Exposing the co-adaptive potential of protein-protein interfaces through computational sequence design

Area of Science:

• Evolutionary biology
• Structural biology
• Computational biology

Background:

• Protein-protein interactions are vital and evolve under selective pressures.
• Compensatory mutations maintain crucial interactions, but sequence covariance is confounded by factors like common ancestry.
• Distinguishing evolutionary signals from physical interactions is challenging.

Purpose of the Study:

• To isolate compensatory mutations arising specifically from physical protein interactions.
• To compare the co-adaptability potential of obligate versus transient protein complexes.
• To investigate the role of protein-protein interface dynamics in evolutionary adaptation.

Main Methods:

• Large-scale computational mutagenesis experiments on over 260 protein-protein interfaces.
• Modeling protein complexes in both bound and unbound states.
• Analyzing correlated mutation patterns in obligate and transient protein pairs.

Main Results:

• Transient protein complexes exhibit a higher relative capacity for correlated mutation compared to obligate complexes.
• This finding holds true even after controlling for differences in interface size.
• Computational mutagenesis effectively differentiates evolutionary signals of physical interaction.

Conclusions:

• Transient protein interactions may possess greater inherent evolutionary flexibility.
• Understanding co-adaptability in protein complexes can inform drug design and protein engineering.
• Computational approaches are valuable for dissecting evolutionary mechanisms in protein interactions.