Refine
Year of publication
- 2009 (2432) (remove)
Document Type
- Article (978)
- Doctoral Thesis (391)
- Part of Periodical (311)
- Book (210)
- Review (128)
- Working Paper (116)
- Part of a Book (86)
- Report (65)
- Conference Proceeding (58)
- Preprint (15)
Language
- German (1439)
- English (855)
- Portuguese (55)
- Croatian (39)
- French (24)
- Multiple languages (5)
- Italian (4)
- Spanish (4)
- dut (2)
- Hungarian (2)
Keywords
- Deutsch (58)
- Linguistik (35)
- Literatur (30)
- Rezension (24)
- Filmmusik (21)
- Lehrdichtung (18)
- Reiseliteratur (16)
- Deutschland (14)
- Film (13)
- Literaturwissenschaft (13)
Institute
- Medizin (284)
- Extern (198)
- Biochemie und Chemie (158)
- Biowissenschaften (91)
- Präsidium (80)
- Physik (67)
- Gesellschaftswissenschaften (61)
- Rechtswissenschaft (51)
- Geowissenschaften (48)
- Geschichtswissenschaften (48)
The representation of small molecules as molecular graphs is a common technique in various fields of cheminformatics. This approach employs abstract descriptions of topology and properties for rapid analyses and comparison. Receptor-based methods in contrast mostly depend on more complex representations impeding simplified analysis and limiting the possibilities of property assignment. In this study we demonstrate that ligand-based methods can be applied to receptor-derived binding site analysis. We introduce the new method PocketGraph that translates representations of binding site volumes into linear graphs and enables the application of graph-based methods to the world of protein pockets. The method uses the PocketPicker algorithm for characterization of binding site volumes and employs a Growing Neural Gas procedure to derive graph representations of pocket topologies. Self-organizing map (SOM) projections revealed a limited number of pocket topologies. We argue that there is only a small set of pocket shapes realized in the known ligand-receptor complexes.
Die vorliegende, in kumulativer Schreibweise verfasste Arbeit erläutert die Entwicklung, Charakterisierung und Optimierung zweier unterschiedlicher Leitstrukturen, die als Agonisten von Peroxisomen Proliferator-aktivierten Rezeptoren (PPAR) und gleichsam als duale Inhibitoren der mikrosomalen Prostaglandin E2 Synthase-1 (mPGES-1) und der 5-Lipoxygenase (5-LO) wirken. Chemisch betrachtet sind dies zum ersten die Gruppe der alpha-n-Hexyl-Pirinixinsäurederivate und zum zweiten die Gruppe der 2-(Phenylthio)-hexansäurederivate. Die Publikation zur Synthese und in vitro-pharmakologischen Charakterisierung der alpha-n-Hexyl-Pirinixinsäurederivate an PPAR (Zettl et al., QSAR & Combinatorial Science, 28:576–586, 2009) enthält einerseits die strukturelle Optimierung durch Variation der Aryl-Substitution des zentralen Pyrimidinringes der Leitstruktur und andererseits die durch Docking-Verfahren gestützte Untersuchung des Einflusses der Stereochemie auf die PPAR-Aktivierung. Letztlich konnte durch die Einführung von Biphenyl-Substituenten eine Verbesserung insbesondere der PPARalpha-Aktivität gegenüber der als strukturellen Referenz dienenden alpha-n-Hexyl-Pirinixinsäure (Rau et al., Archiv der Pharmazie, 341:191–195, 2008) erreicht werden. Mit Hilfe von präparativer enantioselektiver HPLC wurde eine ausgewählte Verbindung in ihre beiden Enantiomere getrennt. Deren in vitro-pharmakologische Charakterisierung ergab, dass das (R)-Enantiomer insbesondere bei PPARalpha als Eutomer fungiert. Dieses Ergebnis konnte mit Hilfe von Docking-Studien weiter untermauert werden. Hierbei wurde deutlich, dass die Besetzung der linken proximalen Bindetasche der PPARalpha-Liganden-Bindungs-Domäne durch den alpha-n-Hexyl-Rest lediglich im Fall einer (R)-Konfiguration optimal erfolgen kann. Die Synthese und die in vitro-pharmakologische Charakterisierung der Substanzklasse der 2-(Phenylthio)-hexansäurederivate an PPAR sind in Zettl et al., Bioorganic & Medicinal Chemistry Letters, 19: 4421-4426, 2009 zusammengefasst. Bei der Analyse der Struktur-Wirkungs-Beziehungen erwies sich die Leitstruktur als hochaktiv und sehr robust. Je nach Substitutionsmuster des lipophilen Molekülteils wurden potente selektive PPARalpha-Agonisten wie auch PPARalpha-präferenzielle duale PPARalpha/gamma-Agonisten dargestellt. Durch die Synthese von Kohlenstoff-Analoga und alpha-unsubstituierten Verbindungen wurde des Weiteren der Einfluss des Schwefelatoms und des n-Butylrestes in alpha-Position zur Carbonsäure auf die PPAR-Aktivität untersucht. Hierbei konnte gezeigt werden, dass beide Strukturelemente einen großen Beitrag zur hohen PPARalpha-Aktivität der Leitstruktur leisten. Wie auch bei den alpha-n-Hexyl-Pirinixinsäurederivaten wurde eine ausgewählte Verbindung in ihre Enantiomere getrennt und der Einfluss des Stereozentrums in alpha-Position zur Carbonsäure untersucht. Das Ergebnis bestätigte die Resultate der vorangegangenen Studie: Das (R)-Enantiomer wirkte als Eutomer, wobei der stereochemische Einfluss bei PPARalpha besonders deutlich war. Ausgewählte Synthesen und die in vitro-pharmakologische Charakterisierung von Pirinixinsäurederivaten an mPGES-1, 5-LO sowie der Cyclooxygenase (COX) sind in Koeberle und Zettl et al., Journal of Medicinal Chemistry, 51:8068–8076, 2009 publiziert. Die Arbeit beinhaltet eine umfassende Reihe an Pirinixinsäurederivaten mit Strukturvariationen in alpha-Position zur Carbonsäure und im Aryl-Substitutionsmuster des Pyrimidinringes. Hinsichtlich der alpha-Substitution zeigte sich, dass für Alkylreste eine Kettenlänge von mindestens 6 Kohlenstoffatomen für einen dualen Wirkmechanismus erforderlich ist. Als Leitstruktur für duale mPGES-1/5-LO-Inhibitoren ergab sich somit alpha-n-Hexyl-substituierte Pirinixinsäure, deren Aryl-Substitutionsmuster am zentralen Pyrimidin weiter optimiert wurde. Als vorteilhaft erwies sich die Substitution mit Biphenylresten, wodurch die Darstellung von niedrig mikromolar aktiven dualen mPGES-1/5-LO-Inhibitoren gelang. Bei der Analyse der Strukur-Wirkungs-Beziehungen von unterschiedlichen Biphenylresten zeigte sich eine hohe strukturelle Toleranz hinsichtlich der dualen inhibitorischen Aktivität an der mPGES-1 und der 5-LO. Somit stellen die alpha-n-Hexyl-Pirinixinsäurederivate die ersten publizierten dualen mPGES-1/5-LO-Inhibitoren dar.
This study focuses on structural features of a particular GPCR type, the family C GPCRs. Structure- and ligand-based approaches were adopted for prediction of novel mGluR5 binding ligand and their binding modes. The objectives of this study were: 1. An analysis of function and structural implication of amino acids in the TM region of family C GPCRs. 2. The prediction of the TM domain structure of mGluR5. 3. The discovery of novel selective allosteric modulators of mGluR5 by virtual screening. 4. The prediction of a ligand binding mode for the allosteric binding site in mGluR5. GPCRs are a super-family of structurally related proteins although their primary amino acid sequence can be diverse. Using sequence information a conservation analysis of family C GPCRs should be applied to reveal characteristic differences and similarities with respect function, folding and ligand binding. Using experimental data and conservation analysis the allosteric binding site of mGluR5 should be characterized regarding NAM and PAM and selective ligand binding. For further evaluation experimental knowledge about family A GPCRs as well as conservation between vertebrate rhodopsins was planned to be compared to results obtained for family C GPCRs (Section 4.1 Conservation analysis of family C GPCRs). Since no receptor structure is available for any family C GPCR, discussion of conserved sequence positions between family A and C GPCRs requires the prediction of a receptor structure for mGluR5 using a family A receptor as template. In order to predict the mGluR5 structure a sequence alignment to a GPCR template protein will have to be proposed and GPCR specific features considered in structure calculation (Section 4.1.4 Structure prediction of mGluR5). The obtained structure was intended to be involved in ligand binding mode prediction of newly discovered active molecules. For discovery of novel selective mGluR modulators several ligand-based virtual screening protocols were adapted and evaluated. Prediction models were derived for selection of possibly active molecules using a diverse collection of known mGluR binding ligands. For that purpose a data collection of known mGluR binding ligands should be established and this reference collection analyzed with respect to different ligand activity classes, NAM or PAM and selective modulators. The prediction of novel NAMs and PAMs using several combinations of 2D-, 3D-, pharmacophore or molecule shape encoding methods with machine learning techniques and similarity determining methods should be tested in a prospective manner (Section 4.2 Virtual screening for novel mGluR modulators). In collaboration with Merz Pharmaceuticals (Merz GmbH & Co. KGaA, Frankfurt am Main, Germany) the modulating effect of a few hundred molecules should be approved in a functional cell-based assay. With the objective to predict a binding mode of the discovered active molecules, molecule docking should be applied using the allosteric binding site of the modeled mGluR5 structure (Section 4.2.4 Modeling of binding modes). Predicted ligand binding modes are to be correlated to conservation profiles that had resulted from the sequence-based entropy analysis and information from mutation experiments, and shall be compared to known ligand binding poses from crystal structures of family A GPCRs.
Die Identifizierung neuartiger Verbindungsklassen für ein pharmakologisches Zielsystem ist eine fordernde Aufgabe für die frühe präklinische Forschung, insbesondere wenn bereits vorherige umfangreiche Studien durchgeführt und viele Leitstrukturserien gefunden wurden. In dieser Arbeit konnte gezeigt werden, dass Scaffold Hopping durch Methoden des Virtual Screenings auch für Systeme möglich ist, für die bereits eine Vielzahl von Referenzsubstanzen beschrieben ist und somit wenig freier chemischer Raum für Innovation zur Verfügung steht. Als Beispielsystem wurde die GlycinB-Bindungsstelle der NR1-Untereinheit des NMDA-Rezeptors betrachtet. Verschiedene zwei- und dreidimensionale Techniken des Virtual Screenings wurden einer umfangreichen retrospektiven Validierung unterworfen. Zur Durchführung der prospektiven Virtual-Screening-Studie wurde eine automatisierte in silico Plattform entwickelt, die 8,9 Millionen käufliche Substanzen aus 46 Substanzkatalogen von 33 verschiedenen Anbietern sammelte, um etwa 5 Millionen unterschiedliche Moleküle in zweidimensionaler Darstellung aufzuarbeiten. Diese Menge an Substanzen stellt den größten Teil der zurzeit kommerziell verfügbaren chemischen Verbindungen, also den „verfügbaren chemischen Raum“ dar. Anhand der retrospektiv validierten Virtual Screening Techniken konnten in einer prospektiven Suche 21 GlycinB-Antagonisten mit neuartigen, d.h. für GlycinB noch unbeschriebenen Scaffolds gefunden werden. Ausgehend von drei dieser Virtual Screening Hits wurden 53 weitere Verbindungen mit insgesamt fünf unterschiedlichen neuartigen Scaffolds und einem gemeinsamen Azo-Motiv identifiziert. Die Struktur-Wirkungsbeziehungen dieser fünf chemischen Serien wurden charakterisiert. Das Ergebnis dieser Arbeit zeigt eindeutig, dass es lohnend ist, alle vorhandenen Methoden auszuschöpfen, da sich die validierten Methoden komplementär zueinander verhielten und kein Virtual Screening Hit von mehr als einer Technik gefunden wurde. Die Flexibilität von Proteinen als Antwort auf die Bindung unterschiedlicher Liganden stellt ein bislang ungelöstes chemieinformatisches Problem dar, welches auch grundlegende pharmakologische Bedeutung hat. So verursachen z.B. bei NMDA/GlycinB agonistische Liganden eine Konformationsänderung des Rezeptors. Diese ruft dann eine direkte funktionale Antwort in Form der Öffnung des Ionenkanals hervor. Auch der Bindungsmodus der Antagonisten von GlycinB ist trotz Vorhandenseins von zwei Kristallstrukturen und mehreren Hundert zum Teil hochaffiner Referenzstrukturen zum großen Teil ungeklärt. Im zweiten Teil dieser Arbeit wurde ein auf Moleküldynamiksimulationen basierendes Verfahren entwickelt, welches flexible Aminosäurereste im Rezeptor und damit induzierbare Bewegungen des Proteinrückgrates bestimmt. Die so identifizierten Reste wurden dann in einem erweiterten Verfahren des Induced-Fit-Dockings als explizit flexibel betrachtet. Hierdurch war die Berechnung verschiedener Bindungsmodi von Antagonisten möglich, die aufgrund ihrer Form und Größe nicht in die verfügbaren Kristallstrukturen von GlycinB passten. Diese benötigten somit einen Induced-Fit-Effekt des Rezeptors, um eine Bindung einzugehen. Für die im ersten Teil dieser Arbeit identifizierten Azo-Liganden wurde auf Basis dieser Methode ein gemeinsamer Bindungsmodus vorgeschlagen. Ebenso konnte anhand der Methodik eine Aussage über die funktionale Auswirkung der Proteinflexibilität beim Übergang vom antagonistischen zum agonistischen Rezeptorzustand von GlycinB getroffen werden. Ein großes Problem aktueller Dockingverfahren ist die mangelnde Verfügbarkeit von Scoringfunktionen, welche die tatsächliche biologische Bindungsaffinität eines Liganden berechnen. Hier wurde ein Verfahren für das Zielsystem GlycinB gezeigt, welches aufgrund der Berechnung des thermodynamischen Entropie- und Enthalpiegewinns durch Verdrängung von hydrophob eingeschlossenen Wasser aus der Bindungsstelle durch den Liganden eine Aussage über dessen zu erwartende Bindungsaffinität trifft. Dieses neuartige Scoringsystem wurde auf die im Virtual Screening identifizierten Serie von Azo-Liganden angewandt und verfügte über eine im Vergleich zu klassischen Scoringfunktionen des Molecular Dockings verbesserte Vorhersagekraft der biologischen Bindungsaffinität.
For a virtual screening study, we introduce a combination of machine learning techniques, employing a graph kernel, Gaussian process regression and clustered cross-validation. The aim was to find ligands of peroxisome-proliferator activated receptor gamma (PPAR-y). The receptors in the PPAR family belong to the steroid-thyroid-retinoid superfamily of nuclear receptors and act as transcription factors. They play a role in the regulation of lipid and glucose metabolism in vertebrates and are linked to various human processes and diseases. For this study, we used a dataset of 176 PPAR-y agonists published by Ruecker et al. ...
A new method to bridge the gap between ligand and receptor-based methods in virtual screening (VS) is presented. We introduce a structure-derived virtual ligand (VL) model as an extension to a previously published pseudo-ligand technique [1]: LIQUID [2] fuzzy pharmacophore virtual screening is combined with grid-based protein binding site predictions of PocketPicker [3]. This approach might help reduce bias introduced by manual selection of binding site residues and introduces pocket shape information to the VL. It allows for a combination of several protein structure models into a single "fuzzy" VL representation, which can be used to scan screening compound collections for ligand structures with a similar potential pharmacophore. PocketPicker employs an elaborate grid-based scanning procedure to determine buried cavities and depressions on the protein's surface. Potential binding sites are represented by clusters of grid probes characterizing the shape and accessibility of a cavity. A rule-based system is then applied to project reverse pharmacophore types onto the grid probes of a selected pocket. The pocket pharmacophore types are assigned depending on the properties and geometry of the protein residues surrounding the pocket with regard to their relative position towards the grid probes. LIQUID is used to cluster representative pocket probes by their pharmacophore types describing a fuzzy VL model. The VL is encoded in a correlation vector, which can then be compared to a database of pre-calculated ligand models. A retrospective screening using the fuzzy VL and several protein structures was evaluated by ten fold cross-validation with ROC-AUC and BEDROC metrics, obtaining a significant enrichment of actives. Future work will be devoted to prospective screening using a novel protein target of Helicobacter pylori and compounds from commercial providers.
Two methods for the fast, fragment-based combinatorial molecule assembly were developed. The software COLIBREE® (Combinatorial Library Breeding) generates candidate structures from scratch, based on stochastic optimization [1]. Result structures of a COLIBREE design run are based on a fixed scaffold and variable linkers and side-chains. Linkers representing virtual chemical reactions and side-chain building blocks obtained from pseudo-retrosynthetic dissection of large compound databases are exchanged during optimization. The process of molecule design employs a discrete version of Particle Swarm Optimization (PSO) [2]. Assembled compounds are scored according to their similarity to known reference ligands. Distance to reference molecules is computed in the space of the topological pharmacophore descriptor CATS [3]. In a case study, the approach was applied to the de novo design of potential peroxisome proliferator-activated receptor (PPAR gamma) selective agonists. In a second approach, we developed the formal grammar Reaction-MQL [4] for the in silico representation and application of chemical reactions. Chemical transformation schemes are defined by functional groups participating in known organic reactions. The substructures are specified by the linear Molecular Query Language (MQL) [5]. The developed software package contains a parser for Reaction-MQL-expressions and enables users to design, test and virtually apply chemical reactions. The program has already been used to create combinatorial libraries for virtual screening studies. It was also applied in fragmentation studies with different sets of retrosynthetic reactions and various compound libraries.
There is a renewed interest in pseudoreceptor models which enable computational chemists to bridge the gap of ligand- and receptor-based drug design. We developed a pseudoreceptor model for the histamine H4 receptor (H4R) based on five potent antagonists representing different chemotypes. Here we present the selection of potential ligand binding pockets that occur during molecular dynamics (MD) simulations of a homology-based receptor model. We present a method for prioritizing receptor models according to their match with the consensus ligand-binding mode represented by the pseudoreceptor. In this way, ligand information can be transferred to receptor-based modelling. We use Geometric Hashing to match three-dimensional points in Cartesion space. This allows for the rapid translation- and rotation-free comparison of atom coordinates, which also permits partial matching. The only prerequisite is a hash table, which uses distance triplets as hash keys. Each time a distance triplet occurring in the candidate point set which corresponds to an existing key, the match is represented by a vote of the respective key. Finally, the global match of both point sets can be easily extracted by selection of voted distance triplets. The results revealed a preferred ligand-binding pocket in H4R, which would not have been identified using an unrefined homology model of the protein. The key idea was to rely on ligand information by pseudoreceptor modelling.
A generic drug product (World Health Organization (WHO) terminology: multisource product) is usually marketed and manufactured after the expiry date of the innovator’s patent. Generic drugs are less expensive than the innovator products because generic manufacturers do not have to amortize the investment costs of research, development, marketing, and promotion. Multisource products must contain the same active pharmaceutical ingredients (APIs) as the original formulation and have to be shown to be interchangeable with the original formulation. Multisource products have to be shown bioequivalent to the innovator counterpart with respect to pharmacokinetic and pharmacodynamic properties. Multisource products are therefore identical in dose, strength, route of administration, safety, efficacy, and intended use. Bioequivalence can be demonstrated by in vitro dissolution, pharmacokinetic, pharmacodynamic or clinical studies. Since 2000, the U.S. Food and Drug Administration (FDA) allows the approval of certain multisource products solely on the basis of in vitro studies, i.e. by waiving in vivo studies in humans (“Biowaiver”), based on the Biopharmaceutics Classification Scheme (BCS). The BCS characterizes APIs by their solubility and permeability in the gastrointestinal tract (GIT). The different BCS Classes I-IV (Class I: high solubility, high permeability; Class II: low solubility, high permeability; Class III: high solubility, low permeability and Class IV: low solubility, low permeability) result from all possible combinations of high and low solubility with high and low permeability. Since the adoption of the BCS by the FDA in 1995, the BCS criteria have been under continuous development. In 2006, the WHO has released the most recent bioequivalence guidance including relaxed criteria for bioequivalence studies based on modified BCS criteria. According to this guidance, APIs belonging to the BCS classes I – and under defined conditions - II and III – are eligible for a biowaiver-based approval. The principal objective of this work was to characterize the first-line anti tuberculosis APIs, isoniazid, pyrazinamide, ethambutol dihydrochloride and rifampicin, according to their physicochemical, biopharmaceutical, pharmacokinetic and pharmacological properties and to classify them according to the BCS. Ethambutol dihydrochloride and isoniazid were classified as borderline BCS class I/III APIs. Pyrazinamide was classified as a BCS class III and rifampicin as a BCS class II API. Based on the BCS classification and the additional criteria defined in the WHO bioequivalence guidance, the possibility of biowaiver-based approval for immediate release (immediate release) solid oral dosage forms containing the first-line antituberculosis drugs was evaluated. A biowaiver-based approval with defined constraints was recommended for immediate release solid oral dosage forms containing isoniazid (interaction with reducing sugars), pyrazinamide and ethambutol dihydrochloride (relative narrow therapeutic index). Rifampicin was classified as a BCS class II API, and it was concluded that rifampicin containing solid oral immediate release drug products as well as Scale-Up and Post-Approval Changes (SUPAC) changes should not be approved by a biowaiver on the following basis: (i) its solubility and dissolution are highly variable due to polymorphism and instability, (ii) concomitant intake of food and antacids reduces its absorption and bioavailability, (iii) no in vitro predictive dissolution test has been found which correlates to in vivo absorption and (iv) several publications reporting cases of non-bioequivalent and bioinequivalent rifampicin products have been located in the literature. Thus, it is recommended that bioequivalence of rifampicin containing solid oral immediate release drug products should be established by in vivo pharmacokinetic studies in humans. This risk-benefit benefit assessment of a biowaiver-based approval was presented as a poster at the American Association of Pharmaceutical Scientists (AAPS) 2005 and subsequently published as “Biowaiver Monographs” in the Journal of Pharmaceutical Sciences. Based on the assessment of the dissolution properties of the antituberculosis drugs for a biowaiver approval, quality control dissolution methodologies for the International Pharmacopoeia (Pharm. Int.) were developed, presented at the WHO expert meeting and adopted in the Pharm. Int. (http://www.who.int/medicines/publications/pharmprep/OMS_TRS_948.pdf). Additionally, preliminary biowaiver recommendations were also developed for four firstline antimalarial drugs listed on the WHO Essential Medicines List (EML): Quinine, as both the hydrochloride and sulphate, and proguanil hydrochloride were classified as borderline BCS class I/III APIs. Since quinine is a narrow therapeutic index drug and many cases of non-bioequivalence have been reported in the literature, a biowaiverbased approval was not recommended. For solid oral immediate release dosage forms containing proguanil a biowaiver-based approval was recommended under the condition that they dissolve very rapidly. Primaquine phosphate was classified as a BCS class I API. Therefore, a biowaiver-based approval was recommended for immediate release solid oral dosage forms containing primaquine phosphate. Mefloquine hydrochloride was classified as a basic, BCS class IV/II API, making it ineligible for the biowaiver. Additionally, reports of non-bioequivalence and a narrow therapeutic index were found in the scientific literature. Consequently, bioequivalence of solid oral immediate release dosage forms containing mefloquine hydrochloride should be established by in vivo pharmacokinetic studies. The results for quinine hydrochloride and sulphate, proguanil hydrochloride, primaquine diphosphate and mefloquine hydrochloride were presented as a poster at the Pharmaceutical Sciences World Congress (PSWC) 2007 and published as a WHO Collaborating Center Report in June 2006. The aim of this project was to collect, evaluate, generate and publish relevant information for a biowaiver-based approval of essential medicines in order to provide a summary to local regulatory authorities. This information complements the selected list of essential medicines by providing information about the biopharmaceutical properties and pharmaceutical quality of solid oral immediate release dosage forms containing these APIs. The aim of the biowaiver project, inspired by the WHO and brought in life by the International Pharmaceutical Federation (FIP), is to enable access to essential medicines in standardized quality at an affordable price. In this work, a significant contribution to this aim in the form of four biowaiver monographs for the antituberculosis drugs and several reports on the antimalarials has been achieved.