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

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

Locating binding poses in protein-ligand systems using reconnaissance metadynamics

A molecular dynamics-based protocol is proposed for finding and scoring protein-ligand binding poses. This protocol uses the recently developed reconnaissance metadynamics method, which employs a self-learning algorithm to construct a bias that pushes the system away from the kinetic traps where it would otherwise remain. The exploration of phase space with this algorithm is shown to be roughly six to eight times faster than unbiased molecular dynamics and is only limited by the time taken to diffuse about the surface of the protein. We apply this method to the well-studied trypsin-benzamidine system and show that we are able to refind all the poses obtained from a reference EADock blind docking calculation. These poses can be scored based on the length of time the system remains trapped in the pose. Alternatively, one can perform dimensionality reduction on the output trajectory and obtain a map of phase space that can be used in more expensive free-energy calculations.

A highly potent and specific MET therapeutic protein antagonist with both ligand-dependent and ligand-independent activity

Activation of the MET oncogenic pathway has been implicated in the development of aggressive cancers that are difficult to treat with current chemotherapies. This has led to an increased interest in developing novel therapies that target the MET pathway. However, most existing drug modalities are confounded by their inability to specifically target and/or antagonize this pathway. Anticalins, a novel class of monovalent small biologics, are hypothesized to be "fit for purpose" for developing highly specific and potent antagonists of cancer pathways. Here, we describe a monovalent full MET antagonist, PRS-110, displaying efficacy in both ligand-dependent and ligand-independent cancer models. PRS-110 specifically binds to MET with high affinity and blocks hepatocyte growth factor (HGF) interaction. Phosphorylation assays show that PRS-110 efficiently inhibits HGF-mediated signaling of MET receptor and has no agonistic activity. Confocal microscopy shows that PRS-110 results in the trafficking of MET to late endosomal/lysosomal compartments in the absence of HGF. In vivo administration of PRS-110 resulted in significant, dose-dependent tumor growth inhibition in ligand-dependent (U87-MG) and ligand-independent (Caki-1) xenograft models. Analysis of MET protein levels on xenograft biopsy samples show a significant reduction in total MET following therapy with PRS-110 supporting its ligand-independent mechanism of action. Taken together, these data indicate that the MET inhibitor PRS-110 has potentially broad anticancer activity that warrants evaluation in patients.

The study of ligand binding specificities of the lipid binding proteins : recombinant human a-tocopherol transport protein (a-ttp), supernatant protein factor (spf) and S. cerevisiae Sec 14p for vitamin e (rrr-a-tocopherol) and other hydrophobic ligands.

One of the various functions of proteins in biological systems is the transport of small molecules, for this purpose proteins have naturally evolved special mechanisms to allow both ligand binding and its subsequent release to a target site; a process fundamental to many biological processes. Transport of Vitamin E (a-tocopherol), a lipid soluble antioxidant, to membranes helps in the protection of polyunsaturated fatty acids against peroxidative damage. In this research, the ligand binding characteristics of several members of the CRALTRIO family of lipid binding proteins was examined; the recombinant human a-Tocopherol Transfer Protein (a-TIP), Supernatant Protein Factor (SPF)ffocopherol Associated Protein (TAP), Cellular Retinaldehyde Binding Protein (CRALBP) and the phosphatidylinositol transfer protein from S. cerevisiae Sec 14p. Recombinant Sec 14p was expressed and purified from E. coli for comparison of tocopherol binding to the two other recombinant proteins postulated to traffic a-tocopherol. Competitive binding assays using [3H]-a-tocopherol and Lipidex-l000 resin allowed determination of the dissociation constants ~) of the CRAL-TRIO proteins for a-tocopherol and - 20 hydrophobic ligands for evaluation of the possible biological relevance of the binding interactions observed. The KIs (nM) for RRR-a-tocopherol are: a-TIP: 25.0, Sec 14p: 373, CRALBP: 528 and SPFffAP: 615. This indicates that all proteins recognize tocopherol but not with the same affinity. Sec 14p bound its native ligand PI with a KI of381 whereas SPFffAP bound PI (216) and y-tocopherol (268) similarly in contrast to the preferential binding ofRRR-a-tocopherol by a-TIP. Efforts to adequately represent biologically active SPFff AP involved investigation of tocopherol binding for several different recombinant proteins derived from different constructs and in the presence of different potential modulators (Ca+2, Mg+2, GTP and GDP); none of these conditions enhanced or inhibited a-tocopherol binding to SPF. This work suggests that only aTTP serves as the physiological mediator of a-tocopherol, yet structural homology between proteins allows common recognition of similar ligand features. In addition, several photo-affmity analogs of a-tocopherol were evaluated for their potential utility in further elucidation of a-TTP function or identification of novel tocopherol binding proteins.

Use of cellular impedance to characterize ligand functional selectivity at G protein-coupled receptors

Les récepteurs couplés aux protéines G (RCPGs) représentent la plus grande famille de cibles thérapeutiques pour le traitement d’une panoplie de pathologies humaines. Bien que plusieurs décennies de recherche aient permis de façonner nos connaissances sur ces protéines membranaires, notre compréhension des déterminants moléculaires de leur activité signalétique reste encore limitée. De ces domaines de recherche, une avancée récente a mis à jour un nouveau phénomène, appelé sélectivité fonctionnelle des ligands, qui a bouleversé les paradigmes décrivant leu fonctionnement de ces récepteurs. Ce concept émane d’observations montrant que l’activité pharmacologique de certains ligands n’est pas nécessairement conservée sur tout le répertoire signalétiques connu du récepteur et peu se restreindre à l'activation sélective d’un sous-groupe de voies de signalisation.Ce nouveau modèle pharmacologique de l'activation des RCPG ouvre de nouvelles possibilités pour la découverte de médicaments plus efficace et sûr, ciblant les RCPGs. En effet, il permet la conception de molécules modulant spécifiquement les voies signalétiques d’intérêt thérapeutique, sans engager les autres voies qui pourraient mener à des effets secondaires indésirables ou de la tolérance. Cette thèse décrit l'utilisation d'une nouvelle approche sans marquage, basée sur la mesure du changement l'impédance cellulaire. Par la mesure des changements cellulaires, comme la morphologie, l’adhésion et/ou la redistribution des macromolécules, cette approche permet de mesurer de façon simultanée l'activité de plusieurs voies de signalisation impliqués dans ces réponses. Utilisant le récepteur β2-adrénergique (β2AR) comme modèle, nous avons démontré que les variations dans l’impédance cellulaire étaient directement liées à l’activation de multiples voies de signalisation suite à la stimulation du récepteur par son ligand. L’agoniste type du β2AR, l’isoprotérénol, s’est avéré induire une réponse d’impédance dose-dépendante constituée, dans le temps, de plusieurs caractéristiques distinctes pouvant être bloquées de façon compétitive par l’antagoniste ICI118,551 Par l’utilisation d’inhibiteurs sélectifs, nous avons été en mesure de déterminer la contribution de plusieurs voies signalétiques canoniques, comme les voies dépendantes de Gs et Gi, la production d’AMPc et l’activation de ERK1/2, sur ces changements. De plus, la dissection de la réponse d’impédance a permis d’identifier une nouvelle voie de mobilisation du Ca2+ contribuant à la réponse globale des changements initiés par la stimulation du β2AR. Dans une autre étude, nous avons rapporté que la réponse calcique induite par le β2AR serait attribuable à une transactivation Gs-dépendant du récepteur purinergique P2Y11, lui-même couplé à la protéine Gq. La mesure d’impédance permettant de distinguer et de décrire une pléiade d’activités signalétiques, nous avons émis l’hypothèse que des ligands arborant des profils signalétiques différents généreraient des réponses d’impédance distinctes. Le criblage d’une librairie de ligands spécifiques au β2AR a révélé une grande variété de signatures d’impédance. Grâce au développement d’une approche computationnelle innovatrice, nous avons été en mesure de regrouper ces signatures en cinq classes de composés, un regroupement qui s’est avéré hautement corrélé avec le profil signalétique des différents ligands. Nous avons ensuite combiné le criblage de composés par impédance avec l’utilisation d’inhibiteurs sélectifs de voies signalétiques afin d’augmenter la résolution du regroupement. En évaluant l’impact d’une voie signalétique donnée sur la signature d’impédance, nous avons été en mesure de révéler une plus grande variété de textures parmi les ligands. De plus, cette méthode s’est avérée efficace pour prédire le profil signalétique d’une librairie de composés non caractérisés, ciblant le β2AR. Ces travaux ont mené à l’élaboration d’une méthode permettant d’exprimer visuellement la sélectivité fonctionnelle de ligands et ont révélé de nouvelles classes de composés pour ce récepteur. Ces nouvelles classes de composés ont ensuite été testées sur des cardiomyocytes humains, confirmant que les composés regroupés dans différentes classes produisent des effets distincts sur la contractilité de ces cellules. Globalement, ces travaux démontrent la pertinence de l’utilisation de l’impédance cellulaire pour une évaluation précise des différences fonctionnelles parmi les composés ciblant les RCPGs. En fournissant une représentation pluridimensionnelle de la signalisation émanant des RCPGs à l’aide d’un seul essai ne requérant pas de marquage, les signatures d’impédance représentent une stratégie simple et innovante pour l’évaluation de la fonctionnalité sélective des ligands. Cette méthode pourrait être d’une grande utilité dans le processus de découverte de nouveaux médicaments.

Analyse von Protein-Ligand Interaktionen zur Charakterisierung zyklonukleotidbindender Proteine

Hyperpolarisations-aktivierte zyklonukleotid-gesteuerte (HCN) Kanäle übernehmen wichtige Funktionen in der Regulation der Herz- und Neuronalaktivität und können über einen dualen Mechanismus aus Membranhyperpolarisation und der Bindung von zyklischen Nukleotiden aktiviert werden. Ein großes Ziel der aktuellen Forschung ist die Entwicklung neuartiger Inhibitoren, die einer Fehlregulation der Kanäle entgegenwirken. In der vorliegenden Arbeit wurde die Regulation von HCN Kanälen durch zyklische Nukleotide im Detail analysiert, indem erstmals ein umfassender Screen mit 48 unterschiedlichen Zyklonukleotid-Analoga am C-terminalen Bereich (bestehend aus C-Linker und Zyklonukleotid-Bindedomäne) der drei Isoformen HCN1, HCN2 und HCN4 durchgeführt wurde. Mit Hilfe eines Fluoreszenzpolarisations-Assays wurde der Einfluss von Modifikationen in der Base, der Ribose und dem zyklischen Phosphat auf die Bindungsaffinitäten innerhalb der Zyklonukleotid-Bindedomäne untersucht. Zyklonukleotid-Analoga mit Modifikationen an der Position 7 und 8 der Base verschoben die apparenten Affinitäten im Vergleich zu den beiden natürlich vorkommenden Zyklonukleotiden cAMP und cGMP vom mikromolaren in den nanomolaren Bereich. Selektiv für die HCN4 Isoform erwiesen sich Zyklonukleotid-Analoga mit Modifikationen an der Position 6 der Base, während Modifikationen an der Position 8 der Base zu einer höheren Affinität für die HCN2 Isoform führten. Im Gegensatz zu HCN2 und HCN4 zeigte die HCN1 Isoform besonders hohe Affinitäten für Zyklonukleotid-Analoga mit Modifikationen an der Position 8 von cGMP. Eine Substitution der 2’-Hydroxylgruppe erlaubte keine Bindung an die HCN Kanäle. Mit 7-CH-cAMP konnte ein hochaffines Bindemolekül für HCN Kanäle identifiziert werden, denn der Austausch eines Stickstoffs gegen eine CH-Einheit an Position 7 der Base führte zu einer 100-fachen Steigerung der Affinität im Vergleich zu cAMP. In Übereinstimmung mit der hochaffinen Bindung konnte in kinetischen Analysen eine langsamere Dissoziationsrate für 7-CH-cAMP gemessen werden. Anhand thermodynamischer Messungen konnte ein entropisch favorisierter Bindungsmodus für 7-CH-cAMP im Vergleich zu cAMP identifiziert werden. Basierend auf einer Kristallstruktur des HCN4 CNBD:7-CH-cAMP Komplexes (2,5 Å) lässt sich erklären, dass 7-CH-cAMP durch seine höhere Lipohilie im Vergleich zu cAMP eine stärkere Präferenz für das hydrophobe Netzwerk zwischen Protein und Base besitzt. In detaillierten, vergleichenden Analysen mit den zyklonukleotidbindenden Proteinen PKA Typ I und II, hPKGIβ und Epac 1 und 2 konnte gezeigt werden, dass 7-CH-cAMP die höchsten Affinitäten für die drei Isoformen der HCN Kanäle aufwies. Somit könnte sich 7-CH-cAMP als vielversprechender Kandidat für die selektive Regulation von HCN Kanälen in vitro und in lebenden Zellen eignen und möglicherweise einen wichtigen Beitrag als krankheitsrelevanter Effektor leisten.

SCAPA (Spacially Addressable Protein Array) – a Novel Protein Array for the Differential Profiling of Ligand-receptor Induced Signalling

While protein microarray technology has been successful in demonstrating its usefulness for large scale high-throughput proteome profiling, performance of antibody/antigen microarrays has been only moderately productive. Immobilization of either the capture antibodies or the protein samples on solid supports has severe drawbacks. Denaturation of the immobilized proteins as well as inconsistent orientation of antibodies/ligands on the arrays can lead to erroneous results. This has prompted a number of studies to address these challenges by immobilizing proteins on biocompatible surfaces, which has met with limited success. Our strategy relates to a multiplexed, sensitive and high-throughput method for the screening quantification of intracellular signalling proteins from a complex mixture of proteins. Each signalling protein to be monitored has its capture moiety linked to a specific oligo ‘tag’. The array involves the oligonucleotide hybridization-directed localization and identification of different signalling proteins simultaneously, in a rapid and easy manner. Antibodies have been used as the capture moieties for specific identification of each signaling protein. The method involves covalently partnering each antibody/protein molecule with a unique DNA or DNA derivatives oligonucleotide tag that directs the antibody to a unique site on the microarray due to specific hybridization with a complementary tag-probe on the array. Particular surface modifications and optimal conditions allowed high signal to noise ratio which is essential to the success of this approach.

Computational chemistry for elucidating protein function: energetics and dynamics of myoglobin-ligand systems

State-of-the-art computational methodologies are used to investigate the energetics and dynamics of photodissociated CO and NO in myoglobin (Mb···CO and Mb···NO). This includes the combination of molecular dynamics, ab initio MD, free energy sampling, and effective dynamics methods to compare the results with studies using X-ray crystallography and ultrafast spectroscopy metho ds. It is shown that modern simulation techniques along with careful description of the intermolecular interactions can give quantitative agreement with experiments on complex molecular systems. Based on this agreement predictions for as yet uncharacterized species can be made.

FunFOLDQA: a quality assessment tool for protein-ligand binding site residue predictions

The estimation of prediction quality is important because without quality measures, it is difficult to determine the usefulness of a prediction. Currently, methods for ligand binding site residue predictions are assessed in the function prediction category of the biennial Critical Assessment of Techniques for Protein Structure Prediction (CASP) experiment, utilizing the Matthews Correlation Coefficient (MCC) and Binding-site Distance Test (BDT) metrics. However, the assessment of ligand binding site predictions using such metrics requires the availability of solved structures with bound ligands. Thus, we have developed a ligand binding site quality assessment tool, FunFOLDQA, which utilizes protein feature analysis to predict ligand binding site quality prior to the experimental solution of the protein structures and their ligand interactions. The FunFOLDQA feature scores were combined using: simple linear combinations, multiple linear regression and a neural network. The neural network produced significantly better results for correlations to both the MCC and BDT scores, according to Kendall’s τ, Spearman’s ρ and Pearson’s r correlation coefficients, when tested on both the CASP8 and CASP9 datasets. The neural network also produced the largest Area Under the Curve score (AUC) when Receiver Operator Characteristic (ROC) analysis was undertaken for the CASP8 dataset. Furthermore, the FunFOLDQA algorithm incorporating the neural network, is shown to add value to FunFOLD, when both methods are employed in combination. This results in a statistically significant improvement over all of the best server methods, the FunFOLD method (6.43%), and one of the top manual groups (FN293) tested on the CASP8 dataset. The FunFOLDQA method was also found to be competitive with the top server methods when tested on the CASP9 dataset. To the best of our knowledge, FunFOLDQA is the first attempt to develop a method that can be used to assess ligand binding site prediction quality, in the absence of experimental data.

Corticotropin-releasing factor binding protein dimerizes after association with ligand.

We have suggested recently that the fall in plasma CRF-binding protein (BP) during the last few weeks of pregnancy is a direct effect of association with its ligand because of the rapid decrease in plasma BP concentration seen in normal males reaching a nadir some 15 min after a bolus injection of synthetic CRF. In the present study, we have investigated the physicochemical properties of both natural and recombinant BP by gel filtration under physiological conditions and have shown that association of human CRF to this BP results in an increase in molecular weight consistent with the formation of a dimer form of the BP ligand complex. The dimer is more stable when the interaction occurs in the presence of serum or if a peptide with a higher affinity for the BP is substituted as ligand. Experimental evidence would also suggest that the dimer BP has a higher affinity for ligand than the monomeric form. We suggest that this dimerization occurs in vivo when CRF is released into the bloodstream and provides the trigger that causes the uptake of the complex at specific receptor sites.

The FunFOLD2 server for the prediction of protein-ligand interactions

The FunFOLD2 server is a new independent server that integrates our novel protein–ligand binding site and quality assessment protocols for the prediction of protein function (FN) from sequence via structure. Our guiding principles were, first, to provide a simple unified resource to make our function prediction software easily accessible to all via a simple web interface and, second, to produce integrated output for predictions that can be easily interpreted. The server provides a clean web interface so that results can be viewed on a single page and interpreted by non-experts at a glance. The output for the prediction is an image of the top predicted tertiary structure annotated to indicate putative ligand-binding site residues. The results page also includes a list of the most likely binding site residues and the types of predicted ligands and their frequencies in similar structures. The protein–ligand interactions can also be interactively visualized in 3D using the Jmol plug-in. The raw machine readable data are provided for developers, which comply with the Critical Assessment of Techniques for Protein Structure Prediction data standards for FN predictions. The FunFOLD2 webserver is freely available to all at the following web site: http://www.reading.ac.uk/bioinf/FunFOLD/FunFOLD_form_2_0.html.

In silico identification and characterization of protein-ligand binding sites

Protein–ligand binding site prediction methods aim to predict, from amino acid sequence, protein–ligand interactions, putative ligands, and ligand binding site residues using either sequence information, structural information, or a combination of both. In silico characterization of protein–ligand interactions has become extremely important to help determine a protein’s functionality, as in vivo-based functional elucidation is unable to keep pace with the current growth of sequence databases. Additionally, in vitro biochemical functional elucidation is time-consuming, costly, and may not be feasible for large-scale analysis, such as drug discovery. Thus, in silico prediction of protein–ligand interactions must be utilized to aid in functional elucidation. Here, we briefly discuss protein function prediction, prediction of protein–ligand interactions, the Critical Assessment of Techniques for Protein Structure Prediction (CASP) and the Continuous Automated EvaluatiOn (CAMEO) competitions, along with their role in shaping the field. We also discuss, in detail, our cutting-edge web-server method, FunFOLD for the structurally informed prediction of protein–ligand interactions. Furthermore, we provide a step-by-step guide on using the FunFOLD web server and FunFOLD3 downloadable application, along with some real world examples, where the FunFOLD methods have been used to aid functional elucidation.

Only subtle protein conformational adaptations are required for ligand binding to thyroid hormone receptors: Simulations using a novel multipoint steered molecular dynamics approach

Thyroid hormone receptors (TR) are hormone-dependent transcription regulators that play a major role in human health, development, and metabolic functions. The thyroid hormone resistance syndrome, diabetes, obesity, and some types of cancer are just a few examples of important diseases that are related to TR malfunctioning, particularly impaired hormone binding. Ligand binding to and dissociation from the receptor ultimately control gene transcription and, thus, detailed knowledge of binding and release mechanisms are fundamental for the comprehension of the receptor`s biological function and development of pharmaceuticals. In this work, we present the first computational study of ligand entry into the ligand binding domain (LBD) of a nuclear receptor. We report molecular dynamics simulations of ligand binding to TRs using a generalization of the steered molecular dynamics technique designed to perform single-molecule pulling simulations along arbitrarily nonlinear driving pathways. We show that only gentle protein movements and conformational adaptations are required for ligand entry into the LBDs and that the magnitude of the forces applied to assist ligand binding are of the order of the forces involved in ligand dissociation. Our simulations suggest an alternative view for the mechanisms ligand binding and dissociation of ligands from nuclear receptors in which ligands can simply diffuse through the protein surface to reach proper positioning within the binding pocket. The proposed picture indicates that the large-amplitude protein motions suggested by the apo- and holo-RXR alpha crystallographic structures are not required, reconciling conformational changes of LBDs required for ligand entry with other nuclear receptors apo-structures that resemble the ligand-bound LBDs.

Prion Protein and Its Ligand Stress Inducible Protein 1 Regulate Astrocyte Development

Prion protein (PrP(C)) interaction with stress inducible protein 1 (STI1) mediates neuronal survival and differentiation. However, the function of PrP(C) in astrocytes has not been approached. In this study, we show that STI1 prevents cell death in wild-type astrocytes in a protein kinase A-dependent manner, whereas PrP(C)-null astrocytes were not affected by STI1 treatment. At embryonic day 17, cultured astrocytes and brain extracts derived from PrP(C)-null mice showed a reduced expression of glial fibrillary acidic protein (GFAP) and increased vimentin and nestin expression when compared with wild-type, suggesting a slower rate of astrocyte maturation in PrP(C)-null animals. Furthermore, PrP(C)-null astrocytes treated with STI1 did not differentiate from a flat to a process-bearing morphology, as did wild-type astrocytes. Remarkably, STI1 inhibited proliferation of both wild-type and PrP(C)-null astrocytes in a protein kinase C-dependent manner. Taken together, our data show that PrP(C) and STI1 are essential to astrocyte development and act through distinct signaling pathways.(C) 2009 Wiley-Liss, Inc.