4.8 Article

Enzyme-Polyelectrolyte Complexes Boost the Catalytic Performance of Enzymes

Journal

ACS CATALYSIS
Volume 8, Issue 11, Pages 10876-10887

Publisher

AMER CHEMICAL SOC
DOI: 10.1021/acscatal.8b02935

Keywords

protease; protein engineering; directed evolution; polyelectrolytes; enzyme-polyelectrolyte complexes (EPCs); poly(acrylic acid) (PAA) and poly(L-gamma-glutamic acid) (gamma-PGA); molecular dynamics simulations

Funding

  1. Henkel AG & Co. KGaA, Dusseldorf, Germany
  2. RWTH Aachen University [RWTH0116, JARA0169]

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Understanding interactions between polymers and enzymes to boost enzymatic activity is of high importance for application of enzymes in multicomponent systems, such as laundry, food, pharmaceuticals, or cosmetics. Proteases are widely used in industries and increased performance in the presence of polymers has been reported. Boosting of enzymes activity by polymers and understanding of the molecular principles is of high interest in biomedical and biotechnological applications. A molecular understanding of the boosting effect of poly(acrylic acid) (PAA) and poly(L-gamma-glutamic acid) (gamma-PGA) for a nonspecific subtilisin protease (Protein Database (PDB) ID: 1ST3) was generated through biophysical characterization (fluorescence correlation and circular dichroism spectroscopies, isothermal titration calorimetry), molecular dynamics simulations, and protease reengineering (site-saturation mutagenesis). Our study revealed that enthalpically driven interactions via key amino acid residues close to the protease Ca2+ binding sites cause the boosting effect in protease activity. On the molecular level electrostatic interactions results in the formation of protease-polyelectrolyte complexes. Site-saturation mutagenesis on positions S76, 177, A188, V238, N242, and K245 yielded an increased proteolytic performance against a complex protein mixture (trademark CO-3; up to similar to 300% and similar to 70%) in the presence of PAA and gamma-PGA. Being able to fine-tune interactions between proteins and negatively charged polymers through integrative use of computational design, protein re-engineering and biophysical characterization proved to be an efficient workflow to improve protease performance.

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