Interface Engineering of Carrier-Protein-Dependent Metabolic Pathways

Area of Science:

• Metabolic Engineering
• Synthetic Biology
• Biochemistry

Background:

• Carrier-protein-dependent pathways synthesize crucial metabolites like fatty acids and peptides.
• Protein-protein interactions (PPIs) regulate enzyme activity and timing within these pathways.
• Designing and modifying PPIs is challenging due to complex protein interfaces.

Purpose of the Study:

• To improve computational methods for designing and engineering PPIs in metabolic pathways.
• To develop a more predictive computational protocol for identifying functional PPIs.
• To create a novel hybrid pathway for fatty acid and non-ribosomal peptide synthesis.

Main Methods:

• Iterative computational prediction and mutagenesis using an improved Rosetta score function.
• Increased weight of the electrostatic score term in the computational protocol.
• Experimental validation of designed PPIs through in vitro activity and structural studies.

Main Results:

• The enhanced computational protocol required fewer iterations to identify active mutants.
• Successfully designed novel PPIs between a non-ribosomal peptide synthetase (PltF) and an acyl carrier protein (AcpP).
• Validated the designed PPIs through biochemical assays and structural analysis.

Conclusions:

• Optimizing the electrostatic term in scoring functions enhances PPI prediction accuracy.
• This method provides a robust platform for customized metabolic pathway design.
• Establishes a new standard for engineering carrier-protein-dependent pathways via PPI optimization.