Biomedical research requires to a growing extent the analysis of three-dimensional structures of relevant target proteins (e.g., for understanding important pathomechanisms, the development of specific small molecule inhibitors or antibody-based therapeutics). The structural characterization of such target proteins is to a large extent performed by X-ray crystallographic analysis of protein crystals. One of the main bottlenecks of such a structural characterization is the growth of suitable protein crystals and therefore the control and optimization of crystallization conditions is key to success. Such optimization is usually based on an analysis of high throughput crystallization approaches using an automated imaging system, allowing for the tracing of crystallization progress to render the protein crystallization step as efficient as possible. We therefore plan to install such an imaging system at the Institute of Biochemistry of the University of Lübeck.Conventional imaging systems typically focus on the analysis of crystal growth by various means (e.g., white light, ultraviolet) to detect even difficult to visualize crystals (e.g., microcrystals or small membrane protein crystals in lipidic cubic phase). In contrast, the proposed system offers a dynamic light scattering module, which facilitates to monitor also the monodispersity of a protein solution - and thus indirectly protein stability - as a function of different buffer conditions. This analysis requires only minimal amounts of the protein (~50 nl) and thus constitutes a cheap and useful add-on to any high-throughput crystallization strategy. Initial experiments using this method revealed that such an optimization significantly reduces the number of high-throughput crystallization experiments required for the actual protein crystallization and thus the crystallization process becomes more efficient. In addition, the dynamic light scattering module allows accurate kinetic analysis of nucleation and crystal growth under a variety of conditions, thus providing an additional important parameter for crystallization optimization. Overall, the requested device will thus lead to a significantly more efficient use of the recombinant protein by targeted optimization of both buffer and crystallization conditions and thus an increased efficiency of protein crystallization.
|Effective start/end date||01.01.20 → …|
UN Sustainable Development Goals
In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This project contributes towards the following SDG(s):
Research Areas and Centers
- Academic Focus: Center for Infection and Inflammation Research (ZIEL)
DFG Research Classification Scheme
- 204-05 Immunology
- 204-04 Virology
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