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Updated: Jul 31, 2025
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Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues
Published on: July 14, 2015
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Evolutionary paths that link orthogonal pairs of binding proteins
Ziv Avizemer1, Carlos Martí-Gómez2, Shlomo Yakir Hoch1
1Department of Biomolecular Sciences, Weizmann Institute of Science, 7610001, Rehovot, Israel.
Research Square
|May 3, 2023
Summary
This study reveals how protein binding specificities evolve through gradual mutations. A new computational framework identified a viable 19-mutation path, showing that functional divergence can be driven by positive selection.
Area of Science:
- Evolutionary biology
- Biochemistry
- Computational biology
Background:
- Protein binding pairs with extreme specificity are insulated from homologs.
- Evolution of new specificity while maintaining function is an evolutionary conundrum.
- Previous studies could only enumerate intermediates for mutationally close pairs.
Purpose of the Study:
- Develop a framework to discover low molecular strain single-mutation paths between extant protein pairs.
- Investigate the evolutionary path of two orthogonal bacterial colicin endonuclease-immunity pairs.
- Understand how functional divergence evolves in protein binding specificities.
Main Methods:
- Developed an atomistic and graph-theoretical framework.
- Applied the framework to bacterial colicin endonuclease-immunity pairs.
- Utilized experimental validation for identified mutation trajectories.
Main Results:
- Identified a strain-free 19-mutation trajectory connecting two orthogonal pairs, including non-single-nucleotide exchangeable amino acids.
- Demonstrated that the specificity switch is abrupt, driven by radical mutations.
- Showed that critical mutations increase fitness, supporting positive Darwinian selection.
Conclusions:
- Radical functional changes in protein binding can evolve through viable evolutionary paths.
- Positive Darwinian selection can drive functional divergence even in complex fitness landscapes.
- The developed framework enables enumeration of evolutionary paths beyond experimental capabilities.
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