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Evaluation and ranking of enzyme designs
Gert Kiss1, Daniela Röthlisberger, David Baker
1Department of Chemistry and Biochemistry, University of California, Los Angeles, California 90095, USA.
Protein Science : a Publication of the Protein Society
|July 29, 2010
Summary
Computational enzyme design can now be refined using molecular dynamics (MD) simulations. This approach identifies inactive enzyme designs by pinpointing issues like water penetration and poor residue packing, improving catalyst development efficiency.
Area of Science:
- Biochemistry
- Computational Biology
- Enzyme Engineering
Background:
- A 2008 study reported successful computational design of active Kemp elimination enzyme catalysts.
- Evaluating designed enzymes computationally was previously too time-intensive for practical application.
Purpose of the Study:
- Investigate sources of activity and inactivity in designed Kemp elimination enzymes.
- Predict catalytic potential of designed enzyme structures.
- Establish an efficient computational protocol for enzyme design refinement.
Main Methods:
- Explored quantum mechanics (QM) on model systems.
- Utilized ONIOM QM/MM and AMBER molecular dynamics (MD) for full protein analysis.
- Established a general MD protocol for evaluating enzyme designs.
Main Results:
- Observed significant deviations from ideal catalytic geometries in several designs.
- Identified water penetration into the catalytic site as a cause of inactivity.
- Found insufficient residue packing around the active site to be a key factor in inactivity.
Conclusions:
- Molecular dynamics simulations are effective for evaluating designed enzymes.
- Computational methods can now efficiently rank and refine enzyme candidates.
- This enhances the overall efficiency of the enzyme design process.
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