Simultaneous enhancement of multiple functional properties using evolution-informed protein design

Area of Science:

• Biochemistry and Molecular Biology
• Protein Engineering
• Computational Biology

Background:

• Optimized protein design is crucial for diverse applications.
• Current methods often focus on limited mutations, hindering extensive sequence modification.
• Evolutionary models of sequence co-variation offer a promising avenue for exploring protein diversity.

Approach:

• Applied the EVcouplings evolutionary model to design variants of TEM-1 β-lactamase.
• Generated computationally designed, highly divergent protein sequences.
• Experimentally characterized designed variants using biochemical and biophysical assays.

Key Points:

• Designed variants exhibited high functionality, even with extensive mutations (up to 84).
• Functional designs showed significant increases in thermostability and broadened substrate specificity.
• Protein structure remained largely unchanged compared to the wild-type enzyme.

Conclusions:

• Evolutionary co-variation models capture complex epistasis, enabling substantial sequence divergence.
• These models are effective tools for generating functional protein diversity for various applications.
• This approach advances the field of protein design by facilitating large-scale sequence optimization.