists of LRH-1 are known to date. Here, we identify the first small molecule antagonists of LRH-1 activity. Our search for LRH-1 modulators was empowered by screening of 5.2 million commercially available compounds via molecular docking followed by verification of the top-ranked molecules using in vitro direct binding and transcriptional assays. Experimental evaluation of the predicted ligands identified two compounds that inhibit the transcriptional activity of LRH-1 and diminish the expression of the receptor's target genes. Among the affected transcriptional targets are co-repressor SHP (small heterodimer partner) as well as cyclin E1 (CCNE1) and G0S2 genes that are known to regulate cell growth and proliferation. Treatments of human pancreatic (AsPC-1), colon (HT29), and breast adenocarcinoma cells T47D and MDA-MB-468 with the LRH-1 antagonists resulted in the receptor-mediated inhibition of cancer cell proliferation. Our data suggest that specific antagonists of LRH-1 could be used as specific molecular probes for elucidating the roles of the receptor in different types of malignancies.

Insight into the binding mode and the structural features of the pyrimidine derivatives as human A2A adenosine receptor antagonists

The interaction of 278 monocyclic and bicyclic pyrimidine derivatives with human A2A adenosine receptor (AR) was investigated by employing molecular dynamics, thermodynamic analysis and three-dimensional quantitative structure-activity relationship (3D-QSAR) approaches. The binding analysis reveals that the pyrimidine derivatives are anchored in TM2, 3, 5, 6 and 7 of A2A AR by the aromatic stacking and hydrogen bonding interactions. The key residues involving Phe168, Glu169, and Asn253 stabilize the monocyclic and bicyclic cores of inhibitors. The thermodynamic analysis by molecular mechanics/Poisson Boltzmann surface area (MM-PBSA) approach also confirms the reasonableness of the binding modes. In addition, the ligand-/receptor-based comparative molecular similarity indices analysis (CoMSIA) models of high statistical significance were generated and the resulting contour maps correlate well with the structural features of the antagonists essential for high A2A AR affinity. A minor/bulky group with negative charge at C2/C6 of pyrimidine ring respectively enhances the activity for all these pyrimidine derivatives. Particularly, the higher electron density of the ring in the bicyclic derivatives, the more potent the antagonists. The obatined results might be helpful in rational design of novel candidate of A2A adenosine receptor antagonist for treatment of Parkinson's disease.

Biophysical fragment screening of the β1-adrenergic receptor: identification of high affinity arylpiperazine leads using structure-based drug design

Biophysical fragment screening of a thermostabilized β1-adrenergic receptor (β1AR) using surface plasmon resonance (SPR) enabled the identification of moderate affinity, high ligand efficiency (LE) arylpiperazine hits 7 and 8. Subsequent hit to lead follow-up confirmed the activity of the chemotype, and a structure-based design approach using protein-ligand crystal structures of the β1AR resulted in the identification of several fragments that bound with higher affinity, including indole 19 and quinoline 20. In the first example of GPCR crystallography with ligands derived from fragment screening, structures of the stabilized β1AR complexed with 19 and 20 were determined at resolutions of 2.8 and 2.7 Å, respectively.

X-ray structural information of GPCRs in drug design: what are the limitations and where do we go?

INTRODUCTION

In 2007, the X-ray structural determination of non-rhodopsin G-Protein coupled receptors (GPCRs), considered the most extensively targeted protein class for marketed drugs, commenced. With the relatively rapid availability of additional structures, an assessment of the progression made is needed in addition to the assessment of the understandings gleaned, deployment successes and forthcoming prospects.

AREAS COVERED

The author reviews the approaches and tools that have made it possible to determine the three dimensional structures of GPCRs using X-ray crystallography. Furthermore, the author describes the methods suited for crystallization of membrane bound GPCR proteins including the lipidic cubic phase and various protein modification approaches. The author also provides highlights, from the literature, of the structures determined to date including targets solved, the nature of the content provided (such as selectivity, activating vs. inactivating determinants) and how these structural features relate to drug design strategies.

EXPERT OPINION

The GPCR X-ray structures that have been so far determined have yielded significant information. This has presented dramatic evidence concerning their ability to impact the discovery of compounds through their action as traditional, orthosteric modulators. It is, however, noted that more challenging design strategies, such as identifying biased agonists and the use of sites remote from the orthosteric site for allosteric modulation, are still in their infancy.

Identifying subset errors in multiple sequence alignments

Multiple sequence alignment (MSA) accuracy is important, but there is no widely accepted method of judging the accuracy that different alignment algorithms give. We present a simple approach to detecting two types of error, namely block shifts and the misplacement of residues within a gap. Given a MSA, subsets of very similar sequences are generated through the use of a redundancy filter, typically using a 70-90% sequence identity cut-off. Subsets thus produced are typically small and degenerate, and errors can be easily detected even by manual examination. The errors, albeit minor, are inevitably associated with gaps in the alignment, and so the procedure is particularly relevant to homology modelling of protein loop regions. The usefulness of the approach is illustrated in the context of the universal but little known [K/R]KLH motif that occurs in intracellular loop 1 of G protein coupled receptors (GPCR); other issues relevant to GPCR modelling are also discussed.

The second extracellular loop of GPCRs determines subtype-selectivity and controls efficacy as evidenced by loop exchange study at A2 adenosine receptors

The second extracellular loop (EL2) of G protein-coupled receptors (GPCRs), which represent important drug targets, may be involved in ligand recognition and receptor activation. We studied the closely related adenosine receptor (AR) subtypes A2A and A2B by exchanging the complete EL2 of the human A2BAR for the EL2 of the A2AAR. Furthermore, single amino acid residues (Asp148(45.27), Ser149(45.28), Thr151(45.30), Glu164(45.43), Ser165(45.44), and Val169(45.48)) in the EL2 of the A2BAR were exchanged for alanine. The single mutations did not lead to any major effects, except for the T151A mutant, at which NECA showed considerably increased efficacy. The loop exchange entailed significant effects: The A2A-selective agonist CGS21680, while being completely inactive at A2BARs, showed high affinity for the mutant A2B(EL2-A2A)AR, and was able to fully activate the receptor. Most strikingly, all agonists investigated (adenosine, NECA, BAY60-6583, CGS21680) showed strongly increased efficacies at the mutant A2B(EL2-A2A) as compared to the wt AR. Thus, the EL2 of the A2BAR appears to have multiple functions: besides its involvement in ligand binding and subtype selectivity it modulates agonist-bound receptor conformations thereby controlling signalling efficacy. This role of the EL2 is likely to extend to other members of the GPCR family, and the EL2 of GPCRs appears to be an attractive target structure for drugs.

Discovery of a novel selective kappa-opioid receptor agonist using crystal structure-based virtual screening

Kappa-opioid (KOP) receptor agonists exhibit analgesic effects without activating reward pathways. In the search for nonaddictive opioid therapeutics and novel chemical tools to study physiological functions regulated by the KOP receptor, we screened in silico its recently released inactive crystal structure. A selective novel KOP receptor agonist emerged as a notable result and is proposed as a new chemotype for the study of the KOP receptor in the etiology of drug addiction, depression, and/or pain.

A Strategy Combining Differential Low-Throughput Screening and Virtual Screening (DLS-VS) Accelerating the Discovery of new Modulators for the Orphan GPR34 Receptor

The DLS-VS strategy was developed as an integrated method for identifying chemical modulators for orphan GPCRs. It combines differential low-throughput screening (DLS) and virtual screening (VS). The two cascaded techniques offer complementary advantages and allow the experimental testing of a minimal number of compounds. First, DLS identifies modulators specific for the considered receptor among a set of receptors, through the screening of a small library with diverse chemical compounds. Then, an active molecular model of the receptor is built by homology to a validated template, and it is progressively refined by rotamers modification for key side-chains, by VS of the already screened library, and by iterative selection of the model generating the best enrichment. The refined active model is finally used for the VS of a large chemical library and the selection of a small set of compounds for experimental testing. Applied to the orphan receptor GPR34, the DLS-VS strategy combined the experimental screening of 20 000 compounds and the virtual screening of 1 250 000 compounds. It identified one agonist and eight inverse agonists, showing a high chemical diversity. We describe the method. The strategy can be applied to other GPCRs.

Probing GPCR structure: adenosine and P2Y nucleotide receptors

The adenosine receptors (ARs) provide an example of how to accurately predict ligand recognition, even prior to the availability of a crystallographic structure. Homology modeling has been used to gain structural insight, in conjunction with site-directed mutagenesis, and structure-activity relationships of small molecular ligands. Recent X-ray structures greatly improved the accuracy of knowledge of AR ligand recognition and furthermore characterized conformational changes induced by receptor activation. Now, homology modeling extends these structural insights to related GPCRs and suggests new ligand structures. This strategy is also being applied to the eight subtypes of P2Y receptors for extracellular nucleotides, which lack X-ray structures and are best modeled by homology to the CXCR4 (peptide) receptor. Neoceptors, as studied for three of the four AR subtypes, create a molecular complementarity between a mutant receptor and a chemically tailored agonist ligand to selectively enhance affinity, implying direct physical contact and thus validating docking hypotheses.

Molecular docking methodologies

Molecular docking represents an important technology for structure-based drug design. Docking is a computational technique aimed at the prediction of the most favorable ligand-target spatial configuration and an estimate of the corresponding complex free energy, although as stated at the beginning accurate scoring methods remain still elusive. In this chapter, the state of art of molecular docking methodologies and their applications in drug discovery is summarized.

Stabilised G protein-coupled receptors in structure-based drug design: a case study with adenosine A2A receptor

The first example of structure-based drug design with stabilised GPCRs has enabled the identification of a preclinical candidate for the treatment of Parkinson's disease.

Application of Monte Carlo-based receptor ensemble docking to virtual screening for GPCR ligands

Receptor ensemble docking (RED) is an effective strategy to account for receptor flexibility in the course of a docking-based virtual screening campaign. Such an approach can be applied when multiple crystal structures of a receptor have been solved, but it can also be applied when only a single crystal structure is available. In this case, alternative structures can be generated from the latter by computational means and subsequently applied to RED. Here, we illustrate how such conformers can be generated by subjecting a crystal structure to Monte Carlo conformational searches. Through a controlled virtual screening experiment, we then show the applicability of such a strategy to the identification of ligands of the β(2) adrenergic receptor, a G protein-coupled receptor activated by epinephrine. Requiring the availability of one crystal structure only, this strategy is applicable to all systems for which multiple experimentally elucidated structures are not available.

The GPCR Network: a large-scale collaboration to determine human GPCR structure and function

G protein-coupled receptors (GPCRs) are targeted by ∼30-40% of marketed drugs, and their key roles in normal physiology and in disease demonstrate that an understanding of their structure and function is valuable to researchers in both basic science and drug discovery. However, until recently, detailed structural information on this protein family was limited by challenges in X-ray crystallographic analysis of such membrane proteins. The GPCR Network was created in 2010 with the goal of structurally characterizing 15-25 representative human GPCRs within 5 years, based on an active outreach programme addressing an interdisciplinary community of scientists interested in GPCR structure, chemistry and biology. Here, we provide an overview of how this collaborative effort has enabled the structural determination and characterization of eight human GPCRs so far, and discuss some of the challenges that remain in gaining more detailed insights into structure-function relationships in this receptor superfamily.

Limits of ligand selectivity from docking to models: in silico screening for A(1) adenosine receptor antagonists

G protein-coupled receptors (GPCRs) are attractive targets for pharmaceutical research. With the recent determination of several GPCR X-ray structures, the applicability of structure-based computational methods for ligand identification, such as docking, has increased. Yet, as only about 1% of GPCRs have a known structure, receptor homology modeling remains necessary. In order to investigate the usability of homology models and the inherent selectivity of a particular model in relation to close homologs, we constructed multiple homology models for the A(1) adenosine receptor (A(1)AR) and docked ∼2.2 M lead-like compounds. High-ranking molecules were tested on the A(1)AR as well as the close homologs A(2A)AR and A(3)AR. While the screen yielded numerous potent and novel ligands (hit rate 21% and highest affinity of 400 nM), it delivered few selective compounds. Moreover, most compounds appeared in the top ranks of only one model. These findings have implications for future screens.

Structure-function of the G protein-coupled receptor superfamily

During the past few years, crystallography of G protein-coupled receptors (GPCRs) has experienced exponential growth, resulting in the determination of the structures of 16 distinct receptors-9 of them in 2012 alone. Including closely related subtype homology models, this coverage amounts to approximately 12% of the human GPCR superfamily. The adrenergic, rhodopsin, and adenosine receptor systems are also described by agonist-bound active-state structures, including a structure of the receptor-G protein complex for the β(2)-adrenergic receptor. Biochemical and biophysical techniques, such as nuclear magnetic resonance and hydrogen-deuterium exchange coupled with mass spectrometry, are providing complementary insights into ligand-dependent dynamic equilibrium between different functional states. Additional details revealed by high-resolution structures illustrate the receptors as allosteric machines that are controlled not only by ligands but also by ions, lipids, cholesterol, and water. This wealth of data is helping redefine our knowledge of how GPCRs recognize such a diverse array of ligands and how they transmit signals 30 angstroms across the cell membrane; it also is shedding light on a structural basis of GPCR allosteric modulation and biased signaling.

Structure-activity relationships and molecular modeling of 1,2,4-triazoles as adenosine receptor antagonists

The structure-activity relationship (SAR) for a novel class of 1,2,4-triazole antagonists of the human A(2A) adenosine receptor (hA(2A)AR) was explored. Thirty-three analogs of a ligand that was discovered in a structure-based virtual screen against the hA(2A)AR were tested in hA(1), A(2A), and A(3) radioligand binding assays and in functional assays for the A(2B)AR subtype. As a series of closely related analogs of the initial lead, 1, did not display improved binding affinity or selectivity, molecular docking was used to guide the selection of more distantly related molecules. This resulted in the discovery of 32, a hA(2A)AR antagonist (K(i) 200 nM) with high ligand efficiency. In the light of the SAR for the 1,2,4-triazole scaffold, we also investigated the binding mode of these compounds based on docking to several A(2A)AR crystal structures.

Emerging opportunities for allosteric modulation of G-protein coupled receptors

Their ubiquitous nature, wide cellular distribution and versatile molecular recognition and signalling help make G-protein binding receptors (GPCRs) the most important class of membrane proteins in clinical medicine, accounting for ∼40% of all current therapeutics. A large percentage of current drugs target the endogenous ligand binding (orthosteric) site, which are structurally and evolutionarily conserved, particularly among members of the same GPCR subfamily. With the recent advances in GPCR X-ray crystallography, new opportunities for developing novel subtype selective drugs have emerged. Given the increasing recognition that the extracellular surface conformation changes in response to ligand binding, it is likely that all GPCRs possess an allosteric site(s) capable of regulating GPCR signalling. Allosteric sites are less structurally conserved than their corresponding orthosteric site and thus provide new opportunities for the development of more selective drugs. Constitutive oligomerisation (dimerisation) identified in many of the GPCRs investigated, adds another dimension to the structural and functional complexity of GPCRs. In this review, we compare 60 crystal structures of nine GPCR subtypes (rhodopsin, ß₂-AR, ß₁-AR, A(2a)-AR, CXCR4, D₃R, H₁R, M₂R, M₃R) across four subfamilies of Class A GPCRs, and discuss mechanisms involved in receptor activation and potential allosteric binding sites across the highly variable extracellular surface of these GPCRs. This analysis has identified a new extracellular salt bridge (ESB-2) that might be exploited in the design of allosteric modulators.

Ligand-receptor interaction platforms and their applications for drug discovery

INTRODUCTION

The study of drug-target interactions is essential for the understanding of biological processes and for the efforts to develop new therapeutic molecules. Increased ligand-binding assays have coincided with the advances in reagents, detection and instrumentation technologies, the expansion in therapeutic targets of interest, and the increasingly recognized importance of biochemical aspects of drug-target interactions in determining the clinical performance of drug molecules. Nowadays, ligand-binding assays can determine every aspect of many drug-target interactions.

AREAS COVERED

Given that ligand-target interactions are very diverse, the author has decided to focus on the binding of small molecules to protein targets. This article first reviews the key biochemical aspects of drug-target interactions, and then discusses the detection principles of various ligand-binding techniques in the context of their primary applications for drug discovery and development.

EXPERT OPINION

Equilibrium-binding affinity should not be used as a solo indicator for the in vivo pharmacology of drugs. The clinical relevance of drug-binding kinetics demands high throughput kinetics early in drug discovery. The dependence of ligand binding and function on the conformation of targets necessitates solution-based and whole cell-based ligand-binding assays. The increasing need to examine ligand binding at the proteome level, driven by the clinical importance of the polypharmacology of ligands, has started to make the structure-based in silico binding screen an indispensable technique for drug discovery and development. Integration of different ligand-binding assays is important to improve the efficiency of the drug discovery and development process.

Analysis of structure-based virtual screening studies and characterization of identified active compounds

Structure-based virtual screening makes explicit or implicit use of 3D target structure information to detect novel active compounds. Results of nearly 300 currently available original applications have been analyzed to characterize the state-of-the-art in this field. Compound selection from docking calculations is much influenced by subjective criteria. Although submicromolar compounds are identified, the majority of docking hits are only weakly potent. However, only a small percentage of docking hits can be reproduced by ligand-based methods. When docking calculations identify potent hits, they often originate from specialized compound sources (e.g., pharmaceutical compound decks or target-focused libraries) and also display a notable bias towards kinase targets. Structure-based virtual screening is the dominant approach to computational hit identification. Docking calculations frequently identify active compounds. Limited accuracy of compound scoring and ranking currently presents a major caveat of the approach that is often compensated for by chemical intuition and knowledge.

Directory of useful decoys, enhanced (DUD-E): better ligands and decoys for better benchmarking

A key metric to assess molecular docking remains ligand enrichment against challenging decoys. Whereas the directory of useful decoys (DUD) has been widely used, clear areas for optimization have emerged. Here we describe an improved benchmarking set that includes more diverse targets such as GPCRs and ion channels, totaling 102 proteins with 22886 clustered ligands drawn from ChEMBL, each with 50 property-matched decoys drawn from ZINC. To ensure chemotype diversity, we cluster each target’s ligands by their Bemis–Murcko atomic frameworks. We add net charge to the matched physicochemical properties and include only the most dissimilar decoys, by topology, from the ligands. An online automated tool (http://decoys.docking.org) generates these improved matched decoys for user-supplied ligands. We test this data set by docking all 102 targets, using the results to improve the balance between ligand desolvation and electrostatics in DOCK 3.6. The complete DUD-E benchmarking set is freely available at http://dude.docking.org.

New insights for drug design from the X-ray crystallographic structures of G-protein-coupled receptors

Methodological advances in X-ray crystallography have made possible the recent solution of X-ray structures of pharmaceutically important G protein-coupled receptors (GPCRs), including receptors for biogenic amines, peptides, a nucleoside, and a sphingolipid. These high-resolution structures have greatly increased our understanding of ligand recognition and receptor activation. Conformational changes associated with activation common to several receptors entail outward movements of the intracellular side of transmembrane helix 6 (TM6) and movements of TM5 toward TM6. Movements associated with specific agonists or receptors have also been described [e.g., extracellular loop (EL) 3 in the A(2A) adenosine receptor]. The binding sites of different receptors partly overlap but differ significantly in ligand orientation, depth, and breadth of contact areas in TM regions and the involvement of the ELs. A current challenge is how to use this structural information for the rational design of novel potent and selective ligands. For example, new chemotypes were discovered as antagonists of various GPCRs by subjecting chemical libraries to in silico docking in the X-ray structures. The vast majority of GPCR structures and their ligand complexes are still unsolved, and no structures are known outside of family A GPCRs. Molecular modeling, informed by supporting information from site-directed mutagenesis and structure-activity relationships, has been validated as a useful tool to extend structural insights to related GPCRs and to analyze docking of other ligands in already crystallized GPCRs.