Degenerate codon design (DeCoDe)

Degenerate codon design (DeCoDe) optimizes degenerate codon (DC) libraries to maximize targeted protein-sequence diversity while minimizing nonfunctional variants and library size for high-throughput protein screening.

Key Features:

• Optimization Algorithm: Employs a novel algorithm based on integer linear programming to optimize DC library design and handle complex covariation patterns across multiple proteins.
• Scalability: Scales to accommodate more than a hundred proteins with intricate covariation patterns, exemplified by the lab-derived avGFP lineage.
• Mixed-Length Library Encoding: Supports encoding mixed-length protein libraries, representing the first DC design algorithm with this capability.
• Variant Minimization: Minimizes generation of undesired or nonfunctional variants to reduce screening burden and molecular cost.

Scientific Applications:

• Protein Engineering: Leverages mutual information to design mutagenic libraries that target functional sequence space for engineering desired protein properties.
• Ancestral Protein Reconstruction: Aids reconstruction of ancestral protein states to investigate evolutionary processes and functional adaptations.
• High-Throughput Screening: Enables construction of diverse protein variant pools required for high-throughput screening assays.

Methodology:

Optimizes selection of degenerate codons for sequences with multiple covarying positions using integer linear programming, implemented and solved with Gurobi via the gurobipy Python interface.