A 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 applica- tions in synthetic biology and biotechnology. In this work, we were able to engineer a highly thermo- 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-princi- ples molecular dynamics simulations in combination with genetic algorithm (GA) 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.
2018
140
13
4517
4521
REVIEWED