Novel Strategies for Model-Building of G Protein-Coupled Receptors
van Neuren, Anske Stephanie
The G protein-coupled receptors constitute still the most densely populated proteinfamily encompassing numerous disease-relevant drug targets. Consequently, medicinal chemistry is expected to pursue targets from that protein family in that hits need to be generated and subsequently optimized towards viable clinical candidates for a variety of therapeutic areas. For the purpose of rationalizing structure-activity relationships within such optimization programs, structural information derived from the ligand's as well as the macromolecule's perspective is essential. While it is relatively straightforward to define pharmacophore hypotheses based on comparative modelling of structurally and biologically characterized low-molecular weight ligands, a deeper understanding of the molecular recognition event underlying, remains challenging, since the principally available amount of experimentally derived structural data on GPCRs is extremely scarse when compared to, e.g., soluble enzymes.
In this context, the protein modelling methodologies introduced, developed, optimized, and applied in this thesis provide structural models that are capable of assisting in the development of structural hypotheses on ligand-receptor complexes. As such they provide a valuable structural framework not only for a more detailed insight into ligand-GPCR interaction, but also for guiding the design process towards next-generation compounds which should display enhanced affinity.
The model building procedure developed in this thesis systematically follows a hierarchical approach, sequentially generating a 1D topology, followed by a 2D topology that is finally converted into a 3D topology. The determination of a 1D topology is based on a compartmentalization of the linear amino acid sequence of a GPCR of interest into the extracellular, intracellular, and transmembrane sequence stretches. The entire chapter 3 of this study elaborates on the strengths and weaknesses of applying automated prediction tools for the purpose of identifying the transmembrane sequence domains. Based on an once derived 1D topology, a type of in-plane projection structure for the seven transmembrane helices can be derived with the aide of calculated vectorial property moments, yielding the 2D topology. Thorough bioinformatics studies revealed that only a consensus approach based on a conceptual combination of different methods employing a carefully made selection of parameter sets gave reliable results, emphasizing the danger to fully automate a GPCR modelling procedure.
Chapter 4 describes a procedure to further expand the 2D topological findings into 3D space, exemplified on the human CCK-B receptor protein. This particular GPCR was chosen as the receptor of interest, since an enormous experimentally derived and structurally relevant data-set was available. Within the computational refinement procedure of constructed GPCR models, major emphasis was laid on the explicit treatment of a non-isotropic solvent environment during molecular mechanics (i.e. energy minimization and molecular dynamics simulations) calculations. The majority of simulations was therefore carried out in a tri-phasic solvent box accounting for a central lipid environment, flanked by two aqueous compartments, mimicking the extracellular and cytoplasmic space.
Chapter 5 introduces the reference compound set, comprising low-molecular weight compounds modulating CCK receptors, that was used for validation purposes of the generated models of the receptor protein.
Chapter 6 describes how the generated model of the CCK-B receptor was subjected to intensive docking studies employing compound series introduced in chapter 5. It turned out that by applying the DRAGHOME methodology viable structural hypotheses on putative receptor-ligand complexes could be generated. Based on the methodology pursued in this thesis a detailed model of the receptor binding site could be devised that accounts for known structure-activity relationships as well as for results obtained by site-directed mutagenesis studies in a qualitative manner.
The overall study presented in this thesis is primarily aimed to deliver a feasibility study on generating model structures of GPCRs by a conceptual combination of tailor-made bioinformatics techniques with the toolbox of protein modelling, exemplified on the human CCK-B receptor.
The generated structures should be envisioned as models only, not necessarily providing a detailed image of reality. However, consistent models, when verified and refined against experimental data, deliver an extremely useful structural contextual platform on which different scientific disciplines such as medicinal chemistry, molecular biology, and biophysics can effectively communicate.
Philipps-Universität Marburg
Medical sciences Medicine
urn:nbn:de:hebis:04-z2005-03563
opus:561
https://doi.org/10.17192/z2005.0356
Philipps-Universität Marburg
Ligand docking
GTP-bindende Proteine
G-Proteine
Molekulardesign
Medical sciences Medicine
Medizin
ths
Prof. Dr.
Klebe
Gerhard
Klebe, Gerhard (Prof. Dr.)
2003
Publikationsserver der Universitätsbibliothek Marburg
Universitätsbibliothek Marburg
https://archiv.ub.uni-marburg.de/diss/z2005/0356/cover.png
application/pdf
English
Molecular design
Pharmazeutische Chemie
Computational chemistry
NeueStrategien für Modellierung von G Protein-Gekuppelte Rezeptoren
The G protein-coupled receptors constitute still the most densely populated proteinfamily encompassing numerous disease-relevant drug targets. Consequently, medicinal chemistry is expected to pursue targets from that protein family in that hits need to be generated and subsequently optimized towards viable clinical candidates for a variety of therapeutic areas. For the purpose of rationalizing structure-activity relationships within such optimization programs, structural information derived from the ligand's as well as the macromolecule's perspective is essential. While it is relatively straightforward to define pharmacophore hypotheses based on comparative modelling of structurally and biologically characterized low-molecular weight ligands, a deeper understanding of the molecular recognition event underlying, remains challenging, since the principally available amount of experimentally derived structural data on GPCRs is extremely scarse when compared to, e.g., soluble enzymes.
In this context, the protein modelling methodologies introduced, developed, optimized, and applied in this thesis provide structural models that are capable of assisting in the development of structural hypotheses on ligand-receptor complexes. As such they provide a valuable structural framework not only for a more detailed insight into ligand-GPCR interaction, but also for guiding the design process towards next-generation compounds which should display enhanced affinity.
The model building procedure developed in this thesis systematically follows a hierarchical approach, sequentially generating a 1D topology, followed by a 2D topology that is finally converted into a 3D topology. The determination of a 1D topology is based on a compartmentalization of the linear amino acid sequence of a GPCR of interest into the extracellular, intracellular, and transmembrane sequence stretches. The entire chapter 3 of this study elaborates on the strengths and weaknesses of applying automated prediction tools for the purpose of identifying the transmembrane sequence domains. Based on an once derived 1D topology, a type of in-plane projection structure for the seven transmembrane helices can be derived with the aide of calculated vectorial property moments, yielding the 2D topology. Thorough bioinformatics studies revealed that only a consensus approach based on a conceptual combination of different methods employing a carefully made selection of parameter sets gave reliable results, emphasizing the danger to fully automate a GPCR modelling procedure.
Chapter 4 describes a procedure to further expand the 2D topological findings into 3D space, exemplified on the human CCK-B receptor protein. This particular GPCR was chosen as the receptor of interest, since an enormous experimentally derived and structurally relevant data-set was available. Within the computational refinement procedure of constructed GPCR models, major emphasis was laid on the explicit treatment of a non-isotropic solvent environment during molecular mechanics (i.e. energy minimization and molecular dynamics simulations) calculations. The majority of simulations was therefore carried out in a tri-phasic solvent box accounting for a central lipid environment, flanked by two aqueous compartments, mimicking the extracellular and cytoplasmic space.
Chapter 5 introduces the reference compound set, comprising low-molecular weight compounds modulating CCK receptors, that was used for validation purposes of the generated models of the receptor protein.
Chapter 6 describes how the generated model of the CCK-B receptor was subjected to intensive docking studies employing compound series introduced in chapter 5. It turned out that by applying the DRAGHOME methodology viable structural hypotheses on putative receptor-ligand complexes could be generated. Based on the methodology pursued in this thesis a detailed model of the receptor binding site could be devised that accounts for known structure-activity relationships as well as for results obtained by site-directed mutagenesis studies in a qualitative manner.
The overall study presented in this thesis is primarily aimed to deliver a feasibility study on generating model structures of GPCRs by a conceptual combination of tailor-made bioinformatics techniques with the toolbox of protein modelling, exemplified on the human CCK-B receptor.
The generated structures should be envisioned as models only, not necessarily providing a detailed image of reality. However, consistent models, when verified and refined against experimental data, deliver an extremely useful structural contextual platform on which different scientific disciplines such as medicinal chemistry, molecular biology, and biophysics can effectively communicate.
urn:nbn:de:hebis:04-z2005-03563
GPCR
Fachbereich Pharmazie
doctoralThesis
Arzneimitteldesign
2011-08-10
2005-07-25
Computational chemistry
Membranproteine
GPCR
monograph
opus:561
Drug design
2003-08-19
ppn:132502216
van Neuren, Anske Stephanie
van Neuren
Anske Stephanie
Die Familie der G Protein-gekoppelten Rezeptoren repräsentiert eine der höchst-populierten Proteinfamilien, die zahllose Krankheitsrelevante Zielproteine enthält.
Folglich wird die Medizinische Chemie Repräsentanten dieser Rezeptorfamilie bearbeiten, d.h. Hit-Strukturen generieren und diese zu vielversprechenden Kandidaten
für die klinische Entwicklung weiter optimieren, wobei sich ein breites Spektrum therapeutischer Indikationen adressieren lässt. Zum tiefergehenden Verständnis von
Struktur-Wirkungsbeziehungen im Kontext solcher Optimierungsprogramme liefern Strukturinformation über Liganden und über die Rezeptorproteine wertvolle Beiträge.
Während Pharmakophorhypothesen relativ einfach aus vergleichenden Studien von strukturell wie biologisch charakterisierten niedermolekularen Substanzen aufzustellen
sind, stellt die Generierung eines detaillierten Verständnisses über das zugrundeliegende molekularen Erkennungsgeschehen von z.B. Antagonist-GPCR Wechselwirkung
nach wie vor eine grosse Herausforderung dar. Dies liegt u.a. daran, dass die prinzipiell zur Verfügung stehende, experimentell abgeleitete Strukturinformation im
Vergleich zu z.B. löslichen Enzymen extrem limitiert ist. Vor diesem Hintergrund erlauben die in dieser Arbeit eingeführten, entwickelten und optimierten Methoden
der Proteinmodellierung die Erstellung von Strukturmodellen, die wertvolle Hilfestellung zum Aufstellen von Strukturhypothesen zu Ligand-Rezeptorkomplexen liefern.
Dadurch wird es nicht nur möglich, Ligand-Rezeptor Interaktion auf einem detaillierteren Niveau zu verstehen, auch wird der Designprozess zu
Verbindungen der nächsten Generation beeinflusst, der letztlich zu Substanzen mit verbesserter Affinität führen soll. Das hier entwickelte Verfahren
folgt systematisch einem hierarchischen Vorgehen, das sequentiell eine 1D Topologie, eine 2D Topologie und eine 3D Topologie erzeugt. Die Erstellung der 1D
Topologie beruht auf einer Kompartmentierung der linearen Primärstruktur, sprich der Aminosäuresequenz des GPCRs in extrazelluläre, intrazelluläre und transmembrane
Sequenzabschnitte. Kapitel 3 setzt sich mit den Vor- und Nachteilen der Anwendung automatisierter Vorhersage Programme auseinander, anhand derer die
potentiell transmembranen Sequenzbereiche identifizierbar sein sollten.
Ausgehend von einer erstellten 1D Topologie wird eine Projektionsstruktur für die 7 Helices erstellt, wobei die Projektionsebene parallel zur
Membranoberfläche liegt. Diese Projektionsstruktur(2D) wird mit Hilfe der vektoriellen Eigenschaftsmomente der einzelnen Helices erhalten. Intensive Studien
führten zu dem Resultat, dass nur ein Konsensus-Vorgehen (Kombination unterschiedlicher Methoden), basierend auf sorgfältig ausgewählten Parametersätzen valide 2D
Topologien lieferte, was auf die Gefahr hinweist, die sich in der Anwendung voll-automatisierter GPCR Modellingverfahren zur Modellgenerierung verbirgt.
Kapitel 4 beschreibt ein Procedere zur Transformation der 2D Topologie in ein 3D Strukturmodell, was exemplarisch am humanen CCK-B
Rezeptorprotein demonstriert wird. Dieser Rezeptor wurde ausgewählt, da eine Grosszahl experimentell abgeleiteter strukturrelevanter Daten vorhanden sind.
Zur Computer-gestützten energetischen Verfeinerung konstruierter GPCR-Modelle wurde die Hauptaufmerksamkeit auf die explizite Berücksichtigung der anisotropen
Umgebung im Rahmen von molekulardynamischen-Simulationen gelegt. Alle Simulationen wurden demzufolge in einem speziell entwickelten 3-Phasen-System durchgeführt,
das aus einer zentralen Lipidphase besteht, die von 2 wässrigen Phasen flankiert wird, welche das extrazelluläre und das cytoplasmatische Kompartiment imitieren
sollen.
Im Kapitel 5 wird der Ligandsatz vorgestellt, der als Referenz zur Validierung der Rezeptormodelle im Zuge der in Kapitel 6 beschriebenen Docking-Studien
darstellt. Im Kontext dieser Docking-Studien stellte sich heraus, dass durch Verwendung der DRAGHOME Methodik validierbare Strukturmodelle zur Rezeptor-Ligand Interaktion
erhalten werden konnten. Mithilfe des in dieser Studie verwendeten und entwickelten Methodenarsenals gelang es, ein detailliertes Modell der Rezeptor-Bindungstasche
zu formulieren, das sowohl bekannte Struktur-Wirkungsbeziehungen, als auch Ergebnisse aus Mutagenese-Studien zufriedenstellend zu erklären vermag. Ein
Dieser Arbeit war auch eine Art Machbarkeitsstudie zur Modellierung von GPCRs mit einem Kombination von maßgeschneiderte Bioinformatik-Techniken und Methoden der
Proteinmodellierung, was am Beispiel des humanen CCK-B Rezeptors demonstriert worden ist. Zusammenfassend: die erzeugten Strukturmodelle sind als
Modelle einzustufen, die nicht notwendigerweise mit den realen Gegebenheiten am Rezeptor übereinstimmen. Trotzdem stellt ein in sich konsistentes Modell eine extrem
hilfreiche Plattform dar, auf der unterschiedlichste wissenschaftliche Disziplinen miteinander effektiv kommunizieren können.
https://doi.org/10.17192/z2005.0356
Novel Strategies for Model-Building of G Protein-Coupled Receptors
G protein-gekuppelte Rezeptoren
G protein coupled receptors
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