Genetic Algorithm Based Design and Experimental Characterization of a Highly Thermostable Metalloprotein

The development of thermostable and solvent-tolerant metalloproteins is a long-sought goal for many applications in synthetic biology and biotechnology. In this work, we were able to engineer a highly thermostable and organic solvent-stable metallo variant of the B1 domain of protein G (GB1) with a...

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Published in:Journal of the American Chemical Society 2018-04, Vol.140 (13), p.4517-4521
Main Authors: Bozkurt, Esra, Perez, Marta A. S, Hovius, Ruud, Browning, Nicholas J, Rothlisberger, Ursula
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cited_by cdi_FETCH-LOGICAL-a324t-8b8f2e1aeddbb47900a823dd74ca0bdbef47c817a2b4b7c6c3b80c99a4a2a97d3
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container_issue 13
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container_title Journal of the American Chemical Society
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creator Bozkurt, Esra
Perez, Marta A. S
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Rothlisberger, Ursula
description The development of thermostable and solvent-tolerant metalloproteins is a long-sought goal for many applications in synthetic biology and biotechnology. In this work, we were able to engineer a highly thermostable and organic solvent-stable metallo variant of the B1 domain of protein G (GB1) with a tetrahedral zinc binding site reminiscent of the one of thermolysin. Promising candidates were designed computationally by applying a protocol based on classical and first-principles molecular dynamics simulations in combination with genetic algorithm optimization. The most promising of the computationally predicted mutants was expressed and structurally characterized and yielded a highly thermostable protein. The experimental results thus confirm the predictive power of the applied computational protein engineering approach for the de novo design of highly stable metalloproteins.
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title Genetic Algorithm Based Design and Experimental Characterization of a Highly Thermostable Metalloprotein
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