Using Evolution to Guide Protein Engineering: The Devil IS in the Details.

Area of Science:

• Biophysics
• Protein Engineering
• Evolutionary Biology

Background:

• Protein engineering aims to create novel protein functions by modifying existing proteins.
• Domain recombination allows transfer of protein folds and gross functions, but fine-tuning specific functions remains difficult.
• Evolutionary sequence analysis identifies nonconserved amino acids for targeted mutations to optimize protein function.

Purpose of the Study:

• To review complexities in using evolutionary data for predictable protein function fine-tuning.
• To identify challenges hindering the replication of natural protein functional performance in engineered proteins.
• To propose new goals for future protein design studies.

Main Methods:

• Review of evolutionary and experimental studies on protein function.
• Analysis of complexities in identifying functionally important amino acid positions.
• Examination of epistasis and the contribution of multiple amino acids to protein function.

Main Results:

• Predictably fine-tuning protein function (e.g., ligand affinity, specificity, catalysis) is challenging.
• Evolutionary approaches often fail to engineer proteins matching natural functional performance.
• Complexities include defining amino acid importance, diverse evolutionary patterns, mapping changes to function, nonconventional mutations, epistasis, and widespread amino acid contribution.

Conclusions:

• Significant hurdles exist in predictably engineering protein function using evolutionary insights.
• A deeper understanding of protein biophysics and evolutionary constraints is necessary.
• Future research should focus on addressing these complexities to advance protein design capabilities.