Combinatorial Approach for Exploring Conformational Space and Activation Barriers in Computer-Aided Enzyme Design

Area of Science:

• Biochemistry and Molecular Biology
• Computational Biology
• Protein Engineering

Background:

• Computer-aided enzyme design holds significant potential for biotechnology and medicine.
• Predicting enzyme activation barriers and mutation effects remains a major challenge.
• Accurate computational methods are crucial for advancing enzyme engineering.

Purpose of the Study:

• To develop and validate a computational protocol for predicting mutant protein structures and their activation barriers.
• To assess the reliability of *in silico* directed evolution for enzyme optimization.
• To explore the effects of multiple mutations on enzyme catalytic power.

Main Methods:

• A protocol for predicting initial mutant structures and calculating activation barriers.
• Iterative application of the protocol for subsequent mutations.
• Application to Kemp eliminase and haloalkane dehalogenase for *in silico* directed evolution.

Main Results:

• The protocol successfully predicts reasonable starting structures for enzyme mutants.
• Activation barriers for generated mutants were calculated, enabling assessment of catalytic power.
• The approach was validated using Kemp eliminase and haloalkane dehalogenase.

Conclusions:

• The proposed computational protocol is effective for enzyme design and predicting mutation effects.
• This strategy facilitates the creation of an 'activity funnel' for ranking mutant catalytic efficiency.
• The method supports *in silico* directed evolution for developing enhanced biocatalysts.