GPCR structure, function, drug discovery and crystallography: report from Academia-Industry International Conference (UK Royal Society) Chicheley Hall, 1-2 September 2014

Beyond matrix stiffness: targeting force-induced cancer drug resistance

During tumor progression, mechanical abnormalities in the tumor microenvironment (TME) trigger signaling pathways in cells that activate cellular programs, resulting in tumor growth and drug resistance. In this review, we describe mechanisms of action for anti-cancer therapies and mechanotransduction programs that regulate cellular processes, including cell proliferation, apoptosis, survival and phenotype switching. We discuss how the therapeutic response is impacted by the three main mechanical TME abnormalities: high extracellular matrix (ECM) composition and stiffness; interstitial fluid pressure (IFP); and elevated mechanical forces. We also review drugs that normalize these abnormalities or block mechanosensors and mechanotransduction pathways. Finally, we discuss current challenges and perspectives for the development of new strategies targeting mechanically induced drug resistance in the clinic.

Development of enhanced conformational sampling methods to probe the activation landscape of GPCRs

G protein-coupled receptors (GPCRs) make up the largest superfamily of integral membrane proteins and play critical signal transduction roles in many physiological processes. Developments in molecular biology, biophysical, biochemical, pharmacological, and computational techniques aimed at these important therapeutic targets are beginning to provide unprecedented details on the structural as well as functional basis of their pleiotropic signaling mediated by G proteins, β arrestins, and other transducers. This pleiotropy presents a pharmacological challenge as the same ligand-receptor interaction can cause a therapeutic effect as well as an undesirable on-target side-effect through different downstream pathways. GPCRs don't function as simple binary on-off switches but as finely tuned shape-shifting machines described by conformational ensembles, where unique subsets of conformations may be responsible for specific signaling cascades. X-ray crystallography and more recently cryo-electron microscopy are providing snapshots of some of these functionally-important receptor conformations bound to ligands and/or transducers, which are being utilized by computational methods to describe the dynamic conformational energy landscape of GPCRs. In this chapter, we review the progress in computational conformational sampling methods based on molecular dynamics and discrete sampling approaches that have been successful in complementing biophysical and biochemical studies on these receptors in terms of their activation mechanisms, allosteric effects, actions of biased ligands, and effects of pathological mutations. Some of the sampled simulation time scales are beginning to approach receptor activation time scales. The list of conformational sampling methods and example uses discussed is not exhaustive but includes representative examples that have pushed the limits of classical molecular dynamics and discrete sampling methods to describe the activation energy landscape of GPCRs.

pdCSM-GPCR: predicting potent GPCR ligands with graph-based signatures

MOTIVATION

G protein-coupled receptors (GPCRs) can selectively bind to many types of ligands, ranging from light-sensitive compounds, ions, hormones, pheromones and neurotransmitters, modulating cell physiology. Considering their role in many essential cellular processes, they are one of the most targeted protein families, with over a third of all approved drugs modulating GPCR signalling. Despite this, the large diversity of receptors and their multipass transmembrane architectures make the identification and development of novel specific, and safe GPCR ligands a challenge. While computational approaches have the potential to assist GPCR drug development, they have presented limited performance and generalization capabilities. Here, we explored the use of graph-based signatures to develop pdCSM-GPCR, a method capable of rapidly and accurately screening potential GPCR ligands.

RESULTS

Bioactivity data (IC50, EC50, Ki and Kd) for individual GPCRs were curated. After curation, we used the data for developing predictive models for 36 major GPCR targets, across 4 classes (A, B, C and F). Our models compose the most comprehensive computational resource for GPCR bioactivity prediction to date. Across stratified 10-fold cross-validation and blind tests, our approach achieved Pearson's correlations of up to 0.89, significantly outperforming previous methods. Interpreting our results, we identified common important features of potent GPCRs ligands, which tend to have bicyclic rings, leading to higher levels of aromaticity. We believe pdCSM-GPCR will be an invaluable tool to assist screening efforts, enriching compound libraries and ranking candidates for further experimental validation.

AVAILABILITY AND IMPLEMENTATION

pdCSM-GPCR predictive models and datasets used have been made available via a freely accessible and easy-to-use web server at http://biosig.unimelb.edu.au/pdcsm_gpcr/.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics Advances online.

Olfactory receptor Olfr78 (prostate-specific G protein-coupled receptor PSGR) expression in arterioles supplying skeletal and cardiac muscles and in arterioles feeding some murine organs

The olfactory receptor Olfr78 (prostate-specific G protein-coupled receptor PSGR) is a member of the G protein-coupled receptor family mediating olfactory chemosensation, but it is additionally expressed in other tissues. Olfr78 expressed in kidney participates in blood pressure regulation, and in prostate it plays a role in the development of cancer. We here screened many organs/tissues of transgenic mice co-expressing β-galactosidase with Olfr78. X-gal-positive cells were detectable in smooth muscle cells of numerous arterioles of striated muscles (heart ventricles and skeletal muscles of various embryological origin). In addition, in most organs where we found expression of Olfr78 mRNA, X-gal staining was restricted to smooth muscle cells of small blood vessels. The dominant expression of Olfr78 in arteriolar smooth muscle cells supports the concept of an important role in blood pressure regulation and suggests a participation in the fine tuning of blood supply especially of striated muscles. This should be considered when targeting Olfr78 in other contexts such as prostate cancer.

Analyzing GPCR-Ligand Interactions with the Fragment Molecular Orbital (FMO) Method

G-protein-coupled receptors (GPCRs) have enormous physiological and biomedical importance, and therefore it is not surprising that they are the targets of many prescribed drugs. Further progress in GPCR drug discovery is highly dependent on the availability of protein structural information. However, the ability of X-ray crystallography to guide the drug discovery process for GPCR targets is limited by the availability of accurate tools to explore receptor-ligand interactions. Visual inspection and molecular mechanics approaches cannot explain the full complexity of molecular interactions. Quantum mechanics (QM) approaches are often too computationally expensive to be of practical use in time-sensitive situations, but the fragment molecular orbital (FMO) method offers an excellent solution that combines accuracy, speed, and the ability to reveal key interactions that would otherwise be hard to detect. Integration of GPCR crystallography or homology modelling with FMO reveals atomistic details of the individual contributions of each residue and water molecule toward ligand binding, including an analysis of their chemical nature. Such information is essential for an efficient structure-based drug design (SBDD) process. In this chapter, we describe how to use FMO in the characterization of GPCR-ligand interactions.

G-Protein coupled receptors: structure and function in drug discovery

The G-protein coupled receptors (GPCRs) superfamily comprise similar proteins arranged into families or classes thus making it one of the largest in the mammalian genome. GPCRs take part in many vital physiological functions making them targets for numerous novel drugs. GPCRs share some distinctive features, such as the seven transmembrane domains, they also differ in the number of conserved residues in their transmembrane domain. Here we provide an introductory and accessible review detailing the computational advances in GPCR pharmacology and drug discovery. An overview is provided on family A-C GPCRs; their structural differences, GPCR signalling, allosteric binding and cooperativity. The dielectric constant (relative permittivity) of proteins is also discussed in the context of site-specific environmental effects.

FLRTing Neurons in Cortical Migration During Cerebral Cortex Development

During development, two coordinated events shape the morphology of the mammalian cerebral cortex, leading to the cortex's columnar and layered structure: the proliferation of neuronal progenitors and cortical migration. Pyramidal neurons originating from germinal zones migrate along radial glial fibers to their final position in the cortical plate by both radial migration and tangential dispersion. These processes rely on the delicate balance of intercellular adhesive and repulsive signaling that takes place between neurons interacting with different substrates and guidance cues. Here, we focus on the function of the cell adhesion molecules fibronectin leucine-rich repeat transmembrane proteins (FLRTs) in regulating both the radial migration of neurons, as well as their tangential spread, and the impact these processes have on cortex morphogenesis. In combining structural and functional analysis, recent studies have begun to reveal how FLRT-mediated responses are precisely tuned - from forming different protein complexes to modulate either cell adhesion or repulsion in neurons. These approaches provide a deeper understanding of the context-dependent interactions of FLRTs with multiple receptors involved in axon guidance and synapse formation that contribute to finely regulated neuronal migration.

A novel phosphorylation site on orexin receptor 1 regulating orexinA-induced GRK2-biased signaling

Drug discovery efforts targeting G protein-coupled receptors (GPCRs) have succeeded in developing multiple medications for treating various human diseases including cancer, metabolic disorders, and inflammatory disorders. These medications are broadly classified as either agonists or antagonists that respectively promote or inhibit receptor activation by endogenous stimuli. However, there has been a growing appreciation that GPCR biased signaling between G protein- and β-arrestin-dependent signaling in particular is a promising method for improving drug efficacy and therapy. Orexin receptor 1 (OX1R), a member of the GPCRs, is an important drug target in the central nervous system. In this study, we identified a novel regulatory phosphorylation site (Ser-262) on OX1R that abolished its capability to interact with GRK2, but did not affect its interaction with G proteins, GRK5, or β-arrestin1/2 activation, indicating that Ser-262 is a key amino acid for OX1R internalization that contributes to induction of GRK2-dependent biased signaling via orexin A. Our findings could potentially lead to the development of new drug targets for the prevention and treatment of insomnia, narcolepsy, and substance abuse, with fewer side effects than existing therapies.

Yohimbine as a Starting Point to Access Diverse Natural Product-Like Agents with Re-programmed Activities against Cancer-Relevant GPCR Targets

G protein-coupled receptors (GPCRs) constitute the largest protein superfamily in the human genome. GPCRs play key roles in mediating a wide variety of physiological events including proliferation and cancer metastasis. Given the major roles that GPCRs play in mediating cancer growth, they present promising targets for small molecule therapeutics. One of the principal goals of our lab is to identify complex natural products (NPs) suitable for ring distortion, or the dramatic altering of the inherently complex architectures of NPs, to rapidly generate an array of compounds with diverse molecular skeletal systems. The overarching goal of our ring distortion approach is to re-program the biological activity of select natural products and identify new compounds of importance to the treatment of disease, such as cancer. Described herein are the results from biological screens of diverse small molecules derived from the indole alkaloid yohimbine against a panel of GPCRs involved in various diseases. Several analogues displayed highly differential antagonistic activities across the GPCRs tested. We highlight the re-programmed profile of one analogue, Y7g, which exhibited selective antagonistic activities against AVPR2 (IC₅₀ = 459 nM) and OXTR (IC₅₀ = 1.16 µM). The activity profile of Y7g could correlate its HIF-dependent anti-cancer activity to its GPCR antagonism since these receptors are known to be upregulated in hypoxic cellular environments. Our findings demonstrate that the ring distortion of yohimbine can lead to the identification of new compounds capable of interacting with distinct cancer-relevant targets.

Understanding G Protein Selectivity of Muscarinic Acetylcholine Receptors Using Computational Methods

The neurotransmitter molecule acetylcholine is capable of activating five muscarinic acetylcholine receptors, M1 through M5, which belong to the superfamily of G-protein-coupled receptors (GPCRs). These five receptors share high sequence and structure homology; however, the M1, M3, and M5 receptor subtypes signal preferentially through the Gαq/11 subset of G proteins, whereas the M2 and M4 receptor subtypes signal through the Gαi/o subset of G proteins, resulting in very different intracellular signaling cascades and physiological effects. The structural basis for this innate ability of the M1/M3/M5 set of receptors and the highly homologous M2/M4 set of receptors to couple to different G proteins is poorly understood. In this study, we used molecular dynamics (MD) simulations coupled with thermodynamic analyses of M1 and M2 receptors coupled to both Gαi and Gαq to understand the structural basis of the M1 receptor’s preference for the Gαq protein and the M2 receptor’s preference for the Gαi protein. The MD studies showed that the M1 and M2 receptors can couple to both Gα proteins such that the M1 receptor engages with the two Gα proteins in slightly different orientations and the M2 receptor engages with the two Gα proteins in the same orientation. Thermodynamic studies of the free energy of binding of the receptors to the Gα proteins showed that the M1 and M2 receptors bind more strongly to their cognate Gα proteins compared to their non-cognate ones, which is in line with previous experimental studies on the M3 receptor. A detailed analysis of receptor–G protein interactions showed some cognate-complex-specific interactions for the M2:Gαi complex; however, G protein selectivity determinants are spread over a large overlapping subset of residues. Conserved interaction between transmembrane helices 5 and 6 far away from the G-protein-binding receptor interface was found only in the two cognate complexes and not in the non-cognate complexes. An analysis of residues implicated previously in G protein selectivity, in light of the cognate and non-cognate structures, shaded a more nuanced role of those residues in affecting G protein selectivity. The simulation of both cognate and non-cognate receptor–G protein complexes fills a structural gap due to difficulties in determining non-cognate complex structures and provides an enhanced framework to probe the mechanisms of G protein selectivity exhibited by most GPCRs.

State of the art of Smo antagonists for cancer therapy: advances in the target receptor and new ligand structures

Since the Hedgehog signaling pathway has been associated with cancer, it has emerged as a therapeutic target for cancer therapy. The main target among the key Hedgehog proteins is the GPCR-like Smo receptor. Therefore, some Smo antagonists that have entered clinical trials, including the US FDA-approved drugs vismodegib and sonidegib, to treat basal cell carcinoma and medulloblastoma. However, early resistance of these drugs has spawned the need to understand the molecular bases of this phenomena. We therefore reviewed details about Smo receptor structures and the best Smo antagonist chemical structures. In addition, we discussed strategies that should be considered to develop new, safer generations of Smo antagonists that avoid current clinical limitations.

The Role of G Protein-coupled Receptor Kinases in Cancer

G protein-coupled receptors (GPCRs) are the largest family of plasma membrane receptors. Emerging evidence demonstrates that signaling through GPCRs affects numerous aspects of cancer biology such as vascular remolding, invasion, and migration. Therefore, development of GPCR-targeted drugs could provide a new therapeutic strategy to treating a variety of cancers. G protein-coupled receptor kinases (GRKs) modulate GPCR signaling by interacting with the ligand-activated GPCR and phosphorylating its intracellular domain. This phosphorylation initiates receptor desensitization and internalization, which inhibits downstream signaling pathways related to cancer progression. GRKs can also regulate non-GPCR substrates, resulting in the modulation of a different set of pathophysiological pathways. In this review, we will discuss the role of GRKs in modulating cell signaling and cancer progression, as well as the therapeutic potential of targeting GRKs.

Computational Methods Used in Hit-to-Lead and Lead Optimization Stages of Structure-Based Drug Discovery

GPCR modeling approaches are widely used in the hit-to-lead (H2L) and lead optimization (LO) stages of drug discovery. The aims of these modeling approaches are to predict the 3D structures of the receptor-ligand complexes, to explore the key interactions between the receptor and the ligand and to utilize these insights in the design of new molecules with improved binding, selectivity or other pharmacological properties. In this book chapter, we present a brief survey of key computational approaches integrated with hierarchical GPCR modeling protocol (HGMP) used in hit-to-lead (H2L) and in lead optimization (LO) stages of structure-based drug discovery (SBDD). We outline the differences in modeling strategies used in H2L and LO of SBDD and illustrate how these tools have been applied in three drug discovery projects.

Exploring GPCR-Ligand Interactions with the Fragment Molecular Orbital (FMO) Method

The understanding of binding interactions between any protein and a small molecule plays a key role in the rationalization of affinity and selectivity. It is essential for an efficient structure-based drug design (SBDD) process. FMO enables ab initio approaches to be applied to systems that conventional quantum-mechanical (QM) methods would find challenging. The key advantage of the Fragment Molecular Orbital Method (FMO) is that it can reveal atomistic details about the individual contributions and chemical nature of each residue and water molecule toward ligand binding which would otherwise be difficult to detect without using QM methods. In this chapter, we demonstrate the typical use of FMO to analyze 19 crystal structures of β1 and β2 adrenergic receptors with their corresponding agonists and antagonists.

Molecular modeling study on resistance of WT/D473H SMO to antagonists LDE-225 and LEQ-506

The smoothened (SMO) receptor, an essential signal transducer in the Hedgehog pathway, was targeted with antagonists to suppress the tumor. It is interesting that SMO D473H mutation confers resistance on inhibitor LDE-225 rather than LEQ-506. In this paper, the binding modes of them against the wild type and mutant SMO receptors were identified to gain insights into the resistant and non-resistant factors, based on a comprehensive protocol involving molecular docking, molecular dynamic simulations, free energy calculation and decomposition. A comparison of resistant LDE-225 and non-resistant LEQ-506 indicates that the volume of the binding cavity decreases seriously in the mutant complex with resistant LDE-225. In addition, the D473H mutation disrupts the hydrogen bond network with residues R400 and Q477, which results in the TM6 conformation inward. Owing to the absence of the hydrogen bond, residues R400 and Q477 make weak contributions to LDE-225. However, the D473H mutation along with TM6 conformational change has no effect on non-resistant LEQ-506. Finally, the resistance ascribes to adverse interaction between the greater polarity of mutant residue H473 and the nonpolar phenmethyl of LDE-225. The elaborate insights into structural and energetic mechanism of drug resistance provide an effective strategy to design rationally non-resistant antagonists.

Using the fragment molecular orbital method to investigate agonist-orexin-2 receptor interactions

The understanding of binding interactions between any protein and a small molecule plays a key role in the rationalization of affinity and selectivity and is essential for an efficient structure-based drug discovery (SBDD) process. Clearly, to begin SBDD, a structure is needed, and although there has been fantastic progress in solving G-protein-coupled receptor (GPCR) crystal structures, the process remains quite slow and is not currently feasible for every GPCR or GPCR-ligand complex. This situation significantly limits the ability of X-ray crystallography to impact the drug discovery process for GPCR targets in 'real-time' and hence there is still a need for other practical and cost-efficient alternatives. We present here an approach that integrates our previously described hierarchical GPCR modelling protocol (HGMP) and the fragment molecular orbital (FMO) quantum mechanics (QM) method to explore the interactions and selectivity of the human orexin-2 receptor (OX2R) and its recently discovered nonpeptidic agonists. HGMP generates a 3D model of GPCR structures and its complexes with small molecules by applying a set of computational methods. FMO allowsab initioapproaches to be applied to systems that conventional QM methods would find challenging. The key advantage of FMO is that it can reveal information on the individual contribution and chemical nature of each residue and water molecule to the ligand binding that normally would be difficult to detect without QM. We illustrate how the combination of both techniques provides a practical and efficient approach that can be used to analyse the existing structure-function relationships (SAR) and to drive forward SBDD in a real-world example for which there is no crystal structure of the complex available.

Application of an Integrated GPCR SAR-Modeling Platform To Explain the Activation Selectivity of Human 5-HT2C over 5-HT2B

Agonism of the 5-HT2C serotonin receptor has been associated with the treatment of a number of diseases including obesity, psychiatric disorders, sexual health, and urology. However, the development of effective 5-HT2C agonists has been hampered by the difficulty in obtaining selectivity over the closely related 5-HT2B receptor, agonism of which is associated with irreversible cardiac valvulopathy. Understanding how to design selective agonists requires exploration of the structural features governing the functional uniqueness of the target receptor relative to related off targets. X-ray crystallography, the major experimental source of structural information, is a slow and challenging process for integral membrane proteins, and so is currently not feasible for every GPCR or GPCR-ligand complex. Therefore, the integration of existing ligand SAR data with GPCR modeling can be a practical alternative to provide this essential structural insight. To demonstrate this, we integrated SAR data from 39 azepine series 5-HT2C agonists, comprising both selective and unselective examples, with our hierarchical GPCR modeling protocol (HGMP). Through this work we have been able to demonstrate how relatively small differences in the amino acid sequences of GPCRs can lead to significant differences in secondary structure and function, as supported by experimental data. In particular, this study suggests that conformational differences in the tilt of TM7 between 5-HT2B and 5-HT2C, which result from differences in interhelical interactions, may be the major source of selectivity in G-protein activation between these two receptors. Our approach also demonstrates how the use of GPCR models in conjunction with SAR data can be used to explain activity cliffs.

Application of advanced X-ray methods in life sciences

BACKGROUND

Synchrotron radiation (SR) sources provide diverse X-ray methods for the investigation of structure-function relationships in biological macromolecules.

SCOPE OF REVIEW

Recent developments in SR sources and in the X-ray tools they offer for life sciences are reviewed. Specifically, advances in macromolecular crystallography, small angle X-ray solution scattering, X-ray absorption and fluorescence spectroscopy, and imaging are discussed with examples.

MAJOR CONCLUSIONS

SR sources offer a range of X-ray techniques that can be used in a complementary fashion in studies of biological systems at a wide range of resolutions from atomic to cellular scale. Emerging applications of X-ray techniques include the characterization of disordered proteins, noncrystalline and nonequilibrium systems, elemental imaging of tissues, cells and organs, and detection of time-resolved changes in molecular structures.

GENERAL SIGNIFICANCE

X-ray techniques are in the center of hybrid approaches that are used to gain insight into complex problems relating to biomolecular mechanisms, disease and possible therapeutic solutions. This article is part of a Special Issue entitled "Science for Life". Guest Editors: Dr. Austen Angell, Dr. Salvatore Magazù and Dr. Federica Migliardo.

Applications of the BLEND Software to Crystallographic Data from Membrane Proteins

X-ray diffraction from crystals of membrane proteins very often yields incomplete datasets due to, among other things, severe radiation damage. Multiple crystals are thus required to form complete datasets, provided the crystals themselves are isomorphous. Selection and combination of data from multiple crystals is a difficult and tedious task that can be facilitated by purpose-built software. BLEND, in the CCP4 suite of programs for macromolecular crystallography (MX), has been created exactly for this reason. In this chapter the program is described and its workings illustrated by means of data from two membrane proteins.

Structure-Based Sequence Alignment of the Transmembrane Domains of All Human GPCRs: Phylogenetic, Structural and Functional Implications

The understanding of G-protein coupled receptors (GPCRs) is undergoing a revolution due to increased information about their signaling and the experimental determination of structures for more than 25 receptors. The availability of at least one receptor structure for each of the GPCR classes, well separated in sequence space, enables an integrated superfamily-wide analysis to identify signatures involving the role of conserved residues, conserved contacts, and downstream signaling in the context of receptor structures. In this study, we align the transmembrane (TM) domains of all experimental GPCR structures to maximize the conserved inter-helical contacts. The resulting superfamily-wide GpcR Sequence-Structure (GRoSS) alignment of the TM domains for all human GPCR sequences is sufficient to generate a phylogenetic tree that correctly distinguishes all different GPCR classes, suggesting that the class-level differences in the GPCR superfamily are encoded at least partly in the TM domains. The inter-helical contacts conserved across all GPCR classes describe the evolutionarily conserved GPCR structural fold. The corresponding structural alignment of the inactive and active conformations, available for a few GPCRs, identifies activation hot-spot residues in the TM domains that get rewired upon activation. Many GPCR mutations, known to alter receptor signaling and cause disease, are located at these conserved contact and activation hot-spot residue positions. The GRoSS alignment places the chemosensory receptor subfamilies for bitter taste (TAS2R) and pheromones (Vomeronasal, VN1R) in the rhodopsin family, known to contain the chemosensory olfactory receptor subfamily. The GRoSS alignment also enables the quantification of the structural variability in the TM regions of experimental structures, useful for homology modeling and structure prediction of receptors. Furthermore, this alignment identifies structurally and functionally important residues in all human GPCRs. These residues can be used to make testable hypotheses about the structural basis of receptor function and about the molecular basis of disease-associated single nucleotide polymorphisms.

G-protein coupled receptors (GPCRs) are a large superfamily of integral membrane proteins that share a characteristic 7 transmembrane helix fold. They detect various molecules outside of the cell and signal their presence to the inside of the cell. At least half of the 800 human GPCRs are potential drug targets, so understanding their structure and function is critical. Experimental structures are now available for at least one receptor from each GPCR class. The structure of the 7 helix fold is highly conserved even for receptors with very low sequence similarity. We analyze the available experimental structures and compare the common inter-helical contacts. Our analysis leads to a unified sequence-structure alignment of the GPCR superfamily that can then be used as the starting point for structure prediction of all other GPCRs. A key result of our analysis is a list of conserved contact residues and activation “hot-spots” residues that are critical for GPCR folding and function. We propose that mutations and natural variants of amino acids at these locations in the GPCRs can dramatically influence their activation state and alter intracellular signaling. This provides hypotheses for the molecular mechanisms underlying disease causing mutants for any GPCR.

Beyond Membrane Protein Structure: Drug Discovery, Dynamics and Difficulties

Most of the previous content of this book has focused on obtaining the structures of membrane proteins. In this chapter we explore how those structures can be further used in two key ways. The first is their use in structure based drug design (SBDD) and the second is how they can be used to extend our understanding of their functional activity via the use of molecular dynamics. Both aspects now heavily rely on computations. This area is vast, and alas, too large to consider in depth in a single book chapter. Thus where appropriate we have referred the reader to recent reviews for deeper assessment of the field. We discuss progress via the use of examples from two main drug target areas; G-protein coupled receptors (GPCRs) and ion channels. We end with a discussion of some of the main challenges in the area.

The Fragment Molecular Orbital Method Reveals New Insight into the Chemical Nature of GPCR–Ligand Interactions

Our interpretation of ligand-protein interactions is often informed by high-resolution structures, which represent the cornerstone of structure-based drug design. However, visual inspection and molecular mechanics approaches cannot explain the full complexity of molecular interactions. Quantum Mechanics approaches are often too computationally expensive, but one method, Fragment Molecular Orbital (FMO), offers an excellent compromise and has the potential to reveal key interactions that would otherwise be hard to detect. To illustrate this, we have applied the FMO method to 18 Class A GPCR-ligand crystal structures, representing different branches of the GPCR genome. Our work reveals key interactions that are often omitted from structure-based descriptions, including hydrophobic interactions, nonclassical hydrogen bonds, and the involvement of backbone atoms. This approach provides a more comprehensive picture of receptor-ligand interactions than is currently used and should prove useful for evaluation of the chemical nature of ligand binding and to support structure-based drug design.

Preclinical research strategies for newly approved drugs as reflected in early publication patterns

The present study aimed to explore early publication patterns (i.e. up to 1 year after obtaining regulatory approval) for newly registered drugs. From the website of the US Food and Drug Administration, all newly approved drugs for 6 calendar years between 1991 and 2011 were identified. Non-clinical original publications for these compounds were retrieved from PubMed and their abstracts analysed for type of study and reported data. This yielded 170 compounds for which 1954 original non-clinical publications were identified, i.e. a median/mean of 5/11.5 publications per compound; however, number of publications per compound varied widely (0-90) and this variation exhibited a non-Gaussian distribution. The earliest non-clinical publication typically was published less than 5 years before regulatory approval and more than 5 years after filing of the primary patent, but some compounds exhibited notable deviations from this pattern. Publications most often reported on efficacy related to the target indication and on potential future indications, with fewer studies addressing mechanisms of action, potency, selectivity, pharmacokinetics and toxic effects. For most compounds, data at the cellular and in vivo level were published, with fewer reports on effects on isolated tissues and even fewer at the molecular level. The preferred species for cellular studies was human, whereas for in vivo studies, it was rats and mice. In 75 % of cases, the lead author of the publication came from an academic institution, and most studies were published in classic pharmacology journals. We conclude that number, timing and scope of early non-clinical publications on newly approved drugs exhibit major variance. Factors potentially associated with such variance are explored in a companion paper.