Experimental optimization of protein refolding with a genetic algorithm

Authors

  • Bernd Anselment,

    1. Lehrstuhl für Bioverfahrenstechnik, Technische Universität München, Boltzmannstr. 15, D-85748 Garching, Germany
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  • Danae Baerend,

    1. Department Chemie and Center for Integrated Protein Science Munich (CIPSM), Technische Universität München, D-85748 Garching, Germany
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  • Elisabeth Mey,

    1. Department Chemie and Center for Integrated Protein Science Munich (CIPSM), Technische Universität München, D-85748 Garching, Germany
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  • Johannes Buchner,

    1. Department Chemie and Center for Integrated Protein Science Munich (CIPSM), Technische Universität München, D-85748 Garching, Germany
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  • Dirk Weuster-Botz,

    1. Lehrstuhl für Bioverfahrenstechnik, Technische Universität München, Boltzmannstr. 15, D-85748 Garching, Germany
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  • Martin Haslbeck

    Corresponding author
    1. Department Chemie and Center for Integrated Protein Science Munich (CIPSM), Technische Universität München, D-85748 Garching, Germany
    • Lehrstuhl für Biotechnologie, Department Chemie, Technische Universität München, D-85748 Garching, Germany

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Abstract

Refolding of proteins from solubilized inclusion bodies 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. Here, we introduce a new strategy that combines screening and optimization of refolding yields with a genetic algorithm (GA). The experimental setup was designed to achieve a robust and universal method that should allow optimizing the folding of a variety of proteins with the same routine procedure guided by the GA. In the screen, we incorporated a large number of common refolding additives and conditions. Using this design, the refolding of four structurally and functionally different model proteins was optimized experimentally, achieving 74–100% refolding yield for all of them. Interestingly, our results show that this new strategy provides optimum conditions not only for refolding but also for the activity of the native enzyme. It is designed to be generally applicable and seems to be eligible for all enzymes.

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