Library analysis of SCHEMA-guided protein recombination

Area of Science:

• Protein engineering and computational biology.
• Enzyme function and structure-function relationships.

Background:

• Recombination can disrupt protein structure and function by altering interacting amino acid residues.
• Predicting the functional impact of recombination is crucial for protein design.

Purpose of the Study:

• To evaluate the predictive accuracy of the SCHEMA computational algorithm for estimating disruption caused by recombination.
• To determine if SCHEMA can guide the creation of functional protein chimeras.

Main Methods:

• Developed the SCHEMA computational algorithm to quantify disruption based on broken residue-residue contacts.
• Created a library of 16,384 protein chimeras by shuffling two distantly related beta-lactamases (PSE-4 and TEM-1) at 13 sites.
• Assessed chimera function by selecting for retained lactamase activity after gene sequencing.

Main Results:

• The percentage of functional chimeras decreased exponentially with increasing calculated disruption (E).
• Chimeras with low E values showed a higher probability of retaining function compared to random selections.
• SCHEMA effectively predicted which chimera sequences were most likely to maintain protein function.

Conclusions:

• The SCHEMA algorithm's simple distance metric accurately predicts functional outcomes of protein recombination.
• This approach can optimize crossover site selection for creating stable, mosaic proteins.
• SCHEMA facilitates the design of novel, functional protein chimeras.