Computational Design and Optimization of G-CSFR Modulators

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dc.contributor.advisor Lupas, Andrei (Prof. Dr.)
dc.contributor.author Ullrich, Timo
dc.date.accessioned 2024-02-23T10:59:30Z
dc.date.available 2024-02-23T10:59:30Z
dc.date.issued 2026-01-30
dc.identifier.uri http://hdl.handle.net/10900/151271
dc.identifier.uri http://nbn-resolving.de/urn:nbn:de:bsz:21-dspace-1512715 de_DE
dc.identifier.uri http://dx.doi.org/10.15496/publikation-92611
dc.description.abstract Considering the indispensable role played by proteins in maintaining vital life processes, it is not surprising that proteins are linked to a broad spectrum of diseases. Conversely, proteins can be leveraged for effective therapeutic interventions. For example, secreted growth factors known as cytokines have emerged as promising candidates for protein-based therapeutics, primarily due to their potent immunomodulatory properties. An integral element of the innate immune system consists of neutrophils, the maturation of which is coordinated by a hematopoietic subprocess known as granulopoiesis. This process requires a complex interplay among various cytokines and their corresponding receptor molecules. A critical player in these interactions is the granulocyte-colony stimulating factor receptor (G-CSFR), which is activated by its native ligand, G-CSF. Unlike most other cytokines, G-CSF has found clinical use in its native form due to its favorable safety profile and its ability to increase the number of neutrophils in the blood. However, G-CSF application is restricted by its stability, production cost and native activity on G-CSFR. Additionally, there is very limited knowledge regarding non-native G-CSFR modulators, which could be key not only for understanding G-CSFR related diseases, but also for the development of innovative therapeutic applications. In order to unlock the untapped potential of the clinically significant G-CSFR beyond its native activity, my objective was to employ protein design techniques to craft novel ligands capable of modulating G-CSFR activity. In addition to customizing receptor activity, these designs offer enhanced stability and more efficient production compared to their native counterpart G-CSF. To this end, I utilized a recently developed hyper-thermostable de novo designed GCSFR binding module and optimized it with in silico and in vitro high-throughput methods to obtain a broad spectrum of variants with enhanced binding affinity. I demonstrate that these enhanced binding modules can be utilized to generate GCSFR agonists that achieve G-CSF activity in cell-based assays and can also be used to create ligands capable of modulating G-CSFR activity by tuning receptor geometry. These ligands featured fine-tuned intracellular signaling, transcriptomic activity, and primary stem cell differentiation and exhibit in vivo activity in zebrafish and mouse models. In addition to designing agonists, I show that these enhanced binding modules can be used to generate competitive G-CSFR antagonists with nanomolar inhibitory activity. To the best of my knowledge this work is the first demonstration that G-CSFR activity can be tuned by the design of ligands inducing non-native receptor geometries. Additionally, this study presents an array of binding modules with diverse affinities to G-CSFR, along with the newly designed ligands, providing the foundational components for systematic investigation of G-CSFR activity modulation. These findings hold significant promise for advancing the development of innovative protein therapeutics. en
dc.description.abstract Die Dissertation ist gesperrt bis zum 30. Januar 2026 ! de_DE
dc.language.iso en de_DE
dc.publisher Universität Tübingen de_DE
dc.rights ubt-podok de_DE
dc.rights.uri http://tobias-lib.uni-tuebingen.de/doku/lic_mit_pod.php?la=de de_DE
dc.rights.uri http://tobias-lib.uni-tuebingen.de/doku/lic_mit_pod.php?la=en en
dc.subject.ddc 570 de_DE
dc.title Computational Design and Optimization of G-CSFR Modulators en
dc.type PhDThesis de_DE
dcterms.dateAccepted 2024-02-01
utue.publikation.fachbereich Biologie de_DE
utue.publikation.fakultaet 7 Mathematisch-Naturwissenschaftliche Fakultät de_DE
utue.publikation.noppn yes de_DE

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