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Will combinatorial chemistry keep its promise? Biotechnol. Healthc., 2(3):26, 2005. [253] John J. Irwin and Brian K. Shoichet. ZINC { a free database of commercially available compounds for virtual screening. J. Chem. Inf. Model., 45:177{182, 2005. growing opus:6959 docking Fragment 2016-09-23 Publikationsserver der Universitätsbibliothek Marburg Universitätsbibliothek Marburg docking growing ligand scubidoo Pharmazeutische Chemie Verbesserter Ansatz zum Ligand growing durch Fragment docking und dem designen von Fragment Bibliotheken Fachbereich Pharmazie scubidoo 2016-11-10 https://archiv.ub.uni-marburg.de/diss/z2016/0809/cover.png monograph Die Fragment-basierte Wirkstoffforschung (“fragment-based drug discovery“ – FBDD) hat in den vergangenen zwei Jahrzehnten kontinuierlich an Beliebtheit gewonnen und sich zu einem dominanten Instrument der Erforschung neuer chemischer Moleküle als potentielle bioaktive Modulatoren entwickelt. FBDD ist eng mit Ansätzen zur Fragment-Erweiterung, wie etwa dem Fragment-„growing“, „merging“ oder dem „linking“, verknüpft. Diese Entwicklungsansätze können mit Hilfe von Computerprogrammen oder teilautomatischen Prozessen der „de novo“ Wirkstoffentwicklung beschleunigt werden. Obwohl Computer mühelos Millionen von Vorschlägen generieren können, geschieht dies allerdings oft auf Kosten unsicherer synthetischer Realisierbarkeit der Verbindungen mit einer potentiellen Sackgasse im Optimierungsprozess. Dieses Manuskript beschreibt die Entwicklung zweier computerbasierter Instrumente, PINGUI und SCUBIDOO, mit dem Ziel den FBDD Ausarbeitungs-Zyklus zu fördern. PINGUI ist ein halbautomatischer Arbeitsablauf zur Fragment-Erweiterung basierend auf der Proteinstruktur unter Berücksichtigung der synthetischen Umsetzbarkeit. SCUBIDOO ist eine freizugängliche Datenbank mit aktuell 21 Millionen verfügbaren virtuellen Produkten, entwickelt durch die Kombination kommerziell verfügbarer Bausteine („building blocks“) mit bewährten organischen Reaktionen. Zu jedem erzeugten virtuellen Produkt wird somit eine Synthesevorschrift geliefert. Die entscheidenden Funktionen von PINGUI, wie die Erzeugung abgeleiteter Bibliotheken oder das Anwenden organischer Reaktionen, wurden daraufhin in die SCUBIDOO Webseite integriert. PINGUI als auch SCUBIDOO wurden des Weiteren zur Erforschung Fragment-basierter Liganden („fragment-based ligand discovery“) mit dem β-2 adrenergen Rezeptor (β-2-AR) und der PIM1 Kinase als Zielproteine („targets“) eingesetzt. Im Rahmen einer ersten Studie zum β-2-AR wurden mit PINGUI acht unterschiedliche Erweiterungen für verschiedene Fragment-Treffer („hits“) vorhergesagt (ausgewählt?). Alle acht Verbindungen konnten dabei erfolgreich synthetisiert werden und vier der acht Produkte zeigten im Vergleich zu den Ausgangsfragmenten eine erhöhte Affinität zum target. Eine zweite Studie umfasste die Anwendung von SCUBIDOO zur schnellen Identifikation von Fragmenten und deren möglichen Erweiterungen mit potentieller Bindungsaktivität zur PIM-1 Kinase. Als Ergebnis ergab sich ein Fragment-Treffer mit der dazugehörigen Kristallstruktur. Weitere Folgeprodukte befinden sich derzeit in Synthese. Abschließend wurde SCUBIDOO an eine automatische Roboter- Synthese gekoppelt, wodurch hunderte von Verbindungen effizient parallel synthetisiert werden können. 127 der 240 vorhergesagten Produkte (53%) wurden mit dem Ziel an den β-2-AR zu binden bereits synthetisiert und werden in Kürze weitergehend getestet. Die beiden vorgestellten Computer-Tools könnten zur Verbesserung im Anfangsstadium befindlicher Projekte zur Fragment-basierten Wirkstoffentwicklung, vor allem hinsichtlich der Strategien im Bereich der Fragment Erweiterung, eingesetzt werden. PINGUI zum Beispiel generiert Vorschläge zur Fragment- Erweiterung, die sich mit hoher Wahrscheinlichkeit an die Zielstruktur anlagern, und stellt somit ein nützliches und kreatives Werkzeug zur Untersuchung von Struktur-Wirkungsbeziehungen („structure-activity relationship“ – SAR) dar. SCUBIDOO zeigte sich mit einem bisherigen 53-prozentigen Synthese-Erfolg als zugänglich für die Integration an die effiziente automatisierte Roboter-Synthese. Jede zukünftige Synthese liefert neue Kenntnisse innerhalb der Datenbank und wird somit nach und nach den Synthese-Erfolg erhöhen. Des Weiteren stellen alle synthetisierten Produkte neuartige Verbindungen dar, was umso mehr den möglichen Einfluss SCUBIDOOs bei der Entdeckung neuer chemischer Strukturen hervorhebt. fragment Philipps-Universität Marburg ligand doctoralThesis In the past two decades, fragment-based drug discovery (FBDD) has continuously gained popularity in drug discovery efforts and has become a dominant tool in order to explore novel chemical entities that might act as bioactive modulators. FBDD is intimately connected to fragment extension approaches, such as growing, merging or linking. These approaches can be accelerated using computational programs or semi-automated workflows for textit{de novo} design. Although computers allow for the facile generation of millions of suggestions, this often comes at a price: uncertain synthetic feasibility of the generated compounds, potentially leading to a dead end in an optimization process. In this manuscript we developed two computational tools which could support the FBDD elaboration cycle: PINGUI and SCUBIDOO. PINGUI is a semi-automated workflow for fragments growing guided by both the protein structure and synthetic feasibility. SCUBIDOO is a freely accessible database which currently holds 21 M virtual products. This database was created by combining commercially available building blocks with robust organic reactions. Thus, every virtual product comes with synthetic instructions. Most of the crucial functions of PINGUI (creation of derived libraries or applying organic reaction) were then implemented in the SCUBIDOO website. PINGUI and SCUBIDOO were then applied to fragment-based ligand discovery efforts targeting the $beta_{2}$-adrenergic receptor ($beta_{2}$AR) and the PIM1 kinase. In a first study focusing on the $beta_{2}$AR, we suggested a total of eight diverse extensions for different fragment hits using PINGUI. The eight compounds were successfully synthesized and further assays showed that four products had an improved affinity compared to their respective initial fragment. In a second study, SCUBIDOO was applied in order to quickly identify fragments and suggest extensions that could bind to PIM1. This study yielded a fragment hit and its associated crystal structure. Synthesis of derived products is in progress. Lastly, SCUBIDOO was coupled with automated robotic synthesis in order to synthesize hundreds of compounds in parallel. 127 products among the 240 suggested were synthesized (53%). Those compounds were designed so they are likely to bind to the $beta_{2}$AR and will be tested in the near future. The aforementioned computational tools could improve early fragment-based drug discovery projects, especially in the realm of fragment growing strategies. For instance, PINGUI suggests extensions that are very likely to be attachable, making it a useful creative tool for medicinal chemists during structure-activity relationship (SAR) studies. With so far 53% success synthesis rate, SCUBIDOO has shown that it is amenable to be integrated to automated robotic synthesis. Every synthesis attempt is prone to improve the knowledge contained within the database and thus increase the synthesis success rate over time. Furthermore, all synthesized product were novel compounds, thus demonstrating how SCUBIDOO could explore new quadrants of the chemical space.​ Improved approaches to ligand growing through fragment docking and fragment-based library design Fragment ths Dr. Kolb Peter Kolb, Peter (Dr.) https://doi.org/10.17192/z2016.0809 2016 215 application/pdf urn:nbn:de:hebis:04-z2016-08097