Heavier-than-air flying machines are impossible

Alpha-bulges in G protein-coupled receptors

Agonist binding is related to a series of motions in G protein-coupled receptors (GPCRs) that result in the separation of transmembrane helices III and VI at their cytosolic ends and subsequent G protein binding. A large number of smaller motions also seem to be associated with activation. Most helices in GPCRs are highly irregular and often contain kinks, with extensive literature already available about the role of prolines in kink formation and the precise function of these kinks. GPCR transmembrane helices also contain many α-bulges. In this article we aim to draw attention to the role of these α-bulges in ligand and G-protein binding, as well as their role in several aspects of the mobility associated with GPCR activation. This mobility includes regularization and translation of helix III in the extracellular direction, a rotation of the entire helix VI, an inward movement of the helices near the extracellular side, and a concerted motion of the cytosolic ends of the helices that makes their orientation appear more circular and that opens up space for the G protein to bind. In several cases, α-bulges either appear or disappear as part of the activation process.

Current progress in Structure-Based Rational Drug Design marks a new mindset in drug discovery

The past decade has witnessed a paradigm shift in preclinical drug discovery with structure-based drug design (SBDD) making a comeback while high-throughput screening (HTS) methods have continued to generate disappointing results. There is a deficit of information between identified hits and the many criteria that must be fulfilled in parallel to convert them into preclinical candidates that have a real chance to become a drug. This gap can be bridged by investigating the interactions between the ligands and their receptors. Accurate calculations of the free energy of binding are still elusive; however progresses were made with respect to how one may deal with the versatile role of water. A corpus of knowledge combining X-ray structures, bioinformatics and molecular modeling techniques now allows drug designers to routinely produce receptor homology models of increasing quality. These models serve as a basis to establish and validate efficient rationales used to tailor and/or screen virtual libraries with enhanced chances of obtaining hits. Many case reports of successful SBDD show how synergy can be gained from the combined use of several techniques. The role of SBDD with respect to two different classes of widely investigated pharmaceutical targets: (a) protein kinases (PK) and (b) G-protein coupled receptors (GPCR) is discussed. Throughout these examples prototypical situations covering the current possibilities and limitations of SBDD are presented.

Developing a high-quality scoring function for membrane protein structures based on specific inter-residue interactions

Membrane proteins are of particular biological and pharmaceutical importance, and computational modeling and structure prediction approaches play an important role in studies of membrane proteins. Developing an accurate model quality assessment program is of significance to the structure prediction of membrane proteins. Few such programs are proposed that can be applied to a broad range of membrane protein classes and perform with high accuracy. We developed a new model scoring function Interaction-based Quality assessment (IQ), based on the analysis of four types of inter-residue interactions within the transmembrane domains of helical membrane proteins. This function was tested using three high-quality model sets: all 206 models of GPCR Dock 2008, all 284 models of GPCR Dock 2010, and all 92 helical membrane protein models of the HOMEP set. For all three sets, the scoring function can select the native structures among all of the models with the success rates of 93, 85, and 100% respectively. For comparison, these three model sets were also adopted for a recently published model assessment program for membrane protein structures, ProQM, which gave the success rates of 85, 79, and 92% separately. These results suggested that IQ outperforms ProQM when only the transmembrane regions of the models are considered. This scoring function should be useful for the computational modeling of membrane proteins.

Drug design for ever, from hype to hope

In its first 25 years JCAMD has been disseminating a large number of techniques aimed at finding better medicines faster. These include genetic algorithms, COMFA, QSAR, structure based techniques, homology modelling, high throughput screening, combichem, and dozens more that were a hype in their time and that now are just a useful addition to the drug-designers toolbox. Despite massive efforts throughout academic and industrial drug design research departments, the number of FDA-approved new molecular entities per year stagnates, and the pharmaceutical industry is reorganising accordingly. The recent spate of industrial consolidations and the concomitant move towards outsourcing of research activities requires better integration of all activities along the chain from bench to bedside. The next 25 years will undoubtedly show a series of translational science activities that are aimed at a better communication between all parties involved, from quantum chemistry to bedside and from academia to industry. This will above all include understanding the underlying biological problem and optimal use of all available data.

Integrating GPCR-specific information with full text articles

Background

With the continued growth in the volume both of experimental G protein-coupled receptor (GPCR) data and of the related peer-reviewed literature, the ability of GPCR researchers to keep up-to-date is becoming increasingly curtailed.

Results

We present work that integrates the biological data and annotations in the GPCR information system (GPCRDB) with next-generation methods for intelligently exploring, visualising and interacting with the scientific articles used to disseminate them. This solution automatically retrieves relevant information from GPCRDB and displays it both within and as an adjunct to an article.

Conclusions

This approach allows researchers to extract more knowledge more swiftly from literature. Importantly, it allows reinterpretation of data in articles published before GPCR structure data became widely available, thereby rescuing these valuable data from long-dormant sources.

Structural model of ligand-G protein-coupled receptor (GPCR) complex based on experimental double mutant cycle data: MT7 snake toxin bound to dimeric hM1 muscarinic receptor

The snake toxin MT7 is a potent and specific allosteric modulator of the human M1 muscarinic receptor (hM1). We previously characterized by mutagenesis experiments the functional determinants of the MT7-hM1 receptor interaction (Fruchart-Gaillard, C., Mourier, G., Marquer, C., Stura, E., Birdsall, N. J., and Servent, D. (2008) Mol. Pharmacol. 74, 1554-1563) and more recently collected evidence indicating that MT7 may bind to a dimeric form of hM1 (Marquer, C., Fruchart-Gaillard, C., Mourier, G., Grandjean, O., Girard, E., le Maire, M., Brown, S., and Servent, D. (2010) Biol. Cell 102, 409-420). To structurally characterize the MT7-hM1 complex, we adopted a strategy combining double mutant cycle experiments and molecular modeling calculations. First, thirty-three ligand-receptor proximities were identified from the analysis of sixty-one double mutant binding affinities. Several toxin residues that are more than 25 Å apart still contact the same residues on the receptor. As a consequence, attempts to satisfy all the restraints by docking the toxin onto a single receptor failed. The toxin was then positioned onto two receptors during five independent flexible docking simulations. The different possible ligand and receptor extracellular loop conformations were described by performing simulations in explicit solvent. All the docking calculations converged to the same conformation of the MT7-hM1 dimer complex, satisfying the experimental restraints and in which (i) the toxin interacts with the extracellular side of the receptor, (ii) the tips of MT7 loops II and III contact one hM1 protomer, whereas the tip of loop I binds to the other protomer, and (iii) the hM1 dimeric interface involves the transmembrane helices TM6 and TM7. These results structurally support the high affinity and selectivity of the MT7-hM1 interaction and highlight the atypical mode of interaction of this allosteric ligand on its G protein-coupled receptor target.

HIV-1 entry inhibition by small-molecule CCR5 antagonists: a combined molecular modeling and mutant study using a high-throughput assay

Based on the attrition rate of CCR5 small molecule antagonists in the clinic the discovery and development of next generation antagonists with an improved pharmacology and safety profile is necessary. Herein, we describe a combined molecular modeling, CCR5-mediated cell fusion, and receptor site-directed mutagenesis approach to study the molecular interactions of six structurally diverse compounds (aplaviroc, maraviroc, vicriviroc, TAK-779, SCH-C and a benzyloxycarbonyl-aminopiperidin-1-yl-butane derivative) with CCR5, a coreceptor for CCR5-tropic HIV-1 strains. This is the first study using an antifusogenic assay, a model of the interaction of the gp120 envelope protein with CCR5. This assay avoids the use of radioactivity and HIV infection assays, and can be used in a high throughput mode. The assay was validated by comparison with other established CCR5 assays. Given the hydrophobic nature of the binding pocket several binding models are suggested which could prove useful in the rational drug design of new lead compounds.

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

BACKGROUND

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

METHODOLOGY

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

CONCLUSIONS

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

Homology modelling and spectroscopy, a never-ending love story

Homology modelling is normally the technique of choice when experimental structure data are not available but three-dimensional coordinates are needed, for example, to aid with detailed interpretation of results of spectroscopic studies. Herein, the state of the art of homology modelling will be described in the light of a series of recent developments, and an overview will be given of the problems and opportunities encountered in this field. The major topic, the accuracy and precision of homology models, will be discussed extensively due to its influence on the reliability of conclusions drawn from the combination of homology models and spectroscopic data. Three real-world examples will illustrate how both homology modelling and spectroscopy can be beneficial for (bio)medical research.

Comparing four different approaches for the determination of inter-residue interactions provides insight for the structure prediction of helical membrane proteins

Studying inter-residue interactions provides insight into the folding and stability of both soluble and membrane proteins and is essential for developing computational tools for protein structure prediction. As the first step, various approaches for elucidating such interactions within protein structures have been proposed and proven useful. Since different approaches may grasp different aspects of protein structural folds, it is of interest to systematically compare them. In this work, we applied four approaches for determining inter-residue interactions to the analysis of three distinct structure datasets of helical membrane proteins and compared their correlation to the three individual quality measures of structures in these datasets. These datasets included one of 35 structures of rhodopsin receptors and bacterial rhodopsins determined at various resolutions, one derived from the HOMEP benchmark dataset previously reported, and one comprising of 139 homology models. It was found that the correlation between the average number of inter-residue interactions obtained by applying the four approaches and the available structure quality measures varied quite significantly among them. The best correlation was achieved by the approach focusing exclusively on favorable inter-residue interactions. These results provide interesting insight for the development of objective quality measure for the structure prediction of helical membrane proteins.

Comparison of the potential multiple binding modes of bicyclam, monocylam, and noncyclam small-molecule CXC chemokine receptor 4 inhibitors

CXC chemokine receptor (CXCR)4 is an HIV coreceptor and a chemokine receptor that plays an important role in several physiological and pathological processes, including hematopoiesis, leukocyte homing and trafficking, metastasis, and angiogenesis. This receptor belongs to the class A family of G protein-coupled receptors and is a validated target for the development of a new class of antiretroviral therapeutics. This study compares the interactions of three structurally diverse small-molecule CXCR4 inhibitors with the receptor and is the first report of the molecular interactions of the nonmacrocyclic CXCR4 inhibitor (S)-N'-(1H-benzimidazol-2-ylmethyl)-N'-(5,6,7,8-tetrahydroquinolin-8-yl)butene-1,4-diamine (AMD11070). Fourteen CXCR4 single-site mutants representing amino acid residues that span the entire putative ligand binding pocket were used in this study. These mutants were used in binding studies to examine how each single-site mutation affected the ability of the inhibitors to compete with (125)I-stromal-derived factor-1alpha binding. Our data suggest that these CXCR4 inhibitors bind to overlapping but not identical amino acid residues in the transmembrane regions of the receptor. In addition, our results identified amino acid residues that are involved in unique interactions with two of the CXCR4 inhibitors studied. These data suggest an extended binding pocket in the transmembrane regions close to the second extracellular loop of the receptor. Based on site-directed mutagenesis and molecular modeling, several potential binding modes were proposed for each inhibitor. These mechanistic studies might prove to be useful for the development of future generations of CXCR4 inhibitors with improved clinical pharmacology and safety profiles.

Molecular modeling of adenosine receptors: new results and trends

Adenosine is a ubiquitous neuromodulator, which carries out its biological task by stimulating four cell surface receptors (A(1), A(2A), A(2B), and A(3)). Adenosine receptors (ARs) are members of the superfamily of G protein-coupled receptors (GPCRs). Their discovery opened up new avenues for potential drug treatment of a variety of conditions such as asthma, neurodegenerative disorders, chronic inflammatory diseases, and many other physiopathological states that are believed to be associated with changes in adenosine levels. Knowledge of the 3D structure of ARs could be of great help in the task of understanding their function and in the rational design of specific ligands. However, since GPCRs are membrane-bound proteins, high-resolution structural characterization is still an extremely difficult task. For this reason, great importance has been placed on molecular modeling studies and, particularly in the last few years, on homology modeling (HM) techniques. The publication of the first high-resolution crystal structure for bovine rhodopsin (bRh), a GPCR superfamily member, provides the option of utilizing HM to generate 3D models based on detailed structural information. In this review we report, analyze, and compare the main experimental data, computational HM procedures and validation methods used for ARs, describing in detail the most successful results.

Predicting transmembrane helix pair configurations with knowledge-based distance-dependent pair potentials

As a first step toward a novel de novo structure prediction approach for alpha-helical membrane proteins, we developed coarse-grained knowledge-based potentials to score the mutual configuration of transmembrane (TM) helices. Using a comprehensive database of 71 known membrane protein structures, pairwise potentials depending solely on amino acid types and distances between C(alpha)-atoms were derived. To evaluate the potentials, they were used as an objective function for the rigid docking of 442 TM helix pairs. This is by far the largest test data set reported to date for that purpose. After clustering 500 docking runs for each pair and considering the largest cluster, we found solutions with a root mean squared (RMS) deviation <2 A for about 30% of all helix pairs. Encouragingly, if only clusters that contain at least 20% of all decoys are considered, a success rate >71% (with a RMS deviation <2 A) is obtained. The cluster size thus serves as a measure of significance to identify good docking solutions. In a leave-one-protein-family-out cross-validation study, more than 2/3 of the helix pairs were still predicted with an RMS deviation <2.5 A (if only clusters that contain at least 20% of all decoys are considered). This demonstrates the predictive power of the potentials in general, although it is advisable to further extend the knowledge base to derive more robust potentials in the future. When compared to the scoring function of Fleishman and Ben-Tal, a comparable performance is found by our cross-validated potentials. Finally, well-predicted "anchor helix pairs" can be reliably identified for most of the proteins of the test data set. This is important for an extension of the approach towards TM helix bundles because these anchor pairs will act as "nucleation sites" to which more helices will be added subsequently, which alleviates the sampling problem.

The Angiotensin II AT1 Receptor Structure-Activity Correlations in the Light of Rhodopsin Structure

The most prevalent physiological effects of ANG II, the main product of the renin-angiotensin system, are mediated by the AT1 receptor, a rhodopsin-like AGPCR. Numerous studies of the cardiovascular effects of synthetic peptide analogs allowed a detailed mapping of ANG II's structural requirements for receptor binding and activation, which were complemented by site-directed mutagenesis studies on the AT1 receptor to investigate the role of its structure in ligand binding, signal transduction, phosphorylation, binding to arrestins, internalization, desensitization, tachyphylaxis, and other properties. The knowledge of the high-resolution structure of rhodopsin allowed homology modeling of the AT1 receptor. The models thus built and mutagenesis data indicate that physiological (agonist binding) or constitutive (mutated receptor) activation may involve different degrees of expansion of the receptor's central cavity. Residues in ANG II structure seem to control these conformational changes and to dictate the type of cytosolic event elicited during the activation. 1) Agonist aromatic residues (Phe8 and Tyr4) favor the coupling to G protein, and 2) absence of these residues can favor a mechanism leading directly to receptor internalization via phosphorylation by specific kinases of the receptor's COOH-terminal Ser and Thr residues, arrestin binding, and clathrin-dependent coated-pit vesicles. On the other hand, the NH2-terminal residues of the agonists ANG II and [Sar1]-ANG II were found to bind by two distinct modes to the AT1 receptor extracellular site flanked by the COOH-terminal segments of the EC-3 loop and the NH2-terminal domain. Since the [Sar1]-ligand is the most potent molecule to trigger tachyphylaxis in AT1 receptors, it was suggested that its corresponding binding mode might be associated with this special condition of receptors.

Identification of Nonpeptide CCR5 Receptor Agonists by Structure-based Virtual Screening

A three-dimensional model of the chemokine receptor CCR5 has been built to fulfill structural peculiarities of its alpha-helix bundle and to distinguish known CCR5 antagonists from randomly chosen drug-like decoys. In silico screening of a library of 1.6 million commercially available compounds against the CCR5 model by sequential filters (drug-likeness, 2-D pharmacophore, 3-D docking, scaffold clustering) yielded a hit list of 59 compounds, out of which 10 exhibited a detectable binding affinity to the CCR5 receptor. Unexpectedly, most binders tested in a functional assay were shown to be agonists of the CCR5 receptor. A follow-up database query based on similarity to the most potent binders identified three new CCR5 agonists. Despite a moderate affinity of all nonpeptide ligands for the CCR5 receptor, one of the agonists was shown to promote efficient receptor internalization, which is a process therapeutically favorable for protection against HIV-1 infection.

How a small change in retinal leads to G-protein activation: initial events suggested by molecular dynamics calculations

Rhodopsin is the prototypical G-protein coupled receptor, coupling light activation with high efficiency to signaling molecules. The dark-state X-ray structures of the protein provide a starting point for consideration of the relaxation from initial light activation to conformational changes that may lead to signaling. In this study we create an energetically unstable retinal in the light activated state and then use molecular dynamics simulations to examine the types of compensation, relaxation, and conformational changes that occur following the cis-trans light activation. The results suggest that changes occur throughout the protein, with changes in the orientation of Helices 5 and 6, a closer interaction between Ala 169 on Helix 4 and retinal, and a shift in the Schiff base counterion that also reflects changes in sidechain interactions with the retinal. Taken together, the simulation is suggestive of the types of changes that lead from local conformational change to light-activated signaling in this prototypical system.

Triton X-100 can alter the temporal sequence of the light-driven proton pump of archaerhodopsin 4

We report that Triton X-100 can alter the temporal sequence of the light-induced proton uptake and release of archaerhodopsin 4 (AR4), a proton pumping protein in a species of Halobacteria from a Tibetan salt lake. Under physiological conditions, AR4 isolated from the bacterium exhibits a reversed temporal order of proton release and uptake compared to what is observed for bacteriorhodopsin (BR). However, in the presence of Triton X-100 early proton release was observed in AR4 at neutral pH by us. Further, this temporal order for light-driven proton release and uptake for AR4 was found to be recovered after the removal of Triton X-100 by Biobeads. This phenomenon of detergent-induced alteration of the order of proton release and uptake has not yet been reported in any other retinal-containing membrane protein such as BR. Our findings indicate that the function of AR4 is influenced by its self-assembled state, and meanwhile imply some subtle protein-lipid interactions or protein-protein interactions in adjusting the proton pumping behavior of AR4.

Ligand-supported homology modeling of the human angiotensin II type 1 (AT1) receptor: Insights into the molecular determinants of telmisartan binding

Angiotensin II type 1 (AT(1)) receptor belongs to the super-family of G-protein-coupled receptors, and antagonists of the AT(1) receptor are effectively used in the treatment of hypertension. To understand the molecular interactions of these antagonists, such as losartan and telmisartan, with the AT(1) receptor, a homology model of the human AT(1) (hAT(1)) receptor with all connecting loops was constructed from the 2.6 A resolution crystal structure (PDB i.d., 1L9H) of bovine rhodopsin. The initial model generated by MODELLER was subjected to a stepwise ligand-supported model refinement. This protocol involved initial docking of non-peptide AT(1) antagonists in the putative binding site, followed by several rounds of iterative energy minimizations and molecular dynamics simulations. The final model was validated based on its correlation with several structure-activity relationships and site-directed mutagenesis data. The final model was also found to be in agreement with a previously reported AT(1) antagonist pharmacophore model. Docking studies were performed for a series of non-peptide AT(1) receptor antagonists in the active site of the final hAT(1) receptor model. The docking was able to identify key molecular interactions for all the AT(1) antagonists studied. Reasonable correlation was observed between the interaction energy values and the corresponding binding affinities of these ligands, providing further validation for the model. In addition, an extensive unrestrained molecular dynamics simulation showed that the docking-derived bound pose of telmisartan is energetically stable. Knowledge gained from the present studies can be used in structure-based drug design for developing novel ligands for the AT(1) receptor.

A combined ligand-based and target-based drug design approach for G-protein coupled receptors: application to salvinorin A, a selective kappa opioid receptor agonist

Combined ligand-based and target-based drug design approaches provide a synergistic advantage over either method individually. Therefore, we set out to develop a powerful virtual screening model to identify novel molecular scaffolds as potential leads for the human KOP (hKOP) receptor employing a combined approach. Utilizing a set of recently reported derivatives of salvinorin A, a structurally unique KOP receptor agonist, a pharmacophore model was developed that consisted of two hydrogen bond acceptor and three hydrophobic features. The model was cross-validated by randomizing the data using the CatScramble technique. Further validation was carried out using a test set that performed well in classifying active and inactive molecules correctly. Simultaneously, a bovine rhodopsin based "agonist-bound" hKOP receptor model was also generated. The model provided more accurate information about the putative binding site of salvinorin A based ligands. Several protein structure-checking programs were used to validate the model. In addition, this model was in agreement with the mutation experiments carried out on KOP receptor. The predictive ability of the model was evaluated by docking a set of known KOP receptor agonists into the active site of this model. The docked scores correlated reasonably well with experimental pK (i) values. It is hypothesized that the integration of these two independently generated models would enable a swift and reliable identification of new lead compounds that could reduce time and cost of hit finding within the drug discovery and development process, particularly in the case of GPCRs.

Selective pharmacophore design for α1-adrenoceptor subtypes

Alpha1-adrenoceptors are G-protein coupled receptors found in a variety of vascular tissues and responsible for vasoconstriction. Selectivity for each of the three subtypes is an important consideration in drug design in order to minimise the possibility of side effects. Using Catalyst we developed ligand-based pharmacophores from alpha(1a,b,d)-selective antagonists available in the literature using three separate training sets. Four-feature pharmacophores were developed for the alpha(1a) and alpha(1b) subtype-selective antagonists and a five-feature pharmacophore was developed for the alpha(1d) subtype-selective antagonists. The alpha(1a) pharmacophore represents both class I and II compounds with good predictivity for other compounds outside the training set as well. The alpha(1b) pharmacophore best predicts the activity of prazosin analogues as these make up the majority of alpha(1b)-selective antagonists. Unexpectedly, no positive ionisable feature was incorporated in the alpha(1b) pharmacophore. The alpha(1d) pharmacophore was based primarily on one structural class of compounds, but has good predictivity for a heterogeneous test set. Preliminary docking studies using AutoDock and optimised alpha1-adrenoceptor homology models, conducted with the antagonists prazosin (32) and 66, showed good agreement with the findings from the pharmacophores.

Progress in structure prediction of α-helical membrane proteins

Transmembrane (TM) proteins comprise 20-30% of the genome but, because of experimental difficulties, they represent less than 1% of the Protein Data Bank. The dearth of membrane protein structures makes computational prediction a potentially important means of obtaining novel structures. Recent advances in computational methods have been combined with experimental data to constrain the modeling of three-dimensional structures. Furthermore, threading and ab initio modeling approaches that were effective for soluble proteins have been applied to TM domains. Surprisingly, experimental structures, proteomic analyses and bioinformatics have revealed unexpected architectures that counter long-held views on TM protein structure and stability. Future computational and experimental studies aimed at understanding the thermodynamic and evolutionary bases of these architectural details will greatly enhance predictive capabilities.

Interaction of arylpiperazine ligands with the hydrophobic part of the 5-HT1A receptor binding site

A flexible docking of a series of arylpiperazine derivatives with structurally different aryl part to the binding site of a model of human 5-HT1A receptor was exercised. The influence of structure and hydrophobic properties of aryl moiety on binding affinities was discussed and a model for ligand binding in the hydrophobic part of the binding site was proposed.

GRIS: glycoprotein-hormone receptor information system

The glycoprotein-hormone receptor information system (GRIS) presents a comprehensive view on all available molecular data for the lutropin/choriogonadotropin receptor, follitropin receptor, and thyrotropin receptor G protein-coupled receptors. It features a mutation database presently containing 696 point mutations, combined with all sequences and the associated homology models. The mutation information was automatically extracted from the literature and manually augmented with respect to constitutivity, surface expression, sensitivity to hormones, and binding affinity. All information in this integrated system is presented in a G protein-coupled receptor specialist-friendly way. A series of interactive tools such as rotamer analysis, mutation prediction, or cavity visualization aids with the design and interpretation of experiments. A universal residue numbering system has been introduced to ease database searches as well as the use of the information in conjunction with literature data from diverse origins. Users can upload new mutations. GRIS is freely accessible at http://gris.ulb.ac.be/.

Transmembrane protein structures without X-rays

Transmembrane (TM) proteins constitute 15-30% of the genome, but <1% of the structures in the Protein Data Bank. This discrepancy is disturbing, and emphasizes that structure determination of TM proteins remains challenging. The challenge is greatest for proteins from eukaryotes, the structures of which remain intractable despite tremendous advances that have been made towards structure determination of bacterial TM proteins. Notably, >50% of the membrane protein families in eukaryotes lack bacterial homologs. Therefore, it is conceivable that many more years will elapse before high-resolution structures of eukaryotic TM proteins emerge. Until then, integrated approaches that combine biochemical and computational analyses with low-resolution structures are likely to have increasingly important roles in providing frameworks for the mechanistic understanding of membrane-protein structure and function.

Investigation of mechanism of desmopressin binding in vasopressin V2 receptor versus vasopressin V1a and oxytocin receptors: Molecular dynamics simulation of the agonist-bound state in the membrane–aqueous system

The vasopressin V2 receptor (V2R) belongs to the Class A G protein-coupled receptors (GPCRs). V2R is expressed in the renal collecting duct (CD), where it mediates the antidiuretic action of the neurohypophyseal hormone arginine vasopressin (CYFQNCPRG-NH2, AVP). Desmopressin ([1-deamino, 8-D]AVP, dDAVP) is strong selective V2R agonist with negligible pressor and uterotonic activity. In this paper, the interactions responsible for binding of dDAVP to vasopressin V2 receptor versus vasopressin V1a and oxytocin receptors has been examined. Three-dimensional activated models of the receptors were constructed using the multiple sequence alignment and the complex of activated rhodopsin with Gt(alpha) C-terminal peptide of transducin MII-Gt(alpha) (338-350) prototype (Slusarz, R.; Ciarkowski, J. Acta Biochim Pol 2004 51, 129-136) as a template. The 1-ns unconstrained molecular dynamics (MD) of receptor-dDAVP complexes immersed in the fully hydrated 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphatidylcholine (POPC) membrane model was conducted in an Amber 7.0 force field. Highly conserved transmembrane residues have been proposed as being responsible for V2R activation and G protein coupling. Molecular mechanism of the dDAVP binding has been suggested. The internal water molecules involved in an intricate network of the hydrogen bonds inside the receptor cavity have been identified and their role in the stabilization of the agonist-bound state proposed.

Influence of N-1 substituent properties on binding affinities of arylpiperazines to the binding site of 5-HT1A receptor

Serotonin receptors (5-HTRs), especially the 5-HT1A subtype, have been the subject of intensive research for the past decade, due to their function in human physiology. Several structurally different classes of ligands are known to bind to the 5-HT1A receptor, but arylpiperazine derivatives are among the most important ligands. In the work, docking analyses were used to explain the binding affinities of a series of ligands with different N-1 substituent. All ligands had in common the arylpiperazine structure, while the N-1 subsistent was modified to investigate the influence of ligand structure on its binding affinity. The shape and size, as well as the rigidity of the subsistents were altered to investigate the possible effects on the formation of the receptor - ligand complex.

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

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

Interactions of human melanocortin 4 receptor with nonpeptide and peptide agonists

Specific interactions of human melanocortin-4 receptor (hMC4R) with its nonpeptide and peptide agonists were studied using alanine-scanning mutagenesis. The binding affinities and potencies of two synthetic, small-molecule agonists (THIQ, MB243) were strongly affected by substitutions in transmembrane alpha-helices (TM) 2, 3, 6, and 7 (residues Glu(100), Asp(122), Asp(126), Phe(261), His(264), Leu(265), and Leu(288)). In addition, a I129A mutation primarily affected the binding and potency of THIQ, while F262A, W258A, Y268A mutations impaired interactions with MB243. By contrast, binding affinity and potency of the linear peptide agonist NDP-MSH were substantially reduced only in D126A and H264A mutants. Three-dimensional models of receptor-ligand complexes with their agonists were generated by distance-geometry using the experimental, homology-based, and other structural constraints, including interhelical H-bonds and two disulfide bridges (Cys(40)-Cys(279), Cys(271)-Cys(277)) of hMC4R. In the models, all pharmacophore elements of small-molecule agonists are spatially overlapped with the corresponding key residues (His(6), d-Phe(7), Arg(8), and Trp(9)) of the linear peptide: their charged amine groups interact with acidic residues from TM2 and TM3, similar to His(6) and Arg(6) of NDP-MSH; their substituted piperidines mimic Trp(9) of the peptide and interact with TM5 and TM6, while the d-Phe aromatic rings of all three agonists contact with Leu(133), Trp(258), and Phe(261) residues.

CoMFA and CoMSIA investigations revealing novel insights into the binding modes of dopamine D3 receptor agonists

As an extension of a series of dopamine D(3) receptor agonists involving FAUC 54, ex-chiral pool synthesis, and biological evaluation of 3-substituted 7-aminotetrahydroindolizines was performed. Considering the structural features of both series of enantiomers, we developed a novel alignment hypothesis for D(3) agonists, allowing for the placement of the aromatic moieties on two alternative, adjacent positions. CoMFA and CoMSIA analyses yielded significant cross-validated q(2) values of 0.726 and 0.590, respectively, when a newly invented program application (IRAS) controlling the alignment selection proved to be useful. Employing the CoMFA/CoMSIA contribution maps, we were able to transform a previously constructed homology model of the D(3) receptor from an inactive into an activate state. Besides the established ionic interactions, we propose pi-stacking with Phe6.51 and a hydrogen bond between His6.55 and the acyl moiety to be primarily involved in the D(3) receptor binding of FAUC 54 and its analogues.

Structure-based Drug Discovery Using GPCR Homology Modeling: Successful Virtual Screening for Antagonists of the Alpha1A Adrenergic Receptor

In this paper, we describe homology modeling of the alpha1A receptor based on the X-ray structure of bovine rhodopsin. The protein model has been generated by applying ligand-supported homology modeling, using mutational and ligand SAR data to guide the protein modeling procedure. We performed a virtual screening of the company's compound collection to test how well this model is suited to identify alpha1A antagonists. We applied a hierarchical virtual screening procedure guided by 2D filters and three-dimensional pharmacophore models. The ca. 23,000 filtered compounds were docked into the alpha1A homology model with GOLD and scored with PMF. From the top-ranked compounds, 80 diverse compounds were tested in a radioligand displacement assay. 37 compounds revealed K(i) values better than 10 microM; the most active compound binds with 1.4 nM to the alpha1A receptor. Our findings suggest that rhodopsin-based homology models may be used as the structural basis for GPCR lead finding and compound optimization.

Conformational investigations on analogs of inflammation response inducing chemotactic tripeptide fMLP

Conformations of three analogs of for-L-Met-L-Leu-L-Phe-OH (fMLP), which initiates inflammatory response by interaction with the formyl peptide receptor (FPR), have been investigated by the application of the X-ray crystallographic technique. The investigated analogs of fMLP peptides are as follows: for-L-Met-1-amino-1-cyclooctane-carbonyl(Ac8c)-L-Phe-OMe; for-L-Met-L-Leu-L-p-iodo-Phe-OH; and for-L-Met-di-n-propylglycyl(Dpg)-L-Phe-OMe. The peptide backbone in and is constrained at position of fMLP by the introduction of Calpha,alpha-disubstituted glycines. In peptide, Phe-OMe is substituted by p-iodo-Phe-OH. Crystal structures reveal an overall folded conformation adopted by and. The former is folded in the type II beta-turn, which is stabilized by an intramolecular 1<--4 (formyl) C==O...H--N (Phe) hydrogen bond, whereas the latter is folded in an open turn without any intramolecular hydrogen bond. On the other hand, peptide has an extended conformation, and two different molecules in a crystallographic asymmetric unit form an antiparallel beta-sheet-like structure. In and, residues Ac8c and Dpg adopt left-handed helical and fully extended (C5) conformations, respectively. The cyclooctane ring in Ac8c acquires a boat-chair conformation. Crystal packing of is characterized by the association of aliphatic-aromatic rings via a C--H...pi interaction. In the crystal of, contrary to the usual observations, peptides are interlinked via networks of head-to-tail hydrogen bond and pi...pi interactions, which are generally observed to be mutually exclusive. The structure-function mechanism of the ligand-receptor interaction is discussed.