Synthesis cost-optimal targeted mutant protein libraries.

Area of Science:

• Biochemistry
• Molecular Biology
• Bioinformatics

Background:

• Protein variant libraries are crucial for protein engineering, aiding in the discovery of improved protein activity and stability.
• Current methods using site-directed mutagenesis and degenerate codons often introduce unwanted amino acids or STOP codons, reducing library efficiency.

Purpose of the Study:

• To develop a novel computational approach for synthesizing targeted protein variant libraries with a higher yield of beneficial mutations.
• To minimize the cost and complexity of producing diverse protein libraries by avoiding unwanted variants.

Main Methods:

• Developed an algorithm to determine the minimum number of degenerate codons required for specific amino acid sets.
• Implemented a dynamic programming method to optimally partition DNA sequences into overlapping oligonucleotides for synthesis.
• Utilized annealing-based recombination of oligonucleotides during synthesis to create targeted libraries.

Main Results:

• Achieved orders of magnitude increase in beneficial variant yields within produced mutant libraries.
• Demonstrated that this method is particularly effective for large combinatorial libraries.
• Showcased a modest increase in DNA synthesis costs leading to significantly improved library outcomes.

Conclusions:

• The developed computational strategy enables the efficient production of targeted protein libraries.
• This approach enhances the discovery of proteins with improved properties by maximizing beneficial variant representation.
• Optimized oligonucleotide synthesis strategies can overcome limitations of traditional mutagenesis techniques.