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G protein-coupled receptors (GPCRs) play regulatory roles in many different physiological processes and they represent one of the most important class of drug targets. However, due to the lack of three-dimensional structures, structure based drug design has not been possible. The major bottleneck in getting three-dimensional crystal structure of GPCRs is to obtain milligram quantities of pure, homogenous and stable protein. Therefore, during my Ph.D. thesis, I focused on expression, characterization and isolation of three GPCRs namely human bradykinin receptor subtype 2 (B2R), human angiotensin II receptor subtype 1 (AT1aR), and human neuromedin U receptor subtype 2 (NmU2R). These receptors were heterologously produced in three different expression systems (i.e. Pichia pastoris, insect cells and mammalian cells), biochemically characterized and subsequently solubilized and purified for structural studies The human bradykinin receptor subtype 2 (B2R) is constitutively expressed in a variety of cells, including endothelial cells, vascular smooth muscle cells and cardiomyocytes. Activation of B2R is important in pathogenesis of inflammation, pain, tissue injury and cardioprotective mechanisms. During this study, recombinant B2R was produced in methylotrophic yeast Pichia pastoris (3.5 pmol/mg), insect cells (10 pmol/mg) and mammalian cells (60 pmol/mg). The recombinant receptor was characterized in terms of [3H] bradykinin binding, G protein coupling, localization, and glycosylation. Subsequently, it was solubilized and purified using affinity chromatography. Homogeneity and stability of purified B2R was monitored by gel filtration analysis. Milligram amounts of pure and stable receptor were obtained from BHK cells and Sf9 cells, which were used for three-dimensional crystallization attempts. The second receptor, which I worked on, is human angiotensin II receptor subtype 1 (AT1aR). AT1aR is distributed in smooth muscle cells, liver, kidney, heart, lung and testis. Activation of AT1aR is implicated in the regulation of blood pressure, hypertension and cardiovascular diseases. Recombinant AT1aR was produced at high levels in Pichia pastoris (167 pmol/mg), while at moderate levels in insect cells (29 pmol/mg) and mammalian cells (32 pmol/mg). The recombinant receptor was characterized in terms of [3H] angiotensin II binding, localization, and glycosylation. Subsequently, the receptor was solubilized and purified using affinity chromatography. Homogeneity and stability of purified AT1aR was monitored by gel filtration analysis. Milligram amounts of pure and stable receptor were obtained from Pichia pastoris, which were used for threedimensional crystallization attempts. In addition to B2R and AT1aR, I also attempted to produce and isolate the human neuromedin U receptor subtype 2 (NmU2R), which was deorphanized recently. It is found in highest abundance in the central nervous system, particularly the medulla oblongata, spinal cord and thalamus. The distribution of this receptor suggests its regulatory role in sensory transmission and modulation. During this study, recombinant NmU2R was produced in Pichia pastoris (6 pmol/mg) and BHK cells (9 pmol/mg). Recombinant receptor was characterized with regard to [125I] NmU binding, localization and glycosylation. Subsequently, the receptor was solubilized and purified using affinity chromatography. Due to its low expression level, further expression optimization is required in order to obtain milligram amounts for structural studies. The long-term goal of this study was to obtain three-dimensional crystal structure of recombinant GPCRs. However, 3-dimensional crystallization of human recombinant membrane proteins still remains a difficult task. On the other hand, recent advances in the solid-state NMR spectroscopy offer ample opportunities to study receptor-ligand systems, provided milligram quantities of purified receptor are available. Therefore, in parallel to 3-dimensional crystallization trials, purified B2R was also used for solid-state NMR analysis in order to investigate the receptor bound conformation of bradykinin. Preliminary results are promising and indicate significant structural changes in bradykinin upon binding to B2R. Further experiments are ongoing and will hopefully result in the structure of receptor bound bradykinin. One of the challenges in GPCR crystallization is the small hydrophilic surface area that is available to make crystal contacts. One possibility to overcome this problem can be the reconstitution of a GPCR complex with an interacting protein for cocrystallization. For this purpose, I coexpressed B2R and AT1aR, which form a stable heterodimer complex, in BHK cells. I could successfully isolate the heterodimer complex by using two-step affinity purification. Unfortunately, this complex was not stable over time and disassociates within three days of purification. However, during coexpression of B2R and AT1aR in BHK cells, I observed that B2R was localized in the plasma membrane in coexpressing cells while it was retained intracellularly when expressed alone. This coexpression of AT1aR with B2R resulted in a four-fold increase in [3H] bradykinin binding sites on the cell surface. In addition, these two receptors were cointernalized in response to their individual specific ligands. Interestingly, colocalization of B2R and AT1aR was also found in human foreskin fibroblasts (which endogenously express both receptors), in line with the possibility that heterodimerization may be required for surface localization of B2R in native tissues as well. This is the first report where surface localization of a peptide GPCR is triggered by a distantly related peptide GPCR. These data support the hypothesis that heterodimerization may be a prerequisite for cell surface localization of some GPCRs. A second approach that I followed to stabilize the purified B2R was to reconstitute the B2R-β-arrestin complex. β-arrestin is a cytosolic protein that participates in agonist mediated desensitization of GPCRs and therefore dampens the cellular responses initiated by the activation of GPCRs. I tried to reconstitute B2R-β-arrestin complex in vitro by mixing purified B2R and purified β-arrestin. But, no interaction of these two proteins was observed in the pull-down assays. However, a C-terminal mutant of B2R (where a part of the C-terminus of the B2R is exchanged with that of the vasopressin receptor) was found to interact with β-arrestin in vitro as revealed by pull-down assays. In conclusion, this work establishes the production, characterization and isolation of three recombinant human GPCRs. Recombinant receptors were produced in milligram amounts and therefore, pave the way for structural analysis. The heterodimer complex of B2R-AT1aR and B2R-β-arrestin complex can be of great help during crystallization. In addition, it was also found for the first time that the surface localization of a peptide GPCR can be triggered by heterodimerization with a distantly related peptide GPCR.
The 5'-terminal cloverleaf (CL)-like RNA structures are essential for the initiation of positive- and negative-strand RNA synthesis of entero- and rhinoviruses. SLD is the cognate RNA ligand of the viral proteinase 3C (3Cpro), which is an indispensable component of the viral replication initiation complex. The structure of an 18mer RNA representing the apical stem and the cGUUAg D-loop of SLD from the first 5'-CL of BEV1 was determined in solution to a root-mean-square deviation (r.m.s.d.) (all heavy atoms) of 0.59 A (PDB 1Z30). The first (antiG) and last (synA) nucleotide of the D-loop forms a novel ‘pseudo base pair’ without direct hydrogen bonds. The backbone conformation and the base-stacking pattern of the cGUUAg-loop, however, are highly similar to that of the coxsackieviral uCACGg D-loop (PDB 1RFR) and of the stable cUUCGg tetraloop (PDB 1F7Y) but surprisingly dissimilar to the structure of a cGUAAg stable tetraloop (PDB 1MSY), even though the cGUUAg BEV D-loop and the cGUAAg tetraloop differ by 1 nt only. Together with the presented binding data, these findings provide independent experimental evidence for our model [O. Ohlenschläger, J. Wöhnert, E. Bucci, S. Seitz, S. Häfner, R. Ramachandran, R. Zell and M. Görlach (2004) Structure, 12, 237–248] that the proteinase 3Cpro recognizes structure rather than sequence.
In order to further understand how DNA polymerases discriminate against incorrect dNTPs, we synthesized two sets of dNTP analogues and tested them as substrates for DNA polymerase a (pol alpha) and Klenow fragment (exo-) of DNA polymerase I (Escherichia coli ). One set of analogues was designed to test the importance of the electronic nature of the base. The bases consisted of a benzimidazole ring with one or two exocyclic substituent(s) that are either electron-donating (methyl and methoxy) or electronwithdrawing (trifluoromethyl and dinitro). Both pol a and Klenow fragment exhibit a remarkable inability to discriminate against these analogues as compared to their ability to discriminate against incorrect natural dNTPs. Neither polymerase shows any distinct electronic or steric preferences for analogue incorporation. The other set of analogues, designed to examine the importance of hydrophobicity in dNTP incorporation, consists of a set of four regioisomers of trifluoromethyl benzimidazole. Whereas pol a and Klenow fragment exhibited minimal discrimination against the 5- and 6-regioisomers, they discriminated much more effectively against the 4- and 7-regioisomers. Since all four of these analogues will have similar hydrophobicity and stacking ability, these data indicate that hydrophobicity and stacking ability alone cannot account for the inability of pol a and Klenow fragment to discriminate against unnatural bases. After incorporation, however, both sets of analogues were not efficiently elongated. These results suggest that factors other than hydrophobicity, sterics and electronics govern the incorporation of dNTPs into DNA by pol {alpha} and Klenow fragment.
DCD – a novel plant specific domain in proteins involved in development and programmed cell death
(2005)
Background: Recognition of microbial pathogens by plants triggers the hypersensitive reaction, a common form of programmed cell death in plants. These dying cells generate signals that activate the plant immune system and alarm the neighboring cells as well as the whole plant to activate defense responses to limit the spread of the pathogen. The molecular mechanisms behind the hypersensitive reaction are largely unknown except for the recognition process of pathogens. We delineate the NRP-gene in soybean, which is specifically induced during this programmed cell death and contains a novel protein domain, which is commonly found in different plant proteins.
Results: The sequence analysis of the protein, encoded by the NRP-gene from soybean, led to the identification of a novel domain, which we named DCD, because it is found in plant proteins involved in d evelopment and c ell d eath. The domain is shared by several proteins in the Arabidopsis and the rice genomes, which otherwise show a different protein architecture. Biological studies indicate a role of these proteins in phytohormone response, embryo development and programmed cell by pathogens or ozone.
Conclusion: It is tempting to speculate, that the DCD domain mediates signaling in plant development and programmed cell death and could thus be used to identify interacting proteins to gain further molecular insights into these processes.
The quinol:fumarate reductase (QFR) is the terminal reductase of anaerobic fumarate respiration, the most commonly occurring type of anaerobic respiration. This membrane protein complex couples the oxidation of menaquinol to menaquinone to the reduction of fumarate to succinate. The three-dimensional crystal structure of the QFR from Wolinella succinogenes has previoulsy been solved at 2.2 Å resolution. Although the diheme-containing QFR from W. succinogenes is known to catalyze an electroneutral process, structural and functional characterization of parental and variant enzymes has revealed active site locations which indicate electrogenic catalysis across the membrane. A solution to this apparent controversy was proposed with the so-called “Epathway hypothesis”. According to this, transmembrane electron transfer via the heme groups is strictly coupled to a parallel, compensatory transfer of protons via a transiently established pathway, which is inactive in the oxidized state of the enzyme. Proposed constituents of the E-pathway are the side chain of Glu C180, and the ring C propionate of the distal heme. Previous experimental evidence strongly supports such a role for the former constituent. One aim of this thesis is to investigate by a combination of specific 13C-heme propionate labeling and FTIR difference spectroscopy whether the ring C propionate of the distal heme is involved in redox-coupled proton transfer in the QFR from W. succinogenes. In addition to W. succinogenes, the primary structures of the QFR enzymes of two other e- proteobacteria are known. These are Campylobacter jejuni and Helicobacter pylori, which unlike W. succinogenes are human pathogens. The QFR from H. pylori has previously been established to be a potential drug target, and the same is likely for the QFR from C. jejuni. The two pathogenic species colonize mucosal surfaces causing several diseases. The possibility of studying these QFRs from these bacteria and creating more efficient drugs specifically active for this enzyme depends substantially on the availability of large amounts of high-quality protein. Further, biochemical and structural studies on QFR enzymes from e- proteobacteria species other than W. succinogenes can be valuable to enlighten new aspects or corroborate the current understanding of this class of membrane proteins.
Virtual screening of potential bioactive substances using the support vector machine approach
(2005)
Die vorliegende Dissertation stellt eine kumulative Arbeit dar, die in insgesamt acht wissenschaftlichen Publikationen (fünf publiziert, zwei eingerichtet und eine in Vorbereitung) dargelegt ist. In diesem Forschungsprojekt wurden Anwendungen von maschinellem Lernen für das virtuelle Screening von Moleküldatenbanken durchgeführt. Das Ziel war primär die Einführung und Überprüfung des Support-Vector-Machine (SVM) Ansatzes für das virtuelle Screening nach potentiellen Wirkstoffkandidaten. In der Einleitung der Arbeit ist die Rolle des virtuellen Screenings im Wirkstoffdesign beschrieben. Methoden des virtuellen Screenings können fast in jedem Bereich der gesamten pharmazeutischen Forschung angewendet werden. Maschinelles Lernen kann einen Einsatz finden von der Auswahl der ersten Moleküle, der Optimierung der Leitstrukturen bis hin zur Vorhersage von ADMET (Absorption, Distribution, Metabolism, Toxicity) Eigenschaften. In Abschnitt 4.2 werden möglichen Verfahren dargestellt, die zur Beschreibung von chemischen Strukturen eingesetzt werden können, um diese Strukturen in ein Format zu bringen (Deskriptoren), das man als Eingabe für maschinelle Lernverfahren wie Neuronale Netze oder SVM nutzen kann. Der Fokus ist dabei auf diejenigen Verfahren gerichtet, die in der vorliegenden Arbeit verwendet wurden. Die meisten Methoden berechnen Deskriptoren, die nur auf der zweidimensionalen (2D) Struktur basieren. Standard-Beispiele hierfür sind physikochemische Eigenschaften, Atom- und Bindungsanzahl etc. (Abschnitt 4.2.1). CATS Deskriptoren, ein topologisches Pharmakophorkonzept, sind ebenfalls 2D-basiert (Abschnitt 4.2.2). Ein anderer Typ von Deskriptoren beschreibt Eigenschaften, die aus einem dreidimensionalen (3D) Molekülmodell abgeleitet werden. Der Erfolg dieser Beschreibung hangt sehr stark davon ab, wie repräsentativ die 3D-Konformation ist, die für die Berechnung des Deskriptors angewendet wurde. Eine weitere Beschreibung, die wir in unserer Arbeit eingesetzt haben, waren Fingerprints. In unserem Fall waren die verwendeten Fingerprints ungeeignet zum Trainieren von Neuronale Netzen, da der Fingerprintvektor zu viele Dimensionen (~ 10 hoch 5) hatte. Im Gegensatz dazu hat das Training von SVM mit Fingerprints funktioniert. SVM hat den Vorteil im Vergleich zu anderen Methoden, dass sie in sehr hochdimensionalen Räumen gut klassifizieren kann. Dieser Zusammenhang zwischen SVM und Fingerprints war eine Neuheit, und wurde von uns erstmalig in die Chemieinformatik eingeführt. In Abschnitt 4.3 fokussiere ich mich auf die SVM-Methode. Für fast alle Klassifikationsaufgaben in dieser Arbeit wurde der SVM-Ansatz verwendet. Ein Schwerpunkt der Dissertation lag auf der SVM-Methode. Wegen Platzbeschränkungen wurde in den beigefügten Veröffentlichungen auf eine detaillierte Beschreibung der SVM verzichtet. Aus diesem Grund wird in Abschnitt 4.3 eine vollständige Einführung in SVM gegeben. Darin enthalten ist eine vollständige Diskussion der SVM Theorie: optimale Hyperfläche, Soft-Margin-Hyperfläche, quadratische Programmierung als Technik, um diese optimale Hyperfläche zu finden. Abschnitt 4.3 enthält auch eine Diskussion von Kernel-Funktionen, welche die genaue Form der optimalen Hyperfläche bestimmen. In Abschnitt 4.4 ist eine Einleitung in verschiede Methoden gegeben, die wir für die Auswahl von Deskriptoren genutzt haben. In diesem Abschnitt wird der Unterschied zwischen einer „Filter“- und der „Wrapper“-basierten Auswahl von Deskriptoren herausgearbeitet. In Veröffentlichung 3 (Abschnitt 7.3) haben wir die Vorteile und Nachteile von Filter- und Wrapper-basierten Methoden im virtuellen Screening vergleichend dargestellt. Abschnitt 7 besteht aus den Publikationen, die unsere Forschungsergebnisse enthalten. Unsere erste Publikation (Veröffentlichung 1) war ein Übersichtsartikel (Abschnitt 7.1). In diesem Artikel haben wir einen Gesamtüberblick der Anwendungen von SVM in der Bio- und Chemieinformatik gegeben. Wir diskutieren Anwendungen von SVM für die Gen-Chip-Analyse, die DNASequenzanalyse und die Vorhersage von Proteinstrukturen und Proteininteraktionen. Wir haben auch Beispiele beschrieben, wo SVM für die Vorhersage der Lokalisation von Proteinen in der Zelle genutzt wurden. Es wird dabei deutlich, dass SVM im Bereich des virtuellen Screenings noch nicht verbreitet war. Um den Einsatz von SVM als Hauptmethode unserer Forschung zu begründen, haben wir in unserer nächsten Publikation (Veröffentlichung 2) (Abschnitt 7.2) einen detaillierten Vergleich zwischen SVM und verschiedenen neuronalen Netzen, die sich als eine Standardmethode im virtuellen Screening etabliert haben, durchgeführt. Verglichen wurde die Trennung von wirstoffartigen und nicht-wirkstoffartigen Molekülen („Druglikeness“-Vorhersage). Die SVM konnte 82% aller Moleküle richtig klassifizieren. Die Klassifizierung war zudem robuster als mit dreilagigen feedforward-ANN bei der Verwendung verschiedener Anzahlen an Hidden-Neuronen. In diesem Projekt haben wir verschiedene Deskriptoren zur Beschreibung der Moleküle berechnet: Ghose-Crippen Fragmentdeskriptoren [86], physikochemische Eigenschaften [9] und topologische Pharmacophore (CATS) [10]. Die Entwicklung von weiteren Verfahren, die auf dem SVM-Konzept aufbauen, haben wir in den Publikationen in den Abschnitten 7.3 und 7.8 beschrieben. Veröffentlichung 3 stellt die Entwicklung einer neuen SVM-basierten Methode zur Auswahl von relevanten Deskriptoren für eine bestimmte Aktivität dar. Eingesetzt wurden die gleichen Deskriptoren wie in dem oben beschriebenen Projekt. Als charakteristische Molekülgruppen haben wir verschiedene Untermengen der COBRA Datenbank ausgewählt: 195 Thrombin Inhibitoren, 226 Kinase Inhibitoren und 227 Faktor Xa Inhibitoren. Es ist uns gelungen, die Anzahl der Deskriptoren von ursprünglich 407 auf ungefähr 50 zu verringern ohne signifikant an Klassifizierungsgenauigkeit zu verlieren. Unsere Methode haben wir mit einer Standardmethode für diese Anwendung verglichen, der Kolmogorov-Smirnov Statistik. Die SVM-basierte Methode erwies sich hierbei in jedem betrachteten Fall als besser als die Vergleichsmethoden hinsichtlich der Vorhersagegenauigkeit bei der gleichen Anzahl an Deskriptoren. Eine ausführliche Beschreibung ist in Abschnitt 4.4 gegeben. Dort sind auch verschiedene „Wrapper“ für die Deskriptoren-Auswahl beschrieben. Veröffentlichung 8 beschreibt die Anwendung von aktivem Lernen mit SVM. Die Idee des aktiven Lernens liegt in der Auswahl von Molekülen für das Lernverfahren aus dem Bereich an der Grenze der verschiedenen zu unterscheidenden Molekülklassen. Auf diese Weise kann die lokale Klassifikation verbessert werden. Die folgenden Gruppen von Moleküle wurden genutzt: ACE (Angiotensin converting enzyme), COX2 (Cyclooxygenase 2), CRF (Corticotropin releasing factor) Antagonisten, DPP (Dipeptidylpeptidase) IV, HIV (Human immunodeficiency virus) protease, Nuclear Receptors, NK (Neurokinin receptors), PPAR (peroxisome proliferator-activated receptor), Thrombin, GPCR und Matrix Metalloproteinasen. Aktives Lernen konnte die Leistungsfähigkeit des virtuellen Screenings verbessern, wie sich in dieser retrospektiven Studie zeigte. Es bleibt abzuwarten, ob sich das Verfahren durchsetzen wird, denn trotzt des Gewinns an Vorhersagegenauigkeit ist es aufgrund des mehrfachen SVMTrainings aufwändig. Die Publikationen aus den Abschnitten 7.5, 7.6 und 7.7 (Veröffentlichungen 5-7) zeigen praktische Anwendungen unserer SVM-Methoden im Wirkstoffdesign in Kombination mit anderen Verfahren, wie der Ähnlichkeitssuche und neuronalen Netzen zur Eigenschaftsvorhersage. In zwei Fällen haben wir mit dem Verfahren neuartige Liganden für COX-2 (cyclooxygenase 2) und dopamine D3/D2 Rezeptoren gefunden. Wir konnten somit klar zeigen, dass SVM-Methoden für das virtuelle Screening von Substanzdatensammlungen sinnvoll eingesetzt werden können. Es wurde im Rahmen der Arbeit auch ein schnelles Verfahren zur Erzeugung großer kombinatorischer Molekülbibliotheken entwickelt, welches auf der SMILES Notation aufbaut. Im frühen Stadium des Wirstoffdesigns ist es wichtig, eine möglichst „diverse“ Gruppe von Molekülen zu testen. Es gibt verschiedene etablierte Methoden, die eine solche Untermenge auswählen können. Wir haben eine neue Methode entwickelt, die genauer als die bekannte MaxMin-Methode sein sollte. Als erster Schritt wurde die „Probability Density Estimation“ (PDE) für die verfügbaren Moleküle berechnet. [78] Dafür haben wir jedes Molekül mit Deskriptoren beschrieben und die PDE im N-dimensionalen Deskriptorraum berechnet. Die Moleküle wurde mit dem Metropolis Algorithmus ausgewählt. [87] Die Idee liegt darin, wenige Moleküle aus den Bereichen mit hoher Dichte auszuwählen und mehr Moleküle aus den Bereichen mit niedriger Dichte. Die erhaltenen Ergebnisse wiesen jedoch auf zwei Nachteile hin. Erstens wurden Moleküle mit unrealistischen Deskriptorwerten ausgewählt und zweitens war unser Algorithmus zu langsam. Dieser Aspekt der Arbeit wurde daher nicht weiter verfolgt. In Veröffentlichung 6 (Abschnitt 7.6) haben wir in Zusammenarbeit mit der Molecular-Modeling Gruppe von Aventis-Pharma Deutschland (Frankfurt) einen SVM-basierten ADME Filter zur Früherkennung von CYP 2C9 Liganden entwickelt. Dieser nichtlineare SVM-Filter erreichte eine signifikant höhere Vorhersagegenauigkeit (q2 = 0.48) als ein auf den gleichen Daten entwickelten PLS-Modell (q2 = 0.34). Es wurden hierbei Dreipunkt-Pharmakophordeskriptoren eingesetzt, die auf einem dreidimensionalen Molekülmodell aufbauen. Eines der wichtigen Probleme im computerbasierten Wirkstoffdesign ist die Auswahl einer geeigneten Konformation für ein Molekül. Wir haben versucht, SVM auf dieses Problem anzuwenden. Der Trainingdatensatz wurde dazu mit jeweils mehreren Konformationen pro Molekül angereichert und ein SVM Modell gerechnet. Es wurden anschließend die Konformationen mit den am schlechtesten vorhergesagten IC50 Wert aussortiert. Die verbliebenen gemäß dem SVM-Modell bevorzugten Konformationen waren jedoch unrealistisch. Dieses Ergebnis zeigt Grenzen des SVM-Ansatzes auf. Wir glauben jedoch, dass weitere Forschung auf diesem Gebiet zu besseren Ergebnissen führen kann.
The technique of site-specific fluorescence labelling with Tetramethylrhodaminemaleimide (TMRM) in combination with two electrode voltage-clamp technique (TEVC), an approach that has been named voltage clamp fluorometry (VCF), has been used in this work to study the Na,K-ATPase. The TMRM dye has the ability to attach covalently to cysteine residues and it responds to changes in the hydrophobicity of its local environment. We exploited this property using a construct of the Na-pump in which the native, extracellularly accessible cysteines were removed and cysteine residues were introduced by site-directed mutagenesis in specific positions of the Na-pump. In this way it was possible to detect site-specific conformational rearrangements of the Na-pump in a time-resolved fashion within a native membrane environment. In particular this technique allows to resolve reactions with low electrogenicity that cannot be satisfactorily analyzed with purely electrophysiological techniques and to identify the conformations of the enzyme under specific ionic composition of the measuring buffers. We used VCF to study the influence that several cations like Na+, K+, NMG+, TEA+ and BTEA+ exert on the distribution of the Na,K-ATPase between several enzymatic intermediates and on some of the reactions related to cation transport. To this end we utilized the mutants N790C in the loop M5-M6 and the mutant E307C, T309C, L311C and E312C in the loop M3-M4. From the correspondence of the fluorescence changes with the activation and inhibition of pumping current, by K+ and ouabain respectively, and from the fact that in Na+/Na+ exchange conditions the voltage distribution of charge movement and fluorescence changes evoked by voltage jumps are in reasonable agreement we conclude that through the fluorescence signals measured from these mutants, we can indeed monitor conformational changes linked to transport activity of the enzyme. For the mutants N790 and L311, it was found that the Na+ dependence of the amplitude and kinetics of the fluorescence signal associated with the E1P-E2P transition is in agreement with the prediction of an access channel model describing the regulation of the access of extracellular Na+ to its binding site. In particular for the mutants E307 and T309 it was found that in Na+/Na+ exchange conditions, the conformational change tracked by the fluorescence was much slower than the charge relaxation at hyperpolarized potentials while the kinetics was very similar at depolarized potentials. This implies that at hyperpolarized potentials the conformational change connected to the E1P-E2P transition does not give a large contribution to the electrogenicity of the process which is also consistent with the access channel model. On the mutant N790C it was found that the external pH does not seem to have any effect on the E1P-E2P equilibrium even if it seems to modulate the fluorescence quantum yield of the dye. Fluorescence quenching experiments with iodide and D2O indicate that at hyperpolarized potentials the local environment of the mutant N790C, experiences a small change in the accessibility to water without major changes in the local electrostatic field ...
The Na+/proline transporter of E. Coli (PutP) is responsible for the uptake of proline which is subsequently used not only as a carbon and nitrogen source and a constituent of proteins but also as a particularly effective osmoprotectant. However, for a long time there was little known about the single steps in the reaction cycle of this transporter and only few details about its structure-function relationship are available. Aim of the present work was to achieve a deeper understanding about the kinetic properties of the Na+/proline transporter and to get insights into the structure-function relationship of the substrate binding. To answer these questions different techniques were used. By using the novel SSM technique combining the preparation of PutP proteoliposomes it was possible to demonstrate for the first time the electrogenic substrate binding to PutP transporter. Due to rapid solution exchange measurements on the SSM it was additionally possible to obtain time resolved information about the kinetic details of the cytoplasmic substrate binding sites which were not available by previous steady state and equilibrium binding measurements. Pre-steady-state charge translocation was observed after rapid addition of one or both of the cosubstrates Na+ and/or proline to the PutP-WT proteoliposomes adsorbed on the SSM. Thereby it was possible to link the observed electrical signals with the binding activity of PutP. The observed Na+ and/or proline induced charge displacement were assigned to an electrogenic Na+ and/or proline binding process at the cytoplasmic face of the enzyme with a rate constant of k > 50 s-1 proceeding the rate limiting step of the reaction cycle. Furthermore, based on the kinetic analysis of the electrical signals obtained from the measurements of PutP on SSM, the following characteristics of the substrates binding in PutP were deduced: (1) both Na+ and proline can bind individually to the transporter. Under physiological conditions, an ordered binding mechanism prevails; while at sufficiently high concentrations, each substrate can bind in the absence of the other; (2) substrate binding is electrogenic not only for Na+, but also for the uncharged cosubstrate proline. The charge displacement associated with Na+ binding and proline binding is of comparable size and independent of the presence of the respective cosubstrate. In addition, it was concluded that Na+ accesses its binding site through a high-field access channel resulting in a charge translocation, whereas the binding of the electroneutral proline induces a conformation alteration involving the displacement of charged amino acid residue(s) of the protein; (3) Na+ and proline binding sites interact cooperatively with each other by increasing the affinity and/or the speed of binding of the respective cosubstrate; (4) proline binding proceeds in a two step process: low affinity (~ 0.9 mM) electroneutral substrate binding followed by a nearly irreversible electrogenic conformational transition; (5) membrane impermeable PCMBS inhibits both Na+ and proline binding to the inside-out orientated PutP transporter, indicating that rather than selectively blocking a specific binding site, PCMBS probably locks the enzyme in an inactive state. The possible targets for this SH-reagent are cysteines 281 and 344 located close to the cytoplasmic surface of the protein. Beyond it, transient electrical currents of PutP were also observed on the BLM after rapid addition of proline in the presence of Na+. This was possible by combining the conventional BLM technique with high-speed flash-photolysis of caged-proline. Indeed the signals on the BLM indicate the detection of a different underlying reaction process in comparison to the data achieved by the SSM technique. This has paved the way for supplemental information about the reaction cycle since it was possible to assign the flash-photolysis BLM signals to the proline binding step followed by the internalization of Na+ and proline into the liposome. Thereby it was found, that the presence of Na+ is indispensable and the time constant for the process is ~ 63 ms. Moreover, structure-function information about the Na+ and proline binding sites of PutP was obtained by investigating the functionally important amino acid residues Asp55, Gly63 and Asp187 with site-directed mutagenesis and the combined SSM technique. One finding is that the mutated proteins PutP-D55C and PutP-G63C showed no activity on the SSM. Therefore, it can be assumed that either both Asp55 and Gly63 are crucial for the structure of PutP protein, or they are located at or close to the Na+ and proline binding sites. Furthermore, the results obtained from PutP-D187N and PutP-D187C mutants on SSM suggest that Asp187 of PutP is likely to be involved in the Na+ binding at the cytoplasmic side of the backward running carrier. Taken together the results of the present work have substantially broadened the known picture of the Na+/proline transporter PutP thereby several steps of the reaction cycle were elucidated, and moreover, valuable insights into the structure-function relationship of the transporter have become available.
Group III presynaptic metabotropic glutamate receptors (mGluRs) play a central role in regulating presynaptic activity through G-protein effects on ion channels and signal transducing enzymes. Like all Class C G-protein coupled receptors, mGluR8 has an extended intracellular C-terminal domain (CTD) presumed to allow for modulation of downstream signaling. To elucidate the function and modulation of mGluR8, yeast two-hybrid screens of an adult rat brain cDNA library were performed with the CTDs of mGluR8a and 8b (mGluR8-C) as baits. Different components of the sumoylation cascade (ube2a, sumo-1, Pias1, Pias gamma and Pias xbeta) and some other proteins were identified as mGluR8 interacting proteins. Binding assays using recombinant GST-fusion proteins confirmed that Pias1 interacts not only with mGluR8-C, but all group III mGluR CTDs. Pias1 binding to mGluR8-C required a region N-terminally to a consensus sumoylation motif and was not affected by arginine substitution of the conserved lysine K882 within this motif. Co-transfection of fluorescently tagged mGluR8a-C, sumo-1 and enzymes of the sumoylation cascade into HEK 293 cells showed that mGluR8a-C can be sumoylated in cells. Arginine substitution of lysine K882 within the consensus sumoylation motif, but not of other conserved lysines within the CTD, abolished in vivo sumoylation. The results are consistent with post-translational sumoylation providing a novel mechanism of group III mGluR regulation.