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

Mutation-Guided Unbiased Modeling of the Fat Sensor GPR119 for High-Yield Agonist Screening

Recent benchmark studies have demonstrated the difficulties in obtaining accurate predictions of ligand binding conformations to comparative models of G-protein-coupled receptors. We have developed a data-driven optimization protocol, which integrates mutational data and structural information from multiple X-ray receptor structures in combination with a fully flexible ligand docking protocol to determine the binding conformation of AR231453, a small-molecule agonist, in the GPR119 receptor. Resulting models converge to one conformation that explains the majority of data from mutation studies and is consistent with the structure-activity relationship for a large number of AR231453 analogs. Another key property of the refined models is their success in separating active ligands from decoys in a large-scale virtual screening. These results demonstrate that mutation-guided receptor modeling can provide predictions of practical value for describing receptor-ligand interactions and drug discovery.

Twenty years after ACEIs and ARBs: emerging treatment strategies for diabetic nephropathy

Diabetic nephropathy (DN) is a serious complication of both type 1 and type 2 diabetes mellitus. The disease is now the most common cause of end-stage kidney disease (ESKD) in developed countries, and both the incidence and prevalence of diabetes mellitus is increasing worldwide. Current treatments are directed at controlling hyperglycemia and hypertension, as well as blockade of the renin angiotensin system with angiotensin-converting enzyme inhibitors (ACEIs), and angiotensin receptor blockers. Despite these therapies, DN progresses to ESKD in many patients. As a result, much interest is focused on developing new therapies. It has been over two decades since ACEIs were shown to have beneficial effects in DN independent of their blood pressure-lowering actions. Since that time, our understanding of disease mechanisms in DN has evolved. In this review, we summarize major cell signaling pathways implicated in the pathogenesis of diabetic kidney disease, as well as emerging treatment strategies. The goal is to identify promising targets that might be translated into therapies for the treatment of patients with diabetic kidney disease.

Structural Determinants for the Binding of Morphinan Agonists to the μ-Opioid Receptor

Atomistic descriptions of the μ-opioid receptor (μOR) noncovalently binding with two of its prototypical morphinan agonists, morphine (MOP) and hydromorphone (HMP), are investigated using molecular dynamics (MD) simulations. Subtle differences between the binding modes and hydration properties of MOP and HMP emerge from the calculations. Alchemical free energy perturbation calculations show qualitative agreement with in vitro experiments performed in this work: indeed, the binding free energy difference between MOP and HMP computed by forward and backward alchemical transformation is 1.2±1.1 and 0.8±0.8 kcal/mol, respectively, to be compared with 0.4±0.3 kcal/mol from experiment. Comparison with an MD simulation of μOR covalently bound with the antagonist β-funaltrexamine hints to agonist-induced conformational changes associated with an early event of the receptor’s activation: a shift of the transmembrane helix 6 relative to the transmembrane helix 3 and a consequent loss of the key R165-T279 interhelical hydrogen bond. This finding is consistent with a previous proposal suggesting that the R165-T279 hydrogen bond between these two helices indicates an inactive receptor conformation.

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

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

The triplet puzzle theory indicates extensive formation of heteromers between opioid and chemokine receptor subtypes

Biochemical studies had previously demonstrated examples of heteromerization between opioid and chemokine receptors. Based on the triplet puzzle theory, it has been discovered that opioid receptors are structurally more closely related to chemokine receptors than to other class A G-protein-coupled receptors. Their similarity is established in terms of the number of triplet homologies Asn-Leu-Ala, Thr-Leu-Pro, and Tyr-Ala-Phe in the amino acid code of extensive numbers of members of these two receptor groups. Such widespread similarities probably mean that many opioid and chemokine receptor subtypes utilize some of these mutual triplets to form heteromers. The findings underline that heteromerization among these two receptor groups can represent a major general mechanism for significant interactions between opioid peptides and chemokines in pain and neuroinflammation within the neural-glial networks of the CNS including immune cells.

Regulation of neuronal communication by G protein-coupled receptors

Neuronal communication plays an essential role in the propagation of information in the brain and requires a precisely orchestrated connectivity between neurons. Synaptic transmission is the mechanism through which neurons communicate with each other. It is a strictly regulated process which involves membrane depolarization, the cellular exocytosis machinery, neurotransmitter release from synaptic vesicles into the synaptic cleft, and the interaction between ion channels, G protein-coupled receptors (GPCRs), and downstream effector molecules. The focus of this review is to explore the role of GPCRs and G protein-signaling in neurotransmission, to highlight the function of GPCRs, which are localized in both presynaptic and postsynaptic membrane terminals, in regulation of intrasynaptic and intersynaptic communication, and to discuss the involvement of astrocytic GPCRs in the regulation of neuronal communication.

Advancements in therapeutically targeting orphan GPCRs

G-protein coupled receptors (GPCRs) are popular biological targets for drug discovery and development. To date there are more than 140 orphan GPCRs, i.e., receptors whose endogenous ligands are unknown. Traditionally orphan GPCRs have been difficult to study and the development of therapeutic compounds targeting these receptors has been extremely slow although these GPCRs are considered important targets based on their distribution and behavioral phenotype as revealed by animals lacking the receptor. Recent advances in several methods used to study orphan receptors, including protein crystallography and homology modeling are likely to be useful in the identification of therapeutics targeting these receptors. In the past 13 years, over a dozen different Class A GPCRs have been crystallized; this trend is exciting, since homology modeling of GPCRs has previously been limited by the availability of solved structures. As the number of solved GPCR structures continues to grow so does the number of templates that can be used to generate increasingly accurate models of phylogenetically related orphan GPCRs. The availability of solved structures along with the advances in using multiple templates to build models (in combination with molecular dynamics simulations that reveal structural information not provided by crystallographic data and methods for modeling hard-to-predict flexible loop regions) have improved the quality of GPCR homology models. This, in turn, has improved the success rates of virtual ligand screens that use homology models to identify potential receptor binding compounds. Experimental testing of the predicted hits and validation using traditional GPCR pharmacological approaches can be used to drive ligand-based efforts to probe orphan receptor biology as well as to define the chemotypes and chemical scaffolds important for binding. As a result of these advances, orphan GPCRs are emerging from relative obscurity as a new class of drug targets.

From Recombinant Expression to Crystals: A Step-by-Step Guide to GPCR Crystallography

G protein-coupled receptors (GPCRs) are the primary targets of drugs prescribed for many human pathophysiological conditions such as hypertension, allergies, schizophrenia, asthma, and various types of cancer. High-resolution structure determination of GPCRs has been a key focus area in GPCR biology to understand the basic mechanism of their activation and signaling and to materialize the long-standing dream of structure-based drug design on these versatile receptors. There has been tremendous effort at this front in the past two decades and it has culminated into crystal structures of 27 different receptors so far. The recent progress in crystallization and structure determination of GPCRs has been driven by innovation and cutting-edge developments at every step involved in the process of crystallization. Here, we present a step-by-step description of various steps involved in GPCR crystallization starting from recombinant expression to obtaining diffracting crystals. We also discuss the next frontiers in GPCR biology that are likely to be a primary focus for crystallography efforts in the next decade or so.

Quenching resonance energy transfer (QRET): a single-label technique for inhibitor screening and interaction studies

The increased number of therapeutic targets has led to a growing need for screening methods enabling possible inhibitor compound selection. Information for new therapeutic targets has been found mostly from sequencing of the human genome but this knowledge cannot be directly converted into clinically relevant drug molecules. After target identification, the multistep drug development process takes many years and hundreds of millions of dollars are spent without certainty of the outcome. The first and the most critical step in the drug development process is hit selection. The optimal high throughput screening method should provide the highest possible number of true positive hits for further studies and lead discovery. The result should be achieved with low material consumption in a rapid and automated process. Radioactive label based methods are sensitive, but due to the problems arising from the radioactivity, luminescence-based methods have become increasingly popular in screening. In this review, the time-resolved luminescence based quenching resonance energy transfer (QRET) technique is discussed for primary screening.

Structure and function of serotonin G protein-coupled receptors

Serotonin receptors are prevalent throughout the nervous system and the periphery, and remain one of the most lucrative and promising drug discovery targets for disorders ranging from migraine headaches to neuropsychiatric disorders such as schizophrenia and depression. There are 14 distinct serotonin receptors, of which 13 are G protein-coupled receptors (GPCRs), which are targets for approximately 40% of the approved medicines. Recent crystallographic and biochemical evidence has provided a converging understanding of the basic structure and functional mechanics of GPCR activation. Currently, two GPCR crystal structures exist for the serotonin family, the 5-HT1B and 5-HT2B receptor, with the antimigraine and valvulopathic drug ergotamine bound. The first serotonin crystal structures not only provide the first evidence of serotonin receptor topography but also provide mechanistic explanations into functional selectivity or biased agonism. This review will detail the findings of these crystal structures from a molecular and mutagenesis perspective for driving rational drug design for novel therapeutics incorporating biased signaling.

Structure prediction of the second extracellular loop in G-protein-coupled receptors

G-protein-coupled receptors (GPCRs) play key roles in living organisms. Therefore, it is important to determine their functional structures. The second extracellular loop (ECL2) is a functionally important region of GPCRs, which poses significant challenge for computational structure prediction methods. In this work, we evaluated CABS, a well-established protein modeling tool for predicting ECL2 structure in 13 GPCRs. The ECL2s (with between 13 and 34 residues) are predicted in an environment of other extracellular loops being fully flexible and the transmembrane domain fixed in its x-ray conformation. The modeling procedure used theoretical predictions of ECL2 secondary structure and experimental constraints on disulfide bridges. Our approach yielded ensembles of low-energy conformers and the most populated conformers that contained models close to the available x-ray structures. The level of similarity between the predicted models and x-ray structures is comparable to that of other state-of-the-art computational methods. Our results extend other studies by including newly crystallized GPCRs.

Monitoring G protein-coupled receptor activation using the protein fragment complementation technique split TEV

G protein-coupled receptors (GPCRs) modulate cellular signaling, often in a ligand-specific manner. Cellular effects regulated include differentiation, proliferation, hormonal regulation, and neuronal activity. Further, they are involved in many disease-relevant processes, such as cancer and neurodevelopmental diseases, and represent the largest class of drug targets. Therefore, monitoring how GPCRs are regulated in their activity is crucial to understand their role in physiological processes and implications for drug development. Split TEV, a method based on TEV protease fragment complementation, can be used to sensitively assay GPCR activities in living cells. The activity of a given GPCR is monitored through its binding to β-arrestin. Split TEV reporters provide at minimum a two-step amplification process facilitating a flexible format and a robust readout. For the initial setup, a GPCR of interest and β-arrestin are fused to the N- and C-terminal fragments of the TEV protease, and occurred interactions are indicated by increased fluorescence or luminescence of TEV cleavage-dependent reporters. The experimental procedure takes 24-72 h to complete, depending on the cell type and complexity of the experimental setup applied.

Expanding the horizons of G protein-coupled receptor structure-based ligand discovery and optimization using homology models

We show the key role of structural homology models in GPCR structure-based lead discovery and optimization, highlighting methodological aspects, recent progress and future directions.

Computational modeling of membrane proteins

The determination of membrane protein (MP) structures has always trailed that of soluble proteins due to difficulties in their overexpression, reconstitution into membrane mimetics, and subsequent structure determination. The percentage of MP structures in the protein databank (PDB) has been at a constant 1-2% for the last decade. In contrast, over half of all drugs target MPs, only highlighting how little we understand about drug-specific effects in the human body. To reduce this gap, researchers have attempted to predict structural features of MPs even before the first structure was experimentally elucidated. In this review, we present current computational methods to predict MP structure, starting with secondary structure prediction, prediction of trans-membrane spans, and topology. Even though these methods generate reliable predictions, challenges such as predicting kinks or precise beginnings and ends of secondary structure elements are still waiting to be addressed. We describe recent developments in the prediction of 3D structures of both α-helical MPs as well as β-barrels using comparative modeling techniques, de novo methods, and molecular dynamics (MD) simulations. The increase of MP structures has (1) facilitated comparative modeling due to availability of more and better templates, and (2) improved the statistics for knowledge-based scoring functions. Moreover, de novo methods have benefited from the use of correlated mutations as restraints. Finally, we outline current advances that will likely shape the field in the forthcoming decade.

D1-like receptors distinguishing thieno-azecine regioisomers

Design of novel azecine derivatives with modulated dopaminergic receptor selectivity and affinity profiles.

Bioluminescent tools for the analysis of G-protein-coupled receptor and arrestin interactions

New protein-based bioluminescent probes for monitoring GPCR interaction with β-arrestin are presented.

On the modularity of the intrinsic flexibility of the µ opioid receptor: a computational study

The µ opioid receptor (µOR), the principal target to control pain, belongs to the G protein-coupled receptors (GPCRs) family, one of the most highlighted protein families due to their importance as therapeutic targets. The conformational flexibility of GPCRs is one of their essential characteristics as they take part in ligand recognition and subsequent activation or inactivation mechanisms. It is assessed that the intrinsic mechanical properties of the µOR, more specifically its particular flexibility behavior, would facilitate the accomplishment of specific biological functions, at least in their first steps, even in the absence of a ligand or any chemical species usually present in its biological environment. The study of the mechanical properties of the µOR would thus bring some indications regarding the highly efficient ability of the µOR to transduce cellular message. We therefore investigate the intrinsic flexibility of the µOR in its apo-form using all-atom Molecular Dynamics simulations at the sub-microsecond time scale. We particularly consider the µOR embedded in a simplified membrane model without specific ions, particular lipids, such as cholesterol moieties, or any other chemical species that could affect the flexibility of the µOR. Our analyses highlighted an important local effect due to the various bendability of the helices resulting in a diversity of shape and volume sizes adopted by the µOR binding site. Such property explains why the µOR can interact with ligands presenting highly diverse structural geometry. By investigating the topology of the µOR binding site, a conformational global effect is depicted: the correlation between the motional modes of the extra- and intracellular parts of µOR on one hand, along with a clear rigidity of the central µOR domain on the other hand. Our results show how the modularity of the µOR flexibility is related to its pre-ability to activate and to present a basal activity.

Stubborn contaminants: influence of detergents on the purity of the multidrug ABC transporter BmrA

Despite the growing interest in membrane proteins, their crystallization remains a major challenge. In the course of a crystallographic study on the multidrug ATP-binding cassette transporter BmrA, mass spectral analyses on samples purified with six selected detergents revealed unexpected protein contamination visible for the most part on overloaded SDS-PAGE. A major contamination from the outer membrane protein OmpF was detected in purifications with Foscholine 12 (FC12) but not with Lauryldimethylamine-N-oxide (LDAO) or any of the maltose-based detergents. Consequently, in the FC12 purified BmrA, OmpF easily crystallized over BmrA in a new space group, and whose structure is reported here. We therefore devised an optimized protocol to eliminate OmpF during the FC12 purification of BmrA. On the other hand, an additional band visible at ∼110 kDa was detected in all samples purified with the maltose-based detergents. It contained AcrB that crystallized over BmrA despite its trace amounts. Highly pure BmrA preparations could be obtained using either a ΔacrAB E. coli strain and n-dodecyl-β-D-maltopyranoside, or a classical E. coli strain and lauryl maltose neopentyl glycol for the overexpression and purification, respectively. Overall our results urge to incorporate a proteomics-based purity analysis into quality control checks prior to commencing crystallization assays of membrane proteins that are notoriously arduous to crystallize. Moreover, the strategies developed here to selectively eliminate obstinate contaminants should be applicable to the purification of other membrane proteins overexpressed in E. coli.

What can we learn from molecular dynamics simulations for GPCR drug design?

Recent years have seen a tremendous progress in the elucidation of experimental structural information for G-protein coupled receptors (GPCRs). Although for the vast majority of pharmaceutically relevant GPCRs structural information is still accessible only by homology models the steadily increasing amount of structural information fosters the application of structure-based drug design tools for this important class of drug targets. In this article we focus on the application of molecular dynamics (MD) simulations in GPCR drug discovery programs. Typical application scenarios of MD simulations and their scope and limitations will be described on the basis of two selected case studies, namely the binding of small molecule antagonists to the human CC chemokine receptor 3 (CCR3) and a detailed investigation of the interplay between receptor dynamics and solvation for the binding of small molecules to the human muscarinic acetylcholine receptor 3 (hM3R).

The influence of alignment-free sequence representations on the semi-supervised classification of class C G protein-coupled receptors: semi-supervised classification of class C GPCRs

G protein-coupled receptors (GPCRs) are integral cell membrane proteins of relevance for pharmacology. The tertiary structure of the transmembrane domain, a gate to the study of protein functionality, is unknown for almost all members of class C GPCRs, which are the target of the current study. As a result, their investigation must often rely on alignments of their amino acid sequences. Sequence alignment entails the risk of missing relevant information. Various approaches have attempted to circumvent this risk through alignment-free transformations of the sequences on the basis of different amino acid physicochemical properties. In this paper, we use several of these alignment-free methods, as well as a basic amino acid composition representation, to transform the available sequences. Novel semi-supervised statistical machine learning methods are then used to discriminate the different class C GPCRs types from the transformed data. This approach is relevant due to the existence of orphan proteins to which type labels should be assigned in a process of deorphanization or reverse pharmacology. The reported experiments show that the proposed techniques provide accurate classification even in settings of extreme class-label scarcity and that fair accuracy can be achieved even with very simple transformation strategies that ignore the sequence ordering.

Structural and functional insights into the juxtamembranous amino-terminal tail and extracellular loop regions of class B GPCRs

Class B guanine nucleotide-binding protein GPCRs share heptahelical topology and signalling via coupling with heterotrimeric G proteins typical of the entire superfamily of GPCRs. However, they also exhibit substantial structural differences from the more extensively studied class A GPCRs. Even their helical bundle region, most conserved across the superfamily, is predicted to differ from that of class A GPCRs. Much is now known about the conserved structure of the amino-terminal domain of class B GPCRs, coming from isolated NMR and crystal structures, but the orientation of that domain relative to the helical bundle is unknown, and even less is understood about the conformations of the juxtamembranous amino-terminal tail or of the extracellular loops linking the transmembrane segments. We now review what is known about the structure and function of these regions of class B GPCRs. This comes from indirect analysis of structure-function relationships elucidated by mutagenesis and/or ligand modification and from the more direct analysis of spatial approximation coming from photoaffinity labelling and cysteine trapping studies. Also reviewed are the limited studies of structure of some of these regions. No dominant theme was recognized for the structures or functional roles of distinct regions of these juxtamembranous portions of the class B GPCRs. Therefore, it is likely that a variety of molecular strategies can be engaged for docking of agonist ligands and for initiation of conformational changes in these receptors that would be expected to converge to a common molecular mechanism for activation of intracellular signalling cascades.

Mechanistic insights into allosteric structure-function relationships at the M1 muscarinic acetylcholine receptor

Benzylquinolone carboxylic acid (BQCA) is the first highly selective positive allosteric modulator (PAM) for the M1 muscarinic acetylcholine receptor (mAChR), but it possesses low affinity for the allosteric site on the receptor. More recent drug discovery efforts identified 3-((1S,2S)-2-hydroxycyclohexyl)-6-((6-(1-methyl-1H-pyrazol-4-yl)pyridin-3-yl)methyl)benzo[h]quinazolin-4(3H)-one (referred to herein as benzoquinazolinone 12) as a more potent M1 mAChR PAM with a structural ancestry originating from BQCA and related compounds. In the current study, we optimized the synthesis of and fully characterized the pharmacology of benzoquinazolinone 12, finding that its improved potency derived from a 50-fold increase in allosteric site affinity as compared with BQCA, while retaining a similar level of positive cooperativity with acetylcholine. We then utilized site-directed mutagenesis and molecular modeling to validate the allosteric binding pocket we previously described for BQCA as a shared site for benzoquinazolinone 12 and provide a molecular basis for its improved activity at the M1 mAChR. This includes a key role for hydrophobic and polar interactions with residues Tyr-179, in the second extracellular loop (ECL2) and Trp-400(7.35) in transmembrane domain (TM) 7. Collectively, this study highlights how the properties of affinity and cooperativity can be differentially modified on a common structural scaffold and identifies molecular features that can be exploited to tailor the development of M1 mAChR-targeting PAMs.

Sequence and conformational preferences at termini of α-helices in membrane proteins: role of the helix environment

α-Helices are amongst the most common secondary structural elements seen in membrane proteins and are packed in the form of helix bundles. These α-helices encounter varying external environments (hydrophobic, hydrophilic) that may influence the sequence preferences at their N and C-termini. The role of the external environment in stabilization of the helix termini in membrane proteins is still unknown. Here we analyze α-helices in a high-resolution dataset of integral α-helical membrane proteins and establish that their sequence and conformational preferences differ from those in globular proteins. We specifically examine these preferences at the N and C-termini in helices initiating/terminating inside the membrane core as well as in linkers connecting these transmembrane helices. We find that the sequence preferences and structural motifs at capping (Ncap and Ccap) and near-helical (N' and C') positions are influenced by a combination of features including the membrane environment and the innate helix initiation and termination property of residues forming structural motifs. We also find that a large number of helix termini which do not form any particular capping motif are stabilized by formation of hydrogen bonds and hydrophobic interactions contributed from the neighboring helices in the membrane protein. We further validate the sequence preferences obtained from our analysis with data from an ultradeep sequencing study that identifies evolutionarily conserved amino acids in the rat neurotensin receptor. The results from our analysis provide insights for the secondary structure prediction, modeling and design of membrane proteins.

Role of G-protein-coupled receptor-related genes in insecticide resistance of the mosquito, Culex quinquefasciatus

G-protein-coupled receptors regulate signal transduction pathways and play diverse and pivotal roles in the physiology of insects, however, the precise function of GPCRs in insecticide resistance remains unclear. Using quantitative RT-PCR and functional genomic methods, we, for the first time, explored the function of GPCRs and GPCR-related genes in insecticide resistance of mosquitoes, Culex quinquefasciatus. A comparison of the expression of 115 GPCR-related genes at a whole genome level between resistant and susceptible Culex mosquitoes identified one and three GPCR-related genes that were up-regulated in highly resistant Culex mosquito strains, HAmCq^G8 and MAmCq^G6, respectively. To characterize the function of these up-regulated GPCR-related genes in resistance, the up-regulated GPCR-related genes were knockdown in HAmCq^G8 and MAmCq^G6 using RNAi technique. Knockdown of these four GPCR-related genes not only decreased resistance of the mosquitoes to permethrin but also repressed the expression of four insecticide resistance-related P450 genes, suggesting the role of GPCR-related genes in resistance is involved in the regulation of resistance P450 gene expression. This results help in understanding of molecular regulation of resistance development in Cx. quinquefasciatus.

HDX-MS guided drug discovery: small molecules and biopharmaceuticals

Hydrogen/deuterium exchange coupled with mass spectrometry (HDX-MS or DXMS) has emerged as an important tool for the development of small molecule therapeutics and biopharmaceuticals. Central to these advances have been improvements to automated HDX-MS platforms and software that allow for the rapid acquisition and processing of experimental data. Correlating the HDX-MS profile of large numbers of ligands with their functional outputs has enabled the development of structure activity relationships (SAR) and delineation of ligand classes based on functional selectivity. HDX-MS has also been applied to address many of the unique challenges posed by the continued emergence of biopharmaceuticals. Here we review the latest applications of HDX-MS to drug discovery, recent advances in technology and software, and provide perspective on future outlook.

Structure-based drug design for G protein-coupled receptors

Our understanding of the structural biology of G protein-coupled receptors has undergone a transformation over the past 5 years. New protein-ligand complexes are described almost monthly in high profile journals. Appreciation of how small molecules and natural ligands bind to their receptors has the potential to impact enormously how medicinal chemists approach this major class of receptor targets. An outline of the key topics in this field and some recent examples of structure- and fragment-based drug design are described. A table is presented with example views of each G protein-coupled receptor for which there is a published X-ray structure, including interactions with small molecule antagonists, partial and full agonists. The possible implications of these new data for drug design are discussed.

Modelling three-dimensional protein structures for applications in drug design

A structural perspective of drug target and anti-target proteins, and their molecular interactions with biologically active molecules, largely advances many areas of drug discovery, including target validation, hit and lead finding and lead optimisation. In the absence of experimental 3D structures, protein structure prediction often offers a suitable alternative to facilitate structure-based studies. This review outlines recent methodical advances in homology modelling, with a focus on those techniques that necessitate consideration of ligand binding. In this context, model quality estimation deserves special attention because the accuracy and reliability of different structure prediction techniques vary considerably, and the quality of a model ultimately determines its usefulness for structure-based drug discovery. Examples of G-protein-coupled receptors (GPCRs) and ADMET-related proteins were selected to illustrate recent progress and current limitations of protein structure prediction. Basic guidelines for good modelling practice are also provided.

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.

Identification of G protein-coupled receptors in Schistosoma haematobium and S. mansoni by comparative genomics

BACKGROUND

Schistosomiasis is a parasitic disease affecting ~200 million people worldwide. Schistosoma haematobium and S. mansoni are two relatively closely related schistosomes (blood flukes), and the causative agents of urogenital and hepatointestinal schistosomiasis, respectively. The availability of genomic, transcriptomic and proteomic data sets for these two schistosomes now provides unprecedented opportunities to explore their biology, host interactions and schistosomiasis at the molecular level. A particularly important group of molecules involved in a range of biological and developmental processes in schistosomes and other parasites are the G protein-coupled receptors (GPCRs). Although GPCRs have been studied in schistosomes, there has been no detailed comparison of these receptors between closely related species. Here, using a genomic-bioinformatic approach, we identified and characterised key GPCRs in S. haematobium and S. mansoni (two closely related species of schistosome).

METHODS

Using a Hidden Markov Model (HMM) and Support Vector Machine (SVM)-based pipeline, we classified and sub-classified GPCRs of S. haematobium and S. mansoni, combined with phylogenetic and transcription analyses.

RESULTS

We identified and classified classes A, B, C and F as well as an unclassified group of GPCRs encoded in the genomes of S. haematobium and S. mansoni. In addition, we characterised ligand-specific subclasses (i.e. amine, peptide, opsin and orphan) within class A (rhodopsin-like).

CONCLUSIONS

Most GPCRs shared a high degree of similarity and conservation, except for members of a particular clade (designated SmGPR), which appear to have diverged between S. haematobium and S. mansoni and might explain, to some extent, some of the underlying biological differences between these two schistosomes. The present set of annotated GPCRs provides a basis for future functional genomic studies of cellular GPCR-mediated signal transduction and a resource for future drug discovery efforts in schistosomes.

Lgr4 promotes glioma cell proliferation through activation of Wnt signaling

The key signaling networks regulating glioma cell proliferation remain poorly defined. The leucine-rich repeat containing G-protein coupled receptor 4 (Lgr4) has been implicated in intestinal, gastric, and epidermal cell functions. We investigated whether Lgr4 functions in glioma cells and found that Lgr4 expression was significantly increased in glioma tissues. In addition, Lgr4 overexpression promoted while its knockdown using small interfering RNA oligos inhibited glioma cell proliferation. In addition, Wnt/β-catenin signaling was activated in cells overexpressing Lgr4. Therefore, our results revealed that Lgr4 activates Wnt/β-catenin signaling to regulate glioma cell proliferation.

Towards structural systems pharmacology to study complex diseases and personalized medicine

Genome-Wide Association Studies (GWAS), whole genome sequencing, and high-throughput omics techniques have generated vast amounts of genotypic and molecular phenotypic data. However, these data have not yet been fully explored to improve the effectiveness and efficiency of drug discovery, which continues along a one-drug-one-target-one-disease paradigm. As a partial consequence, both the cost to launch a new drug and the attrition rate are increasing. Systems pharmacology and pharmacogenomics are emerging to exploit the available data and potentially reverse this trend, but, as we argue here, more is needed. To understand the impact of genetic, epigenetic, and environmental factors on drug action, we must study the structural energetics and dynamics of molecular interactions in the context of the whole human genome and interactome. Such an approach requires an integrative modeling framework for drug action that leverages advances in data-driven statistical modeling and mechanism-based multiscale modeling and transforms heterogeneous data from GWAS, high-throughput sequencing, structural genomics, functional genomics, and chemical genomics into unified knowledge. This is not a small task, but, as reviewed here, progress is being made towards the final goal of personalized medicines for the treatment of complex diseases.

Modeling G protein-coupled receptors in complex with biased agonists

The biological response to the activation of G protein-coupled receptors (GPCRs) typically originates from the simultaneous modulation of various signaling pathways that lead to distinct biological consequences. Hence, 'biased agonists' (i.e., compounds that selectively activate one of the pathways while blocking the others) are highly sought-after molecules to provide fine-tuned pharmacological interventions. This review describes strategies that can be deployed to model the conformation of GPCRs in complex with ligands endowed with specific signaling profiles useful for the generation of hypotheses on the structural requirements for the activation of different signaling pathways or for rational computer-aided ligand discovery campaigns. In particular, it focuses on strategies potentially applicable to model the global or local conformational states of GPCRs stabilized by specific ligands.

An unbiased method to build benchmarking sets for ligand-based virtual screening and its application to GPCRs

Benchmarking data sets have become common in recent years for the purpose of virtual screening, though the main focus had been placed on the structure-based virtual screening (SBVS) approaches. Due to the lack of crystal structures, there is great need for unbiased benchmarking sets to evaluate various ligand-based virtual screening (LBVS) methods for important drug targets such as G protein-coupled receptors (GPCRs). To date these ready-to-apply data sets for LBVS are fairly limited, and the direct usage of benchmarking sets designed for SBVS could bring the biases to the evaluation of LBVS. Herein, we propose an unbiased method to build benchmarking sets for LBVS and validate it on a multitude of GPCRs targets. To be more specific, our methods can (1) ensure chemical diversity of ligands, (2) maintain the physicochemical similarity between ligands and decoys, (3) make the decoys dissimilar in chemical topology to all ligands to avoid false negatives, and (4) maximize spatial random distribution of ligands and decoys. We evaluated the quality of our Unbiased Ligand Set (ULS) and Unbiased Decoy Set (UDS) using three common LBVS approaches, with Leave-One-Out (LOO) Cross-Validation (CV) and a metric of average AUC of the ROC curves. Our method has greatly reduced the “artificial enrichment” and “analogue bias” of a published GPCRs benchmarking set, i.e., GPCR Ligand Library (GLL)/GPCR Decoy Database (GDD). In addition, we addressed an important issue about the ratio of decoys per ligand and found that for a range of 30 to 100 it does not affect the quality of the benchmarking set, so we kept the original ratio of 39 from the GLL/GDD.

Cell surface membrane proteins as personalized biomarkers: where we stand and where we are headed

Personalized medicine requires the development of a wide array of biomarker diagnostic assays, reflecting individual variations and thus allowing tailored therapeutic interventions. Membrane proteins comprise approximately 30% of total human proteins; they play a key role in various physiological functions and pathological conditions, although, currently, only a limited number of membrane proteins are applied as biomarkers. In many normal tissues, cell surface membrane proteins are not easily accessible for diagnostic sampling, and tumor-derived membrane preparations - while serving as potential tumor biomarkers - may not reflect physiological protein expression. In addition to post-translational modifications, which may include glycosylation, phosphorylation and lipid modifications, the trafficking of membrane proteins is also regulated. Moreover, a tight cellular quality control monitors membrane protein maturation, and continuous removal and reinsertion, involving special signaling systems, occurs in many cases. However, cell surface membrane proteins already serve as valuable prognostic and predicative biomarkers, for example, in hematological and immunological diseases, by the determination of the cluster of differentiation markers. In this review, we demonstrate the relevance of cell surface membrane biomarkers in various diseases and call attention to the potential application of red blood cell (erythrocyte) membrane proteins in this regard. Surprisingly, red blood cells express hundreds of membrane proteins, which seem to reflect a general genetic and regulatory background, and may serve as relatively stable and easily accessible personalized membrane biomarkers. Quantitative membrane protein detection in red blood cells by flow cytometry may bring a breakthrough in this regard.

Free energy landscape of G-protein coupled receptors, explored by accelerated molecular dynamics

G-protein coupled receptors (GPCRs) mediate cellular responses to various hormones and neurotransmitters and are important targets for treating a wide spectrum of diseases. They are known to adopt multiple conformational states (e.g., inactive, intermediate and active) during their modulation of various cell signaling pathways. Here, the free energy landscape of GPCRs is explored using accelerated molecular dynamics (aMD) simulations as demonstrated on the M2 muscarinic receptor, a key GPCR that regulates human heart rate and contractile forces of cardiomyocytes. Free energy profiles of important structural motifs that undergo conformational transitions upon GPCR activation and allosteric signaling are analyzed in detail, including the Arg(3.50)-Glu(6.30) ionic lock, the Trp(6.48) toggle switch and the hydrogen interactions between Tyr(5.58)-Tyr(7.53).

Label-free drug discovery

Current drug discovery is dominated by label-dependent molecular approaches, which screen drugs in the context of a predefined and target-based hypothesis in vitro. Given that target-based discovery has not transformed the industry, phenotypic screen that identifies drugs based on a specific phenotype of cells, tissues, or animals has gained renewed interest. However, owing to the intrinsic complexity in drug-target interactions, there is often a significant gap between the phenotype screened and the ultimate molecular mechanism of action sought. This paper presents a label-free strategy for early drug discovery. This strategy combines label-free cell phenotypic profiling with computational approaches, and holds promise to bridge the gap by offering a kinetic and holistic representation of the functional consequences of drugs in disease relevant cells that is amenable to mechanistic deconvolution.

Structure and function of LGR5: an enigmatic G-protein coupled receptor marking stem cells

G-protein coupled receptors (GPCRs) are an important class of membrane protein that transmit extracellular signals invoked by sensing molecules such as hormones and neurotransmitters. GPCR dysfunction is implicated in many diseases and hence these proteins are of great interest to academia and the pharmaceutical industry. Leucine-rich repeat-containing GPCRs contain a characteristic extracellular domain that is an important modulator of intracellular signaling. One member of this class is the leucine-rich repeat-containing G-protein-coupled receptor 5 (LGR5), a stem cell marker in intestinal crypts, and mammary glands. LGR5 modulates Wnt signaling in the presence of the ligand R-spondin (RSPO). The mechanism of activation of LGR5 by RSPO is not understood, nor is the intracellular signaling mechanism known. Recently reported structures of the extracellular domain of LGR5 bound to RSPO reveal a horseshoe-shaped architecture made up of consecutive leucine-rich repeats, with RSPO bound on the concave surface. This review discusses the discovery of LGR5 and the impact it is having on our understanding of stem cell and cancer biology of the colon. In addition, it covers functional relationships suggested by sequence homology and structural analyses, as well as some intriguing conundrums with respect to the involvement of LGR5 in Wnt signaling.

Overview of Recent Progress in Protein-Expression Technologies for Small-Molecule Screening

Production of novel soluble and membrane-localized protein targets for functional and affinity-based screening has often been limited by the inability of traditional protein-expression systems to generate recombinant proteins that have properties similar to those of their endogenous counterparts. Such targets have often been labeled as challenging. Although biological validation of these challenging targets for specific disease areas may be strong, discovery of small-molecule modulators can be greatly delayed or completely halted due to target-expression issues. In this article, the limitations of traditional protein-expression systems will be discussed along with new systems designed to overcome these challenges. Recent work in this field has focused on two major areas for both soluble and membrane targets: construct-design strategies to improve expression levels and new hosts that can carry out the posttranslational modifications necessary for proper target folding and function. Another area of active research has been on the reconstitution of solubilized membrane targets for both structural analysis and screening. Finally, the potential impact of these new systems on the output of small-molecule screening campaigns will be discussed.