Co-evolution of interacting proteins through non-contacting and non-specific mutations

Area of Science:

• Molecular Biology
• Evolutionary Biology
• Protein Engineering

Background:

• Proteins accumulate neutral mutations, altering future evolutionary potential.
• Understanding these mutations is key for protein design and evolutionary prediction.
• Systematic identification of potentiating mutations remains a challenge.

Purpose of the Study:

• To identify single substitutions in bacterial toxins that tolerate antitoxin mutations.
• To explore the impact of these mutations on future evolutionary pathways.
• To assess the efficacy of current methods in identifying such mutations.

Main Methods:

• Comprehensive analysis of a bacterial toxin-antitoxin system.
• Identification of all single substitutions in the toxin.
• Evaluation of tolerance to antitoxin mutations.
• Comparison with covariation and machine learning methods.

Main Results:

• Identified toxin mutations enabling tolerance to diverse antitoxin mutations.
• Found that enabling mutations often do not contact the interface directly.
• Demonstrated that these mutations expand future mutational paths, maintaining and creating new interactions.
• Showed these non-specific mutations are missed by standard covariation and machine learning approaches.

Conclusions:

• Non-specific enabling mutations play a crucial role in protein evolution.
• These mutations offer a broader scope for future functional diversification than specific compensatory mutations.
• Identifying such mutations is vital for protein design and therapeutic applications involving evolving targets.