modeFRONTIER Application in Biotechnology - Unbiased Guidelines for Driving Rational Enzyme Evolution
CHALLENGE - Enzymes are key to biotechnology application due to their natural ability to accelerate chemical reaction rates, stay active in mild conditions, limit generation of waste and side product formation amoung other chemical properties. They are formed by a sequence of amino acids (usually from 200 to more than 400) and present limits in their stability, substrate specificity and yields of production. Researchers must improve the efficiency of the biocatalyst to make them available for industrial use.
SOLUTION - Researchers selected 5 hot-spots for the driven evolution to identify the most stable configuration for a rarely used enzyme, the amidases, and served as input to the modeFRONTIER workflow which automatised the mutant generation stimulated by specific tools (PyMol, GROMACS, and GRID). A scoring function integrating an empirical approach was used to maximize the predictive capability and control the engineered enzyme performance.
BENEFITS - modeFRONTIER’s selection of genetic algorithms empowered researchers to mimic natural evolution. Additionally, researchers were able to streamline in a single workflow while using different analysis tools, thus integrating the screening modeling and experimental-statistical capability of each. This provided valuable insight when checking the quality of the engineered enzymes.