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Combining computational and experimental screening for rapid optimization of protein properties
Robert J Hayes1, Jorg Bentzien, Marie L Ary
1Xencor, 111 West Lemon Avenue, Monrovia, CA 91016, USA.
Summary
We developed a fast protein engineering method using computational screening and experimental testing. This approach rapidly created novel beta-lactamase variants with significantly increased antibiotic resistance.
Area of Science:
- Protein engineering
- Computational biology
- Biotechnology
Background:
- Beta-lactamase enzymes are crucial targets for antibiotic resistance research.
- Optimizing protein function requires efficient methods to explore vast sequence spaces.
Purpose of the Study:
- To develop a rapid, combined computational and experimental approach for protein optimization.
- To engineer beta-lactamase variants with enhanced resistance to cefotaxime.
Main Methods:
- Utilized Protein Design Automation (PDA) for computational screening of protein sequences.
- Generated a library of ~200,000 beta-lactamase mutants.
- Experimentally screened mutants for increased cefotaxime resistance.
Main Results:
- Achieved a 1,280-fold increase in cefotaxime resistance in a single round of optimization.
- Identified novel mutations not previously reported through random mutagenesis or found in natural TEM beta-lactamases.
- Demonstrated the efficacy of the combined computational-experimental strategy.
Conclusions:
- The Protein Design Automation technology significantly accelerates protein engineering.
- This method provides a powerful and broadly applicable tool for improving protein properties.
- Enables rapid development of enzymes with enhanced functionalities for various applications.