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Updated: Feb 21, 2026

Author Spotlight: A Computational Approach to Decipher Amino Acid Preferences in Multispecific Protein-Protein Interactions
Published on: January 26, 2024
Protein-protein interactions leave evolutionary footprints: High molecular coevolution at the core of interfaces
Elin Teppa1, Diego Javier Zea1, Cristina Marino-Buslje1
1Bioinformatics Unit, Fundación Instituto Leloir/IIBBA CONICET, Avda. Patricias Argentinas 435, CABA, Argentina.
Abstract:
Protein-protein interactions are essential to all aspects of life. Specific interactions result from evolutionary pressure at the interacting interfaces of partner proteins. However, evolutionary pressure is not homogeneous within the interface: for instance, each residue does not contribute equally to the binding energy of the complex. To understand functional differences between residues within the interface, we analyzed their properties in the core and rim regions. Here, we characterized protein interfaces with two evolutionary measures, conservation and coevolution, using a comprehensive dataset of 896 protein complexes. These scores can detect different selection pressures at a given position in a multiple sequence alignment. We also analyzed how the number of interactions in which a residue is involved influences those evolutionary signals. We found that the coevolutionary signal is higher in the interface core than in the interface rim region. Additionally, the difference in coevolution between core and rim regions is comparable to the known difference in conservation between those regions. Considering proteins with multiple interactions, we found that conservation and coevolution increase with the number of different interfaces in which a residue is involved, suggesting that more constraints (i.e., a residue that must satisfy a greater number of interactions) allow fewer sequence changes at those positions, resulting in higher conservation and coevolution values. These findings shed light on the evolution of protein interfaces and provide information useful for identifying protein interfaces and predicting protein-protein interactions.
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