The genetic architecture of protein interaction affinity and specificity

The encoding and evolution of specificity and affinity in protein-protein interactions is poorly understood. Here, we address this question by quantifying how all mutations in one protein, JUN, alter binding to all other members of a protein family, the 54 human basic leucine zipper transcription factors. We fit a global thermodynamic model to the data to reveal that most affinity changing mutations equally affect JUN's affinity to all its interaction partners. Mutations that alter binding specificity are relatively rare but distributed throughout the interaction interface. Specificity is determined both by features that promote on-target interactions and by those that prevent off-target interactions. Approximately half of the specificity-defining residues in JUN contribute both to promoting on-target binding and preventing off-target binding. Nearly all specificity-altering mutations in the interaction interface are pleiotropic, also altering affinity to all partners. In contrast, mutations outside the interface can tune global affinity without affecting specificity. Our results reveal the distributed encoding of specificity and affinity in an interaction interface and how coiled-coils provide an elegant solution to the challenge of optimizing both specificity and affinity in a large protein family.

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Publication Details

Journal
Nature Communications
Published
2024-10-14
DOI
https://doi.org/10.1038/s41467-024-53195-4
Citations
19
Primary Topic
Bioinformatics and Genomic Networks
Type
article
Field-Weighted Citation Impact
4.44

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article

The genetic architecture of protein interaction affinity and specificity

Dominique Klein, Kenji Shimada, André J. Faure, Simone Cavadini et al.
19 citations
Nature Communications
Bioinformatics and Genomic Networks
4.44
article

The genetic architecture of protein interaction affinity and specificity

Dominique Klein, Kenji Shimada, André J. Faure, Simone Cavadini, Alexandra M. Bendel, Georg Kempf, Guillaume Diss, Ben Lehner, Romane Lyautey, Nicole Schiffelholz
article en
19 citations

Abstract

The encoding and evolution of specificity and affinity in protein-protein interactions is poorly understood. Here, we address this question by quantifying how all mutations in one protein, JUN, alter binding to all other members of a protein family, the 54 human basic leucine zipper transcription factors. We fit a global thermodynamic model to the data to reveal that most affinity changing mutations equally affect JUN's affinity to all its interaction partners. Mutations that alter binding specificity are relatively rare but distributed throughout the interaction interface. Specificity is determined both by features that promote on-target interactions and by those that prevent off-target interactions. Approximately half of the specificity-defining residues in JUN contribute both to promoting on-target binding and preventing off-target binding. Nearly all specificity-altering mutations in the interaction interface are pleiotropic, also altering affinity to all partners. In contrast, mutations outside the interface can tune global affinity without affecting specificity. Our results reveal the distributed encoding of specificity and affinity in an interaction interface and how coiled-coils provide an elegant solution to the challenge of optimizing both specificity and affinity in a large protein family.

Nature CommunicationsVol. 15(1)
Institució Catalana de Recerca i Estudis Avançats (ES), Universitat Pompeu Fabra (ES), University of Basel (CH), Barcelona Biomedical Research Park (ES), Wellcome Sanger Institute (GB), Friedrich Miescher Institute (CH), Centre for Genomic Regulation (ES), École Polytechnique Fédérale de Lausanne (CH), Friedrich Miescher Institute (CH)
Centres de Recerca de Catalunya, European Commission, Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung, AXA Research Fund, Generalitat de Catalunya, Ministerio de Ciencia e Innovación, Fondation Bettencourt Schueller, Agència de Gestió d'Ajuts Universitaris i de Recerca, Agencia Estatal de Investigación
Zero hunger
Openalex Percentile: Top 5%
Bioinformatics and Genomic Networks
4.44
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