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Genome sequencing projects have led to the identification of an enormous number of open reading frames that code for unknown proteins. Elucidation of the structure and function of these proteins makes it necessary to produce proteins fast, in high yields and at low cost. Hence, bacterial expression systems, as E.coli, represent an ideal tool. However, many proteins show problems with solubility if expressed in E. coli resulting in the formation of large, inactive cytosolic aggregates, so called inclusion bodies. A study on the human genome for example estimated the fraction of soluble, expressible proteins only to be 13 %.

To gain their biological functions, inclusion body forming proteins have to be refolded. This step still represents a major challenge for many recombinantly expressed proteins and often constitutes a major bottleneck. As in vitro refolding is a complex reaction with a variety of critical parameters, suitable refolding conditions are typically derived empirically in extensive screening experiments. Thus, it is necessary to establish efficient refolding protocols yielding functional protein for subsequent analysis. Protein folding as a downstream process step remains challenging, because a multi-parameter space has to be explored in an empiric manner.

The goal of this interdisciplinary project is to establish stochastic search strategies (genetic algorithms) for the efficient experimental optimization of the renaturation conditions of proteins. The setup of this new strategy that combines screening and optimization of refolding yields is designed to achieve a robust method which allows the refolding optimization of a variety of proteins in an automated procedure guided by the genetic algorithm.

The experimental data obtained from the renaturation of structurally different proteins will be the basis for the optimization and the modeling of the coherence of renaturation conditions and refolding yields with the help of artificial neuronal networks. The validated models will be further used to deduce connections between in databases available, global protein parameters (e.g. number of amino acids and composition, isoelectric point, hydrophobicity, etc.) and effective refolding conditions.  To establish a method allowing the prediction of effective refolding conditions on the basis of theoretical ab initio parameters or on a small set of experiments allowing trend- or optimization predictions would be a milestone in the field of protein production in microorganisms.

 

01-01-1970
IGSSE setup of interdisciplinary research in project teams
16.05.17

Apply now: 12th call for proposals

IGSSE supports up to 10 new project teams

Call closes 2 July 2017

11.06.17

Apply now: IGSSE travel grant for ICCE 2017

28-29 September 2017, TU Darmstadt

Submission deadline for abstracts: 18 June 2017

08.06.17

IGSSE Forum 2017

29-31 May 2017, TUM Science and Study Center Raitenhaslach, Burghausen

14.05.17

Climate-KIC: Join the PhD Catapult

Two-week thematic summer schools across Europe

04.05.17

IAS Symposium: Selected topics in science and technology

8-10 May 2017, IAS Building, Garching Campus

02.05.17

IAS Coffee Talk with PTL Florian Praetorius

3 May 2017, 1 pm, TUM IAS Building, Garching Campus

23.02.16

10th IGSSE Forum

1 - 4 June 2016, TUM Science and Study Center, Burghausen

05.06.16

10th IGSSE Forum

Smart cooperation - science and technology in, with and for society

15.12.15

The Science of Cooking

Doctoral Candidates explore the Secrets of a great Dinner

26.11.15

ATUMS@IGSSE

Having heard of a great Canadian Kick-Off Meeting, everyone at IGSSE was thrilled to welcome the...

20.11.15

Breakfast at IGSSE´s

Meet the IGSSE team every other month! All the things IGSSE members wanted to asked but never dared...

13.10.15

Save the Date: Canadian ATUMS Speaker on "Global Science- Global Career"

26. November 2015, 6-8 pm, IAS Faculty Club, Garching Campus

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Friday, 09. June 2017
Workshop: Standing up for science
9 June 2017, 9am-4pm, Brussels
Apply now: McKinsey 'Forschergeist' symposium
9-11 June 2017, Berlin For doctoral researchers and postdocs!